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IJCST 23,1
Multi-purpose three-dimensional body form Sun Mi Park Iowa State University, Ames, Iowa, USA
8
Kueng Mi Choi Dong-Seoul College, Seongnam, South Korea
Received 16 March 2010 Revised 8 June 2010 Accepted 8 June 2010
Yun Ja Nam Seoul National University, Seoul, South Korea, and
Young-A Lee Department of Apparel, Educational Studies, and Hospitality Management, College of Human Sciences, Iowa State University, Ames, Iowa, USA Abstract Purpose – The purpose of this paper is to develop a multi-purpose body form that could be used to develop different types of garments by putting body skins with ease on the standard body form. Design/methodology/approach – Free form deformation method was used to generate a virtual model upon the basis of the averaged wire frame. The virtual model was made into a real-life model by a rapid prototyping (RP) process, and then, the standard body form was made by molding the RP. The 3D polygon shell for a body skin got flattened down to 2D patterns and made by a urethane material. Findings – The standard body form developed by using 3D body scan data better represented the characteristics of the body shapes than the previously hand-made ones. In addition, by standardizing the production of the body form itself, it is now possible to make body forms into the standards and be consistent in their qualities. Research limitations/implications – This paper presents the methodology of utilizing 3D body scan data in a garment design, which is possible by incorporating advanced 3D modeling technologies and 3D data of a human body in making body forms. For the mass production of a body skin, it is necessary to develop various special materials simulating soft tissues. Originality/value – The apparel industry can enjoy cost cutting effects by using this multi-purpose body form. A company does not have to spend money in purchasing different sizes and shapes of body forms, let alone saving the spaces to store them once purchased. Keywords Product development, Garment industry, Modelling, Skin (body), Virtual waste Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 1, 2011 pp. 8-24 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111096705
Introduction Garment fit is considered as a crucial element to garment quality and consumer satisfaction in the apparel industry. A body form, also called a “dress form or dummy,” serves as the foundation for a garment design, working as a vital element in various stages or processes of product development such as design, pattern and prototype development, and fit evaluation. In order to improve the consumer satisfaction of a garment fit, it is necessary for apparel companies to obtain various body forms that accurately represent This research project was supported by the 2005 research service project of the standardization division, led by the Ministry of Commerce, Industry and Energy of Korea.
the average size and shape of their target consumers. However, the current body/dress forms in the apparel industry are still unmet the needs of apparel professionals due to their limitations in terms of size and shape accuracy (Bye and LaBat, 2005; Fan et al., 2004; Loker et al., 2005; Tamburrino, 1992; Workman and Lentz, 2000). Two types of a body form have been widely used so far, which are: (1) “a standard body form” representing the exact shapes and dimensional data of a naked human body; and (2) a body form with a certain degree of ease in its dimensional data. The body form with ease is then again split into various subcategories such as Miss, Missy, and Mrs. The body form also comes as different types according to the type of end products such as jacket type, coat type, trousers type, and bathing suits type (Alvanon, 2009; Fabulousfit, 2009; Lee et al., 2002). However, several researches comment that apparel professionals have hesitated to purchase these body forms until now because of the high cost of them and the limited storage spaces to store them while the apparel industry does need a variety of body forms to meet consumer’s diverse needs (Cui et al., 2006; Koo and Lee, 2005). When people age, they have difficulties to find well-fitting garments, especially middle-aged women aged between 35 and 49 years and older adults aged 65 and over. Although they have diverse body shapes, ready-to-made garments have been pretty much designed based on the youth body forms (Kim, 2001). In our current aging society, there are higher demands for garment alterations and custom-made garments to fulfill the needs of this specific age group. Kim (2001) and Shim (2002) argued that the need of the body forms that well represented the shapes of middle-aged women was becoming more stressed than ever due to the expansion in the population of this middle-aged female consumers and the dramatic growth of aging consumer market. The purpose of this study is to develop a cost efficient multi-purpose body form that can be used to make many different types of garments by only putting body skins with ease on a standard body form. Specific research objectives are: . To establish the methodology to make a standard body form that better represents the body characteristics of middle-aged women. This will lead to enable the production of body forms with more standardized and consistent quality than before. . To develop the methodology to make body skins with ease for different types of a garment that has commercial feasibilities. Apparel companies can enjoy cost cutting effects to purchase body forms and solve the problem of limited storage spaces to store them by only using the various types of body skins. Literature review Virtual body modeling Three-dimensional (3D) body scanners have significant potential for the apparel industry. This technology provides speedy, consistent, and accurate data to redefine apparel sizing systems so that they more closely match the current shapes of human bodies (Ashdown et al., 2004; Istook and Hwang, 2001). Several researchers have focused on developing and examining 3D virtual body modeling to enhance garment fits (Kouchi et al., 2001; Lee and Magnenat-Thalmann, 2001; Mochimaru et al., 2000; Nam et al., 2006; Park et al., 2007).
Multi-purpose 3D body form
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Lee and Magnenat-Thalmann (2001) and Park et al. (2007) used a morphing technology to produce a virtual body model for a garment design. “Morphing” refers to a technology in which the identical landmark in two models are referred to first, and then the polygons around the landmarks are morphed into an average shape between the shapes of the polygons in the two models (Park et al., 2007). However, it turned out to be not as effective in dealing with female bodies as they were composed of softer lines and curves in their shapes, although this approach could be of help in dealing with male bodies with well-developed muscles, where the outline of the human body was more vivid. This led more difficult to determine the outstanding characteristics in their body forms. Kouchi et al. (2001) also discovered a way to develop body forms by modeling a virtual body using around 500 data points that were defined and based on anatomical landmarks. The technology developed by Digital Human Research Center in Japan was used to calculate the average form. Free form deformation (FFD) technique, one of commonly using techniques in computer graphics, was used to model the average body form. In the original FFD technique, control lattice points were defined around a 3D object; then, the 3D object was smoothly deformed by moving the control lattice points (Mochimaru et al., 2000). One limitation of this form is the inability to make a detailed body form because of the small number of data points. Nam et al. (2006) study composed an averaged wire frame by extracting cross-sectional and vertical data from 3D body scan data to produce a standard virtual body of women in their 20s. The virtual model was then generated by the basis of the averaged wire frame, which took the unique characteristics of the body shapes in the target groups and other elements of a garment design. This has led for the apparel industry to present more realistic body shapes of individuals compared with the limited version of body shape available previously. Pattern development through flattening 3D body scan data Previous researches have focused on the conversion of the 3D body scan data into a two-dimensional (2D) pattern development for a garment design (Bruner, 2004; Choi et al., 2007; Hong and Daanen, 2004; Jeong and Hong, 2006). 2D computer-aided-design (CAD) systems such as Gerber MTM and TNO MTM compose garment patterns through extracting 2D information such as a length or girth from 3D body scan data. This technique considers as the combination of conventional 2D working processes with 3D data. However, it failed in the efficient application of measurements in curves or surfaces, which were difficult to calculate in 2D, toward pattern making (Bruner, 2004; Hong and Daanen, 2004). Jeong and Hong (2006) sectionalized 3D body scan data in accordance with the design line and tried triangle simplifications on the sections to generate optimal pieces of triangular shapes. One of numerical ordinary differential equations, Runge-Kutta method, was utilized to flatten the triangular pieces onto 2D surfaces. However, still limited research has been completed to focus on linkages of 3D body scan data with 2D pattern development. In addition, clear methodologies have not been given to the apparel industry about the way to transfer 3D scan data to 2D CAD systems. Another method, called grid method, was employed by Choi et al. (2007) to flatten 3D body scan data into a 2D pattern. The first criterion was the unique characteristic of a human body, which was then used to identify the positions of darts and cutting lines,
while the next criterion was the simplification method of the data of each block. The eventual goal of this process was to maximize the level of efficiency in flattening by using the least amount of meshes. This method makes the two-way conversion of the data possible, which is that, the 3D body scan data can be flattened down to a 2D pattern, and then the 2D pattern can be restored to a 3D virtual model again.
Multi-purpose 3D body form
Multi-purpose body forms Various companies and laboratories, producing body forms such as Fabulousfit, Singer &Co., DonAngeli, Clover Fashion tec., and Human Solutions, have been actively engaged in research to develop multi-purpose body forms that could be shifted to fit garments well for different body shapes. Two basic methods that have been widely used to develop multi-purpose bodies were: (1) segment method which is adjusting the body sizes of various parts such as the bust, waist, and hips by increasing or decreasing the coverage of a certain segment in the body form (Clover Fashion tec., 2009; DonAngeli, 2009; Singer & Co., 2009); and (2) padding method which is changing the body shape to attach form pads with various shapes to necessary positions (Fabulousfit, 2009; Human Solutions, 2009). These two methods are shown in Figure 1.
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Figure 1(a) shows the example of a multi-purpose body form using the segment method, which was developed by Singer & Co. (2009). The basic body form is divided into horizontal and vertical segments. If the dial positioned on the bust, abdomen, and hip is turned, a segment of the basic body form stretches widthwise or longitudinally, changing the size. An example of multi-purpose body forms using the padding method is shown in Figure 1(b). A cover is put on the basic body form and a form pad of soft texture is then put inside the cover in order to change the shape of particular body parts such as bust or hip. Although the segment method has its advantage to scale the size, it is difficult to shift the shape of a certain part of the body. Meanwhile, the padding method is more
Back Width
(a)
(b)
Notes: (a) Segment method (Singer & Co, 2009); (b) padding method (Fabulousfit, 2009)
Figure 1. Two commercialized multi-purpose body forms
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efficient to change the shapes of certain parts but not as good at changing the size scale as the first one does. The existing multi-purpose body forms do not fully meet the level apparel companies require in terms of size and shape accuracy. Therefore, a continuous effort to develop multi-purpose body forms is necessary, which can represent the average body size and shape in a better way as well as to be more commercially available in apparel markets. Nam et al. (2006) recommended using the averaged wire frame-based, parametric virtual body making method, which was composed of transverse and longitudinal sections necessary for garment designs. Several merits of using this method compared to other virtual body making methods are: . possible to generate a virtual body with a range of body shapes by adjusting parameters related to composition of a garment; and . suitable for the purpose of improving the garment fit since it realistically expresses the shape of a human body such as posture as well as the average size of the target group of apparel companies. A flat pattern through flattening 3D body scan data by a grid method was developed by Choi et al. (2007). They elaborated the surface flattening process by the grid method, which made it possible to remodel between the 3D data and the 2D pattern and to convert the bidirectional data of the pattern development and can be presented as a method of automated patternmaking to manufacture garment patterns according to various designs. The main purpose of this study is not to develop a new virtual body model making method but to develop the methodology of creating a cost efficient multi-purpose body form that can be used to make many different types of a garment using 3D body scan data. Therefore, the algorithms that have already been developed by Nam et al. (2006) and Choi et al. (2007) were used to generate an averaged wire frame and 2D flat pattern for this study. Another rationale of using these two existing methods – averaged wire frame method and grid method – is to verify the appropriateness of these methods for commercialization in various age groups, not only for the age 20s that Nam et al. (2006) and Choi et al. (2007) focused in their studies. Research method Concept of multi-purpose body forms In the apparel industry, a body form is essentially required during the product development process, especially the stages of prototype development or fit evaluation. Therefore, apparel companies need to purchase different sizes of body forms to design their apparel products that meet the needs and desires of their target consumers. However, small or medium size apparel companies are somewhat reluctant to buy several body forms by different body shapes and sizes because of the limit of storage spaces and the high cost of each body form. In spite of currently existing commercialized multi-purpose body forms, apparel companies are not fully satisfied by the size and shape accuracy of these. In this study, a multi-purpose body form is developed, which is available for multiple purposes, in consideration of the demands from current apparel companies. Figure 2 shows the conceptual framework of this study to develop a cost efficient multi-purpose body form. The uniqueness of this proposed multi-purpose body form is
Multi-purpose 3D body form
Pregnant body skin
Cocktail body skin
13
Dress body skin
Coat body skin
Standard body form
Jacket body skin
Plus-sized body skin
Wire frame from 3D scan data
to develop a standard body form pertinent to the average size and shape of a target group and put a body skin including ease by different types of a garment on it. This standard body form is designed to reflect the average size and body shape of a target group by utilizing the virtual modeling techniques. The body skin is made by extracting a 3D polygon shell which is a difference in shape between the virtual model of body skin and that of standard body form, and then developing it into a 2D pattern. The advantage of the body skin developed in this study is the exact reflection of body size and shape demanded by apparel companies by the types of garments since it adopts a 3D design technology. Although this study only develops three types of body skins – plus-sized body skin, jacket body skin, and dress body skin – a variety of body skins may be made as required by apparel companies such as pregnant body skin and coat body skin in a long run. The initial body scan data obtained from a 3D body scanner are just composed of geometrical surface information. 3D modeling software, Rapidform for this study, is used to extract a cross section, get meaningful information including distance or angle of the cross section from the body scan data, and verify deviations of the shape. Using a commercially available 3D modeling software such as Rapidform, Polyworks, and
Figure 2. Conceptual map for the development of a multi-purpose body form
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Geomagic allows apparel companies or apparel researchers to develop their own multi-purpose body forms without spending time and effort to develop their own 3D modeling programs when following the methodology this study presents in this paper. Research sample An adult group that had a somatotype characteristic of middle-aged women, 35-49 years old, was purposefully selected for this study from the secondary data, SizeKorea 2004, that were obtained from the Korean National Anthropometric Survey during April 2003 to November 2004 by the Korean Agency for Technology and Standards (KATS) (KATS, 2004). The selection of this age group was based on age categories presented in Nam et al. (2006) study. They categorized ages as young group (18-24), young-adult group (25-34), and adult group (35-49). Among the data set, only 3D body scan data of 1,320 middle-aged women, aged between 35 and 49 years, were used for this study. Data analysis procedure This section includes the procedures of developing a standard body form and a body skin for middle-aged Korean women. Although this target age is chosen for this study, the procedures to develop a multi-purpose body form could be applicable to any other age group after the methodology is proved. Three important concepts that frequently use throughout this study are defined as: (1) Body form. A body form, also called a dress form or dummy, used by designers, tailors, and seamstresses to fit garments in work, or to try out designs or patterns (Mannequin Madness, 2010). (2) Ease. The allowance for body movement and design effect in a garment (MacDonald, 2002). (3) Body skin. An over-garment with ease in sizes that match the requirements of various types of a garment (defined by authors). Standard body form development. A standard body form is developed by the following production processes. Target group selection. The most critical elements of body size that best represents the characteristics of female bodies are the measurements of height (Hh), bust (B), waist (W), and hip (H) (Koo and Lee, 2005; Nam et al., 2006). A cross-tabular analysis of the Hh/B/W/H measurements was conducted in accordance with Korean Standard garment sizing standard to develop the size specification for middle-aged women (Korean Standard Association, 2004). Among the age range between 35 and 49 years old, the group of people who ranged in the middle of Hh/B/W/H measurements were first selected to be used for this study (Figure 3(a)). Averaged wire frame composition. An averaged wire frame was developed followed by the procedures introduced in Nam et al. (2006) study. The averaged wire frame of a target group was generated by taking 19 horizontal cross sections and four vertical section curves from the sample models. The distance from the center of a cross section to the curve was measured at an interval of five degrees and a mean value was obtained. A mean distance was connected in a spline curve which generates a mean cross section (Figure 4). To reflect the posture axis of the sample group, the following two measures were obtained:
Multi-purpose 3D body form
Shoulder Bust Waist Hip
15 Toroso body form
Knee ZC
Leg
YC
XC
Whole body form
(a)
(b)
(c)
(d)
(e)
Notes: (a) Target group; (b) averaged wire frame; (c) virtual model; (d) rapid prototyping; (e) body form
B
R
B
L
F
Figure 3. The processes of developing a standard body form
R
L
F
(1) a mean angle of the side line of the upper body which passed the lateral point of the shoulder and that of the waist; and (2) the side line of the lower body which passed the lateral point of the waist and the lateral ankle point. A total of 23 mean cross sections and two posture axes were then combined to complete an averaged wire frame (Figure 3(b)). Virtual model generation. A virtual model of the standard body shape for middle-aged women was generated upon the basis of the averaged wire frame (Figure 3(c)). The control lattice point of 3D polygon data was moved to correspond to the averaged wire frame by using FFD method. Rapid prototyping creation. RP can be defined as a group of techniques used to quickly fabricate a scale model of a part or assembly using 3D CAD data (Chua et al., 2004). RP was made to reproduce the standard virtual model designed in 3D virtual space into reality in its original size (Figure 3(d)). When RP was made, its principal elements of acrylonitrile butadiene styrene and supporter formed a layer at an interval of 0.25 mm (Stratasys, Inc. 2009). The water-soluble supporter was melted in water for removal during post-treatment. This real-life size RP creation was used as the basis of making a body form, which is the next stage of this process. Body form making and verification. Aconventional/traditional body form made by hands had its problems of inconsistency in sizes and the imbalances of shapes between
Figure 4. Example of generating an averaged cross section
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right and left sides of the body form (Cui et al., 2006; Koo and Lee, 2005). These matters could be resolved through building a resin/fiber glass (FRP) mold that serves as the fundamental framework of the body form by using the RP model. Urethane should be filled in the FRP frame made to maintain its strength. The whole body form was generated by the above molding method. The torso body form was created by connecting the area 100 mm beneath the crotch using the whole body form (Figure 3(e)). Consistency of the body form made to the virtual model needs to be verified using the following steps: (1) the body form shall be scanned; (2) the scanned data of body form and the shape of a virtual model needs to be overlapped; and (3) comparison on the deviation between both shapes needs to be completed. Body skin development. A standard body form is the nude body of a middle-aged woman without any ease in size. This study made it possible to use this standard body form for many types of a garment by wearing body skins with ease in sizes which match the requirements of various types of a garment. The total of three body skins was developed to include the size ease for the design of each type of the following garments: (1) Plus-sized body skin. A body skin with ease for the design of a garment larger than the standard body. (2) Jacket body skin. A body skin with ease for the design of a jacket. (3) Dress body skin. A body skin with ease for the design of a dress. Each type of body skins were developed by the following production procedures. Calculation of the necessary ease for body skins. The ease for the plus-sized body skin has been calculated by using the analysis outcome of the size specification of middle-aged women to make the body skin larger than the standard body by guide by the four differences. In addition, the ease of the jacket body skin and the dress body skin were calculated by analyzing the patterns from existing apparel companies, respectively. Generation of the wire frames and virtual models. With the ease from the previous stage, the wire frame was created to make the body skins. The standard virtual model was then adjusted to fit the wire frame in order to make three virtual models for each of the body skins by using FFD method. Flattening 3D polygon shell. From the body skin solid model, the standard body solid model was extracted by using the Boolean operation which added a solid to or subtracted a solid from another solid. Then, polygon shells were created at positions in a consistent distance, 1.1 mm or 2.3 mm, apart from the difference solid model’s surface by using the offset operation. The offset operation creates a new polygonal shell that is offset from the original. The “difference solid model” is supposed to have two or three polygon shells, in provision with their thickness. Finally, the 3D polygon shells got flattened down to 2D patterns by the grid method introduced in Choi et al. (2007) study. Body skin making. For the sake of efficiency in production and commercialization, it is required to cut down the production cost and to standardize the production process. An urethane material same as those used for a diving suit for divers was selected and used in this study for the above reason. This material is excellent in its shape relevance
against curved surfaces and easier to sew as well as consistent in its thickness and suitable for manufacturing in various thicknesses (Neoprene Sheets, 2009). The material was nylon/PU bonding which came in two different thicknesses, 1.1 mm and 2.3 mm. Verification. The body skin was lastly put on the standard body form and then scanned to be checked against the result of a virtual modeling to verify the shapes of the body skins.
Multi-purpose 3D body form
17 Result and discussion Standard body form development The size specifications of middle-aged women, 1,550/850/710/910, 1,600/880/740/940, 1,600/910/770/940, and 1,600/940/800/970[1] were developed by using the height (Hh)/bust (B)/waist (W)/hip (H) measurements. Among these size specifications, 1,600/880/740/940 specification was chosen because it was the average range for the target body shape group. An averaged wire frame for middle-aged women was developed by extracting cross-sectional and vertical data from the target group. Upon the basis of the averaged wire frame, a virtual model was generated. Both average size of the target group and the average shape of the body were realistically expressed in the standard virtual model. The virtual model was made into a real-life model by the RP process and then, the whole body form and the torso body form were made by molding the RP (Figure 3). In order to verify the shape of the standard body form, the differences in shape against the virtual model were analyzed. Since the deviation turned out to be a mere 2.05 mm, this study showed the consistency in body shapes between the standard body form and the virtual model (Figure 5). This could be in turn acknowledged as an excellent result in terms of the shape consistency and balance of the body form than the previously hand-made ones.
23.13988 20.82589
Total distribution: 99.97572%
18.81190 16.19792 13.88393 11.56994 9.25595 6.94196 4.62798 2.31399
Average
0.00000
Shell / Shell Deviation Analysis Result (units: mm) Minimum distance Maximum distance Average distance Standard deviation
0 23.70 2.05 2.00
Front
Side
Note: 3D models present the shape deviation of body form and virtual model
Back
Figure 5. Shape verification of the standard body form
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Body skin development The ease of three types of body skins developed in this study is presented in Table I. Among various areas of the body, all size of plus-sized body skin was bigger than that of the standard body form except the shoulder slope. The analysis of the jacket patterns from apparel companies revealed that there are the necessary minimum amounts of the ease, such as 954 mm for the chest, 928 mm for the bust, 849 mm for the under bust, 799 mm for the waist, and finally, 970 mm for the hips. Dress body skin was similar to the standard body form except for the bigger sizes for the bust to keep the well-fitted body shape of a dress intact. With the ease for body skins, three different wire frames were designed and virtual models in responses were generated. Figure 6 shows the generation of the wire frames and virtual models for three different body skins: plus-sized body skin, jacket body skin, and dress body skin. The plus-sized body skin was made up of three polygon shells, each of which was then flattened down to a 2D pattern. The polygon shell at the outermost surface was made in 1.1 mm thickness, while the other two were in 2.3 mm in thickness (Figure 7). In case of the jacket body skin, it was composed of two polygon shells of 2.3 mm thickness (Figure 8). Figure 9 shows the dress body skin consisting of a polygon shell of the standard body with 1.1 mm thickness and the polygon shell covering the bust segment with 2.3 mm thickness. The bust’ pattern was flattened in four pieces, respectively, for the upper, lower, left, and right segments of the bust point at the center. The result of the analysis for the shape deviation between body skin and the virtual model showed 5.43 mm average distance for plus-sized body skin, 4.47 mm average distance for jacket body skin, and 4.28 mm average distance for dress body skin (Figure 10). This can be interpreted as virtual model and body skin was almost identical. This finding leads into several research and practical opportunities for future work. These possibilities will be addressed in the following section of “Conclusion and implications.” Conclusion and implications The purpose of this study was to present a possibility to produce a cost efficient multi-purpose body form that can be used to make many different types of a garment by putting body skins with ease on the standard body form. The standard body form,
Standard body form Measurement dimension
Table I. Ease for body skins
Chest circumference Bust circumference Under bust circumference Waist circumference Waist circumference (omphalion) Hip circumference Waist back length Neck shoulder point to breast point Posterior shoulder length Shoulder slope (8)
930 913 789 754 819 938 372 262 383 22
Plus-sized body skin Size Ease 937 926 802 788 837 943 392 273 399 22
þ7 þ 13 þ 13 þ 34 þ 18 þ6 þ 20 þ 11 þ 16 –
Jacket body skin Size Ease 954 928 849 799 843 970 376 257 401 20
þ24 þ15 þ60 þ45 þ24 þ25 þ4 25 þ18 22
Note: The unit of analysis is based on the metric measurement system (unit: mm)
Dress body skin Size Ease 930 938 792 754 819 945 372 262 383 22
– þ 25 þ3 – – – – – – –
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(a)
(b) F Bust cross section
B (c) Notes: (a) Plus-sized body skin; (b) jacket body skin; (c) dress body skin
developed by using 3D body scan data, better represented the characteristics of the body shapes than the previously hand-made ones. In addition, it is now possible to make body forms into the standards and consistent in their qualities. The standard body forms are expected to enhance the garment fits once they are chosen for the basis of pattern designs for the middle-aged women’s garments. Three types of body skins developed in this study were made of an urethane material for the sake of efficiency in production and commercialization. The apparel industry could be enjoying cost cutting effects as it does not have to spend money in purchasing different types of bodies, let alone saving the spaces to store them once purchased. The body skin production method has a higher chance of
Figure 6. Generation of the wire frames and virtual models for body skins
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1st Polygon shell (1.1 mm thickness)
2nd Polygon shell (2.3 mm thickness)
Front
Figure 7. The process of flattening and making a plus-sized body skin
Side
Back
Plus-sized body form
3rd Polygon shell (2.3 mm thickness)
1st Polygon shell (2.3 mm thickness)
Figure 8. The process of flattening and making jacket body skin
Front
Side
Back
Jacket body form 2nd Polygon shell (2.3 mm thickness)
commercialization as it gives more efficiency to manufacture as well. Although only three types of body skin were developed for this study, the methodology suggested in this study could be applicable to any other type of a body skin required during the product development.
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1st Polygon shell (1.1 mm thickness)
Front
Side
Back
2nd Polygon shell (2.3 mm thickness) Dress body form
Figure 9. The process of flattening and making a dress body skin
23.00000 20.70000
Maximum distance: 22.96 mm Average distance: 5.43 mm Standard deviation: 3.56 mm
18.40000 16.10000 (a) 13.80000 11.50000 9.20000
Maximum distance: 15.34 mm Average distance: 4.47 mm Standard deviation: 2.72 mm
6.90000 4.60000 (b) 2.30000 0.00000
Maximum distance: 22.28 mm Average distance: 4.28 mm Standard deviation: 3.01 mm
(c) Notes: 3D models present the shape deviation of body skins and virtual models; (a) plus-sized body skin; (b) jacket body skin; (c) dress body skin
Figure 10. Shape verification of the body skins
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Two main limitations of this study were: (1) the material used for a body skin; and (2) the research sample used. For this study, the body skin was made of an urethane material same as those used for the diving suit for divers; however, for the mass production of the body skin, it is needed to develop various special materials simulating the soft tissue in a long run. Various sewing techniques such as seamless sewing also needs to be explored because the body skin consists of some layers which have different thickness and it does not have a smooth surface. Further study needs to be conducted for the development of a body skin which does not have several layers but have a foam. The subjects of this study were limited to the middle-aged Korean women; therefore, the subsequent study should be progressed for men and women of various ages and races across the nations. The results of this study could be implemented by apparel manufacturers who produce garments for middle-aged women to inform pattern making and garment construction in a long run. Further, the findings can be applied to other consumers under different age categories as well as special population (i.e. obese or overweight individuals). The main purpose of this study was to develop the methodology to make a multi-purpose body form by utilizing an easily accessible 3D modeling software in a current market. If apparel researchers or professionals in the apparel industry wants to adapt the methodology this study proposed, they can easily use this methodology without spending their time and effort to develop their own 3D modeling algorithms. In addition, for any apparel company trying to develop a body skin, the procedures in this study are helpful for a company just to follow the process provided in this study and use it to help develop its products. The 3D virtual body modeling technology can make further contribution in the future by providing a fundamental technology to develop virtual fitting models for an internet shopping as well. References Alvanon (2009), “Alvaform soft series”, available at: www.alvaforms.com/catalog/index. php?cPath¼203 (accessed 9 November 2009). Ashdown, S.P., Loker, S., Schoenfelder, K. and Lyman-Clarke, L. (2004), “Using 3D scans for fit analysis”, Journal of Textile and Apparel, Technology and Management, Vol. 4 No. 1, pp. 1-12. Bruner, D. (2004), “Applications of 3D white light body scanning”, Fashion Information and Technology, Vol. 1, pp. 20-7. Bye, E. and LaBat, K. (2005), “An analysis of apparel industry fit sessions”, Journal of Textile and Apparel, Technology and Management, Vol. 4 No. 3, pp. 1-5. Choi, Y., Nam, Y., Choi, K. and Cui, M. (2007), “A method for garment pattern generation by flattening 3D body scan data”, in Duffy, V.G. (Ed.), Proceedings of the 1st International Conference on Digital Human Modeling, DHM 2007, Beijing, China, July 2007, Lecture Notes in Computer Science 4561, Springer, Berlin, pp. 803-12. Chua, C.K., Leong, K.F. and Lim, C.S. (2004), Rapid Prototyping: Principles and Applications, 2nd ed., World Scientific, River Edge, NJ. Clover Fashion tec. (2009), “Multi size fitting body”, available at: http://203.251.80.101/product/ product_1.htm (accessed 9 November 2009).
Cui, M., Jung, K., Nam, Y. and Choi, K. (2006), “A basic study on the product development of dress forms”, Journal of the Korean Society for Clothing Industry, Vol. 8 No. 3, pp. 317-25. DonAngeli (2009), “My double adjustable dress forms”, available at: www.donangeli.co.uk/ Diana-Small-and-Medium_AO2M.aspx (accessed 9 November 2009). Fabulousfit (2009), “Patented fitting system”, available at: www.fabulousfit.com/ (accessed 9 November 2009). Fan, J., Yu, W.W. and Hunter, L. (2004), Clothing Appearance and Fit: Science and Technology, Woodhead, Cambridge. Hong, S. and Daanen, H. (2004), “3D scan related research in TNO and its application for apparel industry”, Fashion Information and Technology, Vol. 1, pp. 20-7. Human Solutions (2009), “Human Solutions develops individual fashion manikin for garment industry”, available at: www.human-solutions.com/apparel/press_report_en.php?id¼322 (accessed 9 November 2009). Istook, C.L. and Hwang, S. (2001), “3D body scanning systems with application to the apparel industry”, Journal of Fashion Marketing & Management, Vol. 5 No. 2, pp. 120-32. Jeong, Y. and Hong, K. (2006), “Development of 2D tight-fitting pattern from 3D scan data”, Journal of the Korean Society of Clothing and Textiles, Vol. 30 No. 1, pp. 157-66. KATS (2004), The 5th Size Korea Report, Korean Agency for Technology and Standards, Seoul. Kim, S. (2001), “Production model development of mass customized clothing for middle-aged women”, doctoral dissertation, Ewha Womans University, Seoul. Koo, M. and Lee, J. (2005), “Standardized body type and the suitability of figures for the twenties women”, Journal of the Korean Society for Clothing Industry, Vol. 7 No. 6, pp. 601-8. Korean Standard Association (2004), “Sizing systems for female adult’s garments”, KS K0051-2004, Korean Standard Association, Seoul. Kouchi, M., Mochimaru, M. and Ito, Y. (2001), “Development of a new dressmaking dummy based on a 3D human model”, paper presented at Scanning Congress 2001: Numerization 3D Session, 4-5 April, Paris, available at: www.dh.aist.go.jp/en/research/centered/ dressdummy/ (accessed 8 November 2009). Lee, S., Kim, K., Nam, Y., Noh, H., Jung, M., Choi, K. and Choi, Y. (2002), The Apparel Somatology, Kyohakmunkusa, Seoul. Lee, W. and Magnenat-Thalmann, N. (2001), “Virtual body morphing”, Proceedings of IEEE Conference on the Computer Animation, 2001, The 14th Conference on Computer Animation, 7-8 November, IEEE, Seoul, pp. 158-66. Loker, S., Ashdown, S.P. and Schoenfelder, K. (2005), “Size-specific analysis of body scan data to improve apparel fit”, Journal of Textile and Apparel, Technology and Management, Vol. 4 No. 3, pp. 1-15. MacDonald, N.A. (2002), Principles of Flat Pattern Design, Fairchild, New York, NY. Mannequin Madness (2010), “Mannequin terminology”, available at: http://blog.mannequin madness.com/terms-and-descriptions-about-mannequins/ (accessed 6 January 2010). Mochimaru, M., Kouchi, M. and Dohi, M. (2000), “Analysis of 3-D human foot forms using the free form deformation method and its application in grading shoe lasts”, Ergonomics, Vol. 43 No. 9, pp. 1301-13. Nam, Y., Choi, K. and Park, S. (2006), “3D human body modelling using 3D scan data”, Fiber Technology and Industry, Vol. 10 No. 3, pp. 251-8. Neoprene sheets (2009), “Neoprene sheets, neoprene rolls, neoprene fabric”, available at: www. foamorder.com/neoprene.html (accessed 1 June 2010).
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Park, S., Nam, Y. and Choi, K. (2007), “A study of 3D virtual fitting model of men’s lower bodies in forties by morphing technique”, Journal of the Korean Society of Clothing and Textiles, Vol. 31 No. 3, pp. 463-74. Shim, J. (2002), “A study on somatotype classification of the late middle-aged women”, Journal of the Korean Society of Clothing and Textiles, Vol. 26 No. 1, pp. 15-26. Singer & Co. (2009), “Adjustable dress forms and sewing dummy”, available at: www.uksewing. com/Dress-Form-/-Mannequin/c23/index.html (accessed 9 November 2009). Stratasys (2009), “Fused deposition modelling technology”, available at: www.stratasys.com/ Technology.aspx (accessed 9 November 2009). Tamburrino, N. (1992), “Apparel sizing issues – part 1”, Bobbin, Vol. 33 No. 8, pp. 44-6. Workman, J.E. and Lentz, E.S. (2000), “Measurement specifications for manufacturers’ prototype bodies”, Clothing and Textiles Research Journal, Vol. 18 No. 4, pp. 251-9. Corresponding author Young-A Lee can be contacted at:
[email protected]
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Technical textiles as a new route to enhance orthopedic casts’ properties Fawzy Sherif and Hartmut Roedel Mechanical Engineering Faculty, Institute of Textile Machinery and High Performance Materials Technology (ITM), Dresden University of Technology (TUD), Dresden, Germany
Orthopedic casts’ properties
25 Received 23 June 2010 Accepted 10 August 2010
Abstract Purpose – The casts sector is an important sector for orthopaedic textile products. Plaster and plastics casts are widely used in hospitals, pharmacies and health care centers, but they are heavy, not washable and do not offer a suitable fixation for bone fractures (e.g. hand wrist), especially when operated under different swelling conditions. After decreasing of the swelling, the cast is in a hard form and the stabilization effect of the cast is insufficient due to the occurring of distance between the skin and the cast. The purpose of this paper is to develop a new pneumatic cast that depends on Polyvinylchlorid coated fabric as an outer layer, skin friendly internal layers, an air chamber, and metal braces. Design/methodology/approach – For more comfort, the cast is anatomically formed and the internal layers are made of cotton-viscose fabrics and Polyester spacer fabrics. The pressure on the injured part can be controlled by using a pneumatic structure. Findings – The characteristics of the developed pneumatic cast are found to be: easy to use, comfortable, washable, and light weight. Originality/value – The paper describes the development of a new pneumatic cast that can overcome the difficulties of cast fixation with the injured part of the body: an economic product, that should be easy to use, light weight, comfortable, skin friendly, water resistant, easy to clean, and affordable. Keywords Textile technology, Medical appliances, Orthopaedics, Limbs Paper type Research paper
1. Introduction 1.1 Technical textiles The world textile industry is moving rapidly toward the manufacture of high-added value textile structures and products (Czajka, 2005). Medical textiles are one of the most rapidly expanding sectors in the technical textile market, and hosiery products with medical industry applications are among a long list of textile products being consumed in the textiles market. The medical applications of technical textiles are widely used nowadays in several fields such as health care, extra corporal devices, surgical applications, and orthopedic products (Meena, 2010). 1.2 Bones fractures A fracture can be defined as a complete or incomplete break in a bone resulting from the application of excessive force or disease. The fundamental principle of the bones fractures classification is the division of all fractures of a bone segment into three types and their further subdivision into three groups and corresponding subgroups, and the
International Journal of Clothing Science and Technology Vol. 23 No. 1, 2011 pp. 25-33 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111096714
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arrangement of these in an ascending order of severity according to the morphologic complexities of the fractures, the difficulties inherent in their treatment, and their prognosis (Spatz, 2005). 1.3 Hand radius fracture The main goal of bones fractures treatment is to restore the normal form and the continuity of the bone and return to the complete usability to the injured part. The purpose requires two kinds of treatments according to the fracture type; the first is a conservative treatment and the second is operative treatment. This study makes more focus on the hand radius fracture (hand wrist) which is the most often fracture and acts between 10 and 25 percent of all fractures. Women are concerned up to three times more often than men (Katavic, 2003). In a typical radius fracture, a quick swelling appears and the whole wrist region is painful. Most of breaks become immobilized in stable gypsum form (plaster) for four-six weeks (Fricker, 2009). 2. Motivation 2.1 Casts as a treatment of bones fractures 860 AD Rhazes, an Arabian doctor, used casts which were made of lime and in 1814 was the first therapeutic application of a gypsum liquid in Europe (Schleikis, 2007). Gypsum or plaster is the common material of casts because it is cheap, applicable with all individual cases and releases none toxic or allergic reactions to the skin (Voltz, 1996). In 1955, was the first try of using plastics casts that consists of a glass fiber material, which impregnated with cellulose acetate, it is a modern synthetic cast that uses a fabric and a resin together (Schleikis, 2007). This cast is light weight, very hard, and X-ray porosity. Recently, there are some kinds of casts that depends on the fluid technique such as the pneumatic cast and the vacuum cast, both of them depends on an air chamber that made of plastic or rubber and mainly offered for arms and legs in different dimensions. 2.2 Disadvantages of plaster and plastics casts Some of disadvantages of the plaster cast are that it is heavy, not washable and difficult to use. Also, the plastic cast has some disadvantages like high cost and skin irritation. The main disadvantage of both of them is that they do not offer a suitable fixation for bone fractures during the different swelling conditions. After swelling decrease, the cast will be in a hard form and the stabilization effect of the cast is insufficient because of the distance which occurs between the skin and the cast (Figure 1).
Plaster or plastic
Figure 1. Distance change (a) between the skin and the cast during (left) and after the swelling (right)
Skin Bones a
a
3. Goals The objectives of this study are: . Developing a new pneumatic cast that can overcome the difficulties of the cast fixation with the injured part of the body. . Realization of permanent stabilization by using a pneumatic support structure during and after the swelling. . Improvement of the physiological behavior of the available pneumatic casts by using innovative and comfortable textiles. . Producing an economic product, that should be easy to use, light weight, comfortable, skin friendly, water resistant, easy to clean, and with a good price.
Orthopedic casts’ properties
27
4. Development of a new pneumatic cast 4.1 Concepts of the developed cast The developed cast presented in this study is designed and manufactured by ITM Institute, Dresden University of Technology (TU Dresden), Germany for the hand radius fracture as a sample of bones fractures. This developed pneumatic cast depends on some concepts that help it to provide the required pressure, stabilization and comfort levels, especially after swelling decrease. These concepts are: . The hand will be inside a pneumatic structure that will provide a required pressure on the radius fracture. . The pneumatic structure depends on an air chamber that can be pumped and offer a controlled pressure on the radius fracture. In addition, there are two metal braces under the hand for more stabilization to the cast. . The outer layer of the cast is made of Polyvinylchlorid (PVC) coated fabric, and the internal layers are made of cotton-viscose and Polyester (PES) spacer fabrics to be more flexible and comfortable to the skin (Elsner, 2003) (Figure 2). 4.2 Design and manufacturing of the cast By using the 3D design, the pattern of the cast is anatomically built in two categories of sizes (A) and (B) and every category includes two sizes; the first category (A) includes sizes S and M, and the second category (B) includes sizes L and XL (Table I). Only one cast is available for more sizes in the same times. The basic measurement of all sizes is
Coated fabric Cotton-viscose
Value
Hand Air chamber
Spacer fabric
Figure 2. Components of the developed pneumatic cast
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28
the wrist circumference, beside other sub measurements such as underarm circumference, corpus circumference and the length of the cast. The cast consists of two basic parts: front part (Figure 3) and back one (Figure 4). The front part contains an outer layer made of PVC coated fabric with indirect contact to the skin, air chamber that made of rubber coated fabric and contains a valve, and an internal layers that include; cotton-viscose fabric which is in a direct contact with the skin, and PES spacer fabric which makes more flexibility and comfortable to the skin. In addition, the cast has an external pumping system in order to pump air into the air chamber that causes the pressure on the radius fracture. The pneumatic structure includes a manometer with a pump and a rubber tube with a needle. The back part of the cast contains also the same outer layer (PVC coated fabric) and the same internal layers (cotton-viscose fabric and PES spacer fabric) of the front part. In addition, the back part includes two metal braces that are anatomically formed as the hand in order to provide more stabilization to the cast under the hand. These two metal braces can be removed while washing or showering during a horizontal hole in the bottom of the cast. During pumping, the internal layer moves towards the radius fracture in order to realize a continuous pressure on the radius fracture after decrease of swelling and this is the main mission of this developed cast. In the modified model of the cast (Figure 5), it can be seen that more holes in the front part of the cast are made in order to enhance the breathable behavior of the hand. Category
Size (wrist)
A Table I. Categories of the cast sizes
S M L XL
B
Valve
Figure 3. Front part contents
Front
Air chamber
15-17 .17-19 .19-21 .21-23
Orthopedic casts’ properties
29
Back
Figure 4. Back part contents
Figure 5. Modified cast
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30
5. Experiments and results 5.1 Materials In order to choose suitable materials for the cast, they should have special properties. The outer layer and the air chamber fabrics should be flexible, thinly, easy to clean, washable and light weight, because it affects directly on the total weight of the cast which should be not heavy. As shown in Table II, several controlling tests, such as bending rigidity, weight and thickness, have been operated to several fabrics in order to choose the suitable fabric for the outer layer of the cast and the air chamber. As a fabric for the outer layer of the cast, Heytex 55128 PVC coated fabric was used because of its lowest weight, thickness, and bending rigidity. But the fabric of the air chamber should be lighter and more flexible than the outer layer because it expands during pumping; therefore, Pto.E rubber coated fabric has been used as a material for the air chamber. 5.2 Adhesive materials for the air chamber The normal sewing technique is not suitable to build the air chamber because of the effect of the holes created by the needle during sewing; also the welding technique is not suitable for building the air chamber because of the non-thermo plasticity of the rubber coated fabric which has been selected for the air chamber. Therefore, the adhesive technique has been used to build the air chamber. Table III shows several adhesive materials that depend on several chemical basic components. Seam strength test has been operated for all adhesive materials, and Figure 6 shows that Proma Kleber adhesive material scored the highest value of seam strength and elongation; therefore, it has been used as a bonding material for the air chamber.
Table II. Tested fabrics for the outer layer and the air chamber of the cast
Table III. Tested adhesive materials for the air chamber of the cast
Fabric
Coating
Weight (g/m2)
Valmex 7318 Valmex 7316 Heytex 55128 Heytex 3561 Pto.E 13-606-48
PVC PVC PVC PVC NBR-Blend
1,000 630 600 700 580
Bending rigidity (mN *cm)
Thickness (mm)
Thermo-plasticity
120.68 113.23 63.54 80.75 20.96
0.9 0.7 0.5 0.6 0.5
Yes Yes Yes Yes No
Note: NBR, Nitrile Butadiene Rubber
Material
Chemical basic component
Jowatherm 630 SC 4000 Proma Kleber Magnumbond UHO flexible
PUR Polychloroprene Cyanacrylat Cyanacrylat PUR
Note: PUR, Polyurethane
Seam strength (N)
Elongation (%)
162.6 416.6 651.7 378.9 175.7
1.3 7.9 9.9 5.9 2.4
Orthopedic casts’ properties
700
Seam streangth (N)
600 500 400
31
300 200 100 0 Jowat 630
SC 4000
Proma Kleber Magnumbond Adhesive material
UHO Flexible
5.3 Pressure on the skin Compression on the skin caused by medical socks or several casts is a very important factor to evaluate the medical product because it will directly affect the blood circulation. Most of recently scientific researches recommended that the maximum pressure that can be pressured on the skin is 30 mmHg. The British Standard (BS 7505) classified the pressure ,20 mmHg is mild (Partsch, 2008), and the pressure up to 60 mmHg is very strong. Therefore, the pressure of the developed cast has been tested by Argus junior tester. There are two kinds of pressures; the first is pressure of the cast that caused by air pumping, and the second is pressure on the skin that caused by the cast with or without pumping. In order to find the effect of the cast pressure on the skin during and after the swelling, the values between 0 and 100 mmHg of the cast pressure are measured by the external pumping system have been scored by the Argus junior tester in case of without swelling (Figure 7). In order to make a simulation to the swelling, the wrist has been covered with some textiles layers that simulate the swelling thickness. The pressure on the skin during the swelling (without pumping) was 20.8 mmHg. But after the decrease of swelling, the pressure on the skin was reduced to 7.8 mmHg, suggesting that 13 mmHg as a pressure value on the skin (the difference between during and after swelling) is required to be pumped after the decrease of swelling in order to realize a constant enough pressure on the hand radius fracture during and after swelling. This value of pressure is equal to 32 mmHg of the cast pressure, and the maximum allowed value according to The British Standard classification (referred above) is equal to 70 mmHg of the cast pressure, more than this value is not comfortable for the blood circulation. 5.4 Washing cycles Washing test is one of the important tests that help to evaluate efficiency of the seam of the air chamber during a number of washing cycles in order to maximize the number of washing cycles. Because of the hygiene concept, the samples have been washed at 608C up to 15 washing cycles, and the washing test has been operated according to standard (DIN EN ISO 6330). The seam pressure resistance has been tested by the Textest FX 3000 water proof tester according to standard (DIN EN 1734), the obtained results were
Figure 6. Seam strength of the adhesive materials
32
45 Pressure on the skin (mmHg)
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40 35 30 25 20 15 13 10 5
Figure 7. Effect of cast pressure on the skin
0 20
32
40
60 70 80 Cast pressure (mmHg)
100
Note: Without swelling
in cmH2O pressure unit and converted to mmHg pressure unit for easy analysis (Figure 8). The sample before washing scored 663 mmHg which is the highest value of pressure resistance. The sample after 15 washing cycles scored 45 mmHg which is the lowest value of pressure resistance. As shown in Figure 7, the required pressure on the skin after decrease of swelling is only 32 mmHg of the cast pressure, suggesting that the cast can be washed up to 15 washing cycles. 6. Conclusion . Plaster and plastic casts are heavy, not washable and do not provide required pressure to the broken bones after decrease of the swelling. . The newly developed pneumatic cast depends on an anatomic form, pneumatic structure, metal braces, and innovative textiles. . The air chamber (above the hand radius) and the metal braces (below the hand radius) provide more stabilization for the hand.
Figure 8. Seam pressure resistance of the air chamber during washing cycles
Seam pressure resistance (mmHg)
700 600 500 400 300 200 100 0 b.Washing 1. WC 3. WC 5. WC 7. WC 9. WC 11. WC15. WC Washing cycles
.
.
. . . .
PVC coated fabric is the outer layer of the cast and the air chamber made of rubber coated fabric. As a comfort concept for the cast, the internal layers are cotton-viscose and PES spacer fabric, and also many holes for more breathing. Recommended washing cycles are up to ten times and up to 608C. It is easy to control the pressure on the hand by using the external pump system. Recommended maximum pressure by the external pump system is 70 mmHg. Some parameters of the developed cast, such as physiological behavior, valve efficiency and the cost, are still in progress.
References Czajka, R. (2005), “Development of medical textile market”, Fibers and Textiles in Eastern Europe, Vol. 13 No. 1, pp. 13-15. Elsner, P. (2003), Textiles and the Skin, Karger, Basel. Fricker, R. (2009), “Radiusfraktur, Handgelenksnahe Speichenbru¨che. Klinik fu¨r Orthopa¨dische Chirurgie und Traumatologie des Bewegungsapparates”, Kantonsspital Bruderholz, available at: www.bruderholzspital.ch/files/sideboxcollection/Radiusfraktur.pdf (accessed 19 April 2010). Katavic, J. (2003), Problematik der in Fehlstellung ausgeheilten distalen Radiusfraktur, doktorat dissertation, Universita¨t Ulm, Ulm. Partsch, H. (2008), “Classification of compression bandages”, American Society for Dermatologic Surgery, Vol. 34 No. 5, pp. 600-9. Schleikis, A. (2007), Gips und Synthetischer Stu¨tzverband, Steinkopff, Darmstadt. Spatz, H. (2005), Praxisbuch Unfallchirurgie, Teil 2, Springer, Heidelberg. Voltz, T. (1996), Gips- und Stu¨tzverba¨nde, Gustav Fischer, Stuttgart. Further reading Meena, C.R., Ajmera, N. and Sabat, P.K. (n.d.), “Medical textiles”, Fiber 2 Fashion, available at: www.fibre2fashion.com/industry-article/4/330/medical-textiles1.asp (accessed 20 May 2010). Corresponding author Fawzy Sherif can be contacted at:
[email protected]
To purchase reprints of this article please e-mail:
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Orthopedic casts’ properties
33
The current issue and full text archive of this journal is available at www.emeraldinsight.com/0955-6222.htm
IJCST 23,1
Study of the influence of matter and finishing treatments on the denim garment shade
34
Faouzi Khedher, Soufien Dhouib, Slah Msahli and Faouzi Sakli
Received 9 November 2009 Accepted 5 June 2010
Textile Research Unit of ISET Ksar-Hellal, Ksar-Hellal, Tunisia Abstract Purpose – The purpose of this paper is to study the effect on the cloth shade of matter, laundering types, special treatments and their succession applied during the manufacturing process of garment washing. Design/methodology/approach – Denim garment manufacturers are interested in finishing cloth to characterize the aging look of the cloth. The effect of matter, laundering, special treatments and their succession were studied. The treatments have been done on manufactured trousers. One rigorous statistical study is achieved to validate the experimental results. Findings – The mixed washing is the most degrading for the shade of cloth and appearance of the garment’s surface and the succession of special treatments of finishing is demanded to have an increasing whiteness. The finishing resin-treatment realized before any washing process (stone washing or mixed washing) provokes a slight increase of garment colour resistance. Practical implications – Information in this paper will aid manufacturers garment washing jeans in selecting the finishing method that suits their marketing/manufacturing plants. Originality/value – Garment washing is a technology incorporated by garment manufacturers to be able to provide a product in response to consumer’s wants. This study of the effect of matter, washing type, special treatments and their succession on garment denim blue jeans shade provides garment manufacturers with information about the methodical line of finishing to obtain the wanted cloth shade. Keywords Garment industry, Fabric production processes, Cotton, Textile technology Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 1, 2011 pp. 34-45 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111096723
Introduction Denim jeans evolved into a part of the fashion range, its success is due to its ability to change with every social and cultural evolution (Spevack, 1997, p. 7). Denim garment manufacturers are interested in finishing cloth that consumers want to purchase. Consumer demand for jeans with aged look began a revolution in denim processing (Hargraves et al., 1991). To characterizes the ageing look of the cloth, it is very important to start by quantifying the visual aspect (shade [. . .] ). Launderings and special treatments are the most important parameters influencing the cloth shade and the final aspect of denim jeans. In spite of the increasing of the product development process in finishing garment denim blue jeans, studies in this subject are not as numerous as the one on fabrics and the more parts among them treat the influence of the home laundering on some mechanical properties (Higgins et al., 2003a, b; Militky and Bajzik, 1997; Card et al., 2006). Indeed studies led on finishing garment denim blue jeans that treat the effect of special treatments in the industrial conditions are very limited or nearly hopeless. Thus, we were interested first to study the effect of matter, types of launderings (stone wash, enzyme wash, mixed wash and rinse), special treatments (brushing, sanding, resin-treatment, bleach-treatment, permanganate-spray and softening) and their
succession applied during the manufacturing process of garment washing on cloth shade. In a second part a rigorous statistical study is achieved to validate the experimental results. Experimental method Four types of denim fabrics were selected for this study. The selected fabrics differ by their weight (medium weight fabric and heavy weight fabric), the fabric finishing process (mercerized fabric and no mercerized fabric) and the matter composition (cotton and cotton elastane). The fabrics were finished with the same line of finishing (mercerization, skewness, sanforization). A summary of the fabric properties used in this study is given in Tables I and II. The treatments have been done on manufactured trousers from these four fabrics according to a well definite experience plan (Phan-Tan-Luu, 1993; Table III). So each sample was finished by different processes of washing and some special treatments before ending with a cationic softening (Tables III and IV). The measures of the colour coordinates (L, a *, b *) (Roderick, 1997; Mclaren and Rigg, 1976) and the reflectance spectrum have been achieved on a dual-beam spectrophotometer “SPECTRAFLASH 300 (SF 300) of Datacolor International”.
Mass/area (g/m2)
Fabric code
Composition
T1 T2 T3 T4
95% cotton, 5% elastane (on weft) 100% cotton 100% cotton 100% cotton
Fabric code Dyeing of warp yarna T1 T2
Seven indigo baths One sulfur bath and seven indigo baths
350 350 350 421
Concentration of dyeing bath (g/l) Indigo 0.46 0.61
– C1: 1.15 C2: 3.50 C3: 5.00
T3
One sulfur bath and seven indigo baths
0.61
C1: 1.15 C2: 3.50 C3: 5.00
T4
One sulfur bath and seven indigo baths
0.45
C1: 25 C5: 25
35
Fabric finishing Mercerized No mercerized Mercerized No mercerized
Sulfur
Denim garment shade
Table I. Fabric specifications
Colours Sulfur – C1: black greenness C2: blue redness C3: green yellowness C1: black greenness C2: blue redness C3: green yellowness C1: black greenness C5: clear blue redness
Note: aWe recall in this level that the weft yarn of denim fabric are not dyed and that the warp yarn are dyed ring-shaped and not in mass
Table II. Dyeing of warp yarn
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L, a *, b * values of a treated sample are obtained by the relationships between Xn, Yn and Zn where:
36
L* ¼ 116ðY=Yn Þ1=3 2 16
ð1Þ
a* ¼ 500½ðX=Xn Þ1=3 2 ðY=Yn Þ1=3
ð2Þ
b* ¼ 200½ðY=Yn Þ1=3 2 ðZ=Zn Þ1=3
ð3Þ
Xn, Yn and Zn are the tristimulus values, for a particular standard illuminant and observer, for a sample reflecting 100 percent of the light at all wavelengths. The lightness of the sample is represented by L * on a scale running from zero for black to 100 for white. The other attributed can be represented on a plot of b * against a *. Neutral colours plot close to the origin for any illuminant (a * ¼ b * ¼ 0) (Figure 1). The dyestuff concentration of the dyed fabric samples where calculated by the relationships between K and S (Mclaren and Rigg, 1976; Shukla and Dhuri, 1992; Derbyshire and Marshall, 1980): Klt ð1 2 Rl Þ2 ð1 2 Rlt Þ2 ¼ 2 Sl 2Rl 2Rlt
ð4Þ
where: Rl : Reflectance of dyed sample. Rlt : Reflectance of no dyed sample. Klt : Absorption coefficients (light absorbance). Sl : Scattering coefficients (light reflectance). K/S : Dyestuff concentration of the dyed fabric samples. We completed our work by one statistical study while using the factorial experience plan presented in Table III. The choice of these treatments (factors) as well as their mode, drives us to make a factorial experience plan (complete) with only two processes of washing (stone wash and mixed wash)[1] 4 £ 3 £ 2 £ 2 £ 2 £ 2 (Vigier, 1991), containing 192 lines or experiences. This plan is repeated three times, we obtain a factorial plan of 576 experiences.
Levels/ factors
Table III. Experience plan
Type of fabric
Special treatments
Washing types
Bleachtreatment
Permanganate- Cationic spray softening
Bleach (B) No bleach(NB)
Spray (S) No spray (NS)
1 2
T1 T2
Brushing (Br) Sanding (Sa)
Stone (S) Mixed (M)
3
T3
Resintreatment (Re)
4
T4
Enzyme (E) Rinse (R)
Soften (A) No soften (NA)
Treatments
Conditions
Sanding (Sa)
Nature: manual with gun Type of sand: contains at least 5% of SiO2 Pressure ¼ 5 bars Angle of attack ¼ 458 Number of passage ¼ 3 Nature: automatic (robot) Rotational speed: 120 tr/mn Linear speed of the brushes: 20 m/mn Nature of product: DMDHEU Concentration: 25% Pulverization: 5 ml of resin/1 kg of merchandise Nature of product: potassium permanganate Concentration: 50-65 ml for a surface of (0.2 m2) Distance of pulverization: 40-50 cm Pressure ¼ 2.5 bars Number of passage ¼ 3 Product: 6.5 ml/l of gavel water of (128 chlorinate) Report of the bath ¼ 1/5 Temperature ¼ 508C Time of washing ¼ 45 mn Stone: new stones and worn-out stones (80 kg for a load of 140 trousers) Report of the bath ¼ 1/5 Temperature ¼ 508C Time of washing ¼ 45 mn Enzyme: acidic enzyme (pH ¼ 5), 800 g of enzyme for a load of 80 kg of the merchandise Report of the bath ¼ 1/5 Temperature ¼ 50 8C Time of washing ¼ 45 mn Enzyme: acidic enzyme (pH ¼ 5), 800 g of enzyme for a load of 80 kg of the merchandise Stone: new stones and worn-out stones (20 kg for a load of 140 trousers)
Brushing (Br) Resin-treatment (Re) Permanganate-spray (S)
Bleach (B) Stone washing (S)a
Enzyme washing (E)a
Mixed washing (stone þ enzyme) (M)a
Note: aAll types of washing start with a preparation and end by a soaping, softening, wring and drying
Statistics generated by “MINITAB” were used to investigate the differences in K/S for the most important parameters of finishing garment washed denim. Results and discussion Physical survey Influence of types of laundering. In the first part of this study, it is appropriate to assume that when comparing different types of laundering, the different responses observed in the same sample that have the same finishing would be due to different types of laundering. Therefore, we could make comparisons of each laundering in this investigation.
Denim garment shade
37
Table IV. Conditions of finishing treatments
IJCST 23,1
100 L*
White Yellowness b* >0
38
Black
Greenness
Redness
a* <0
Figure 1. Rectangular axes of general opponent colour space (verbal axis labels) and CIELAB colour space (L * a * b *)
O = [000]
a* >0
b* <0 Blueness
When denim blue jeans garments are laundered, colour changes will be influenced by several parameters of types of laundering. Figures 2 and 3 show the effect of different launderings (stone wash (S), enzyme wash (E), mixed wash (M), rinse wash (R)) on the L *, a *, b * parameters and K/S values. In the case of rinse wash, when no enzyme or no stone were used, L *, b * decrease and a * remains constant. The shade of untreated sample is whiter than the treated one. The cloth shade of the untreated sample is influenced by the presence of glue on weft yarns. During a rinse wash a part of the glue becomes soluble in the bath and it facilitates the dye bleeding. After, there is a dye redeposition on the not dyed weft yarns. Then, the cloth shade became darker than the untreated sample. The washing rinse is the softest since the bath contains only an enzyme amylase and a surfactant that do not risk damaging the matter. However, the attenuation of cloth shade by stone washing is more important comparing to enzyme washing proving that stone abrasion is more aggressive than the enzyme one. In fact, when fabrics are laundered with stone or enzyme wash, the surface fibres are aggressively removed from the fabric surface by the stone or enzyme action thereby lower yarn surfaces can be worn away further. If the stones and enzyme are combined in the same laundering as in the mixed wash, the fibre’s degradation become
T3
T4 2
39 37 35 33 31 29 27 25 23 21 19 17 15
a* on the top and b* on the bottom
L*
Figure 2. Evolution of L * and (a *, b *) according to different types of laundering
T2
Wt R E S M Wt R E S M Wt R E S M Wt R E S M
Washing types T1
0 –2 –4 –6 –8 –10 –12 –14 –16 –18
Wt
R
E Washing types
S
M
T1
T2
T3
T4
Denim garment shade
25 T1
T2
T3
T4
20
15 K/S
39
10
5
Figure 3. Evolution of K/S according to different types of laundering
0 Wt
R
E
S
M
Washing types
more important causing an intensive aged look which explain the high increase of L * values as shown in Figure 2. Moreover, all types of fabrics show a similar shade evolution with different launderings. Only a little shade intensity variation is detected between them. Influence of special treatments. To investigate the effect of special treatments, current treatments frequently used in denim manufacturers (brushing (Br), sanding (Sa) and resin-treatment (Re)) are chosen. The application of these special treatments has been done on untreated garments before stone or mixed washing. The shade evolution after washing treatments is shown in Figures 4 and 5. These figures illustrate that, after different treatments, the measured shades of the different samples evolve with the same way for all cloths. Moreover, an increasing of L * values and a decreasing of K/S are observed when fabrics are treated with brushing or sanding before laundering. Moreover, the effect of these two special treatments on obtaining more whiteness and aged look was very important but, in this case, the effect of the sanding is more intense than the brushing due to the big pressure of the sand
T2
T3
Wt S Br+S Sa+S Re+S Wt S Br+S Sa+S Re+S Wt S Br+S Sa+S Re+S Wt S Br+S Sa+S Re+S
Special treatments T1
T4
45 a* on the top and b* on the bottom
40 35
L*
30 25 20 15 10 5 0 Wt
S
Br+S Special treatments
Sa+S
Re+S
2 0 –2 –4 –6 –8 –10 –12 –14 –16 –18 –20
T1
T2
T3
T4
Figure 4. Evolution of L * and (a *, b *) according to special treatments, before a stone washing (stone (S))
IJCST 23,1
15
15 T1
T2
T3
T1
T4
10
Figure 5. Evolution of K/S according to different special treatments before has washing
T3
T4
10 K/S
K/S
40
T2
5
5
0
0 wt
wt
S Re Br Sa Special treatments Note: Stone (S) on the left and mixed (M) on the right
M Re Br Special treatments
Sa
projection. Brushing effect will be more intensive by increasing the pressure and the number of passages or by choosing harder hair brushes. On the other hand, if the fabric is treated with resin before laundering, the colour fastness to washing and bleeding during stonewash and mixed wash treatments are slightly increased because of the formation of a slightly colour resist film on the surface of the garment. In our survey, we use a reticulating resin dimethylol dihydroxyethylene urea (DMDHEU) as a crosslinking agent for the cellulose chains that develop hydrophobic effect on the treated fabrics. This resin is often applied on cotton fabrics to fix a defined form (crimp adjustment or ironed aspect) either to avoid the attenuation of cloth shade in washing jean garments. Influence of the succession of special treatments. While choosing a line of succession of finishing treatments, we can notice from the two Figures 6 and 7 that, for the different types of fabrics, K/S decreases continuously up to ten times and L * increases about 100 percent after ending the finishing treatments. The decrease of K/S values is due to the high level of mechanical abrasion generated progressively on the fabrics by the succession of the washing (stone or mixed) and mechanical special treatments
T1
T2
T3
1=M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad 1=M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad 1=M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad 1=M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad
Special treatments T4
70 a* on the top and b* on the bottom
60 50 L*
40 30
Figure 6. Evolution of L * and (a *, b *) according to the succession of the treatments before a mixed washing (mixed (M))
20 10 0
0 –2 –4 –6 –8 –10 –12 –14 –16 –18
Wt
1 = M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad Special treatments
T1
T2
T3
T4
16 14
T1
T2
T3
T4
Denim garment shade
12 K/S
10 8
41
6 4 2 0 Wt
1=M
2 = Br+1
3 = 2+B
4 = 3+Sp
5 = 4+Ad
Figure 7. Evolution of K/S according to the succession of the treatments before a mixed washing (mixed (M))
Special treatments
(brushing or sanding) and the chemical action of the enzyme and chemical special treatments (bleach or spray). Moreover, except of the softening, b * values increases progressively after each treatment which means that the blueness intensity decreases. Compared to the other fabrics, the heaviest fabric T4 shows the most attenuation of K/S values after the mixed washing and finishes with a weak value of K/S after the succession of treatments as the middle weight fabrics T2 and T3. In fact, supposing that all things are equal otherwise, the dyed thickness of a thick yarn will be weaker than thinner yarn having a weaker diameter since the same quantity of dye will be distributed in the two yarns (Figure 8). Statistical study Statistics generated by “MINITAB” were used to investigate the effect of fabric types, washing types, special treatments, bleach, spray and softening on the cloth shade (K/S). The choice of these treatments (factors) as well as their mode, drives us to make a factorial experience plan (complete) (Table III) with only two processes of washing (stone wash and mixed wash)1 4 £ 3 £ 2 £ 2 £ 2 £ 2 (Vigier, 1991), containing 192 lines or experiences. Through repeating this plan three times, we obtain a factorial plan of 576 experiences. The main effect, the interaction plot and the analysis of variance (ANOVA) were used to determine the presence of significant differences of treatments. The statistical results showed. Justification of the model. By the test of the adjusted regression coefficient, the K/S model is justified because it presents a coefficient of 0.9537 that is very near to 1. Analysis of the main effects plots. The main effects plot represents the averages of the answers for every level of every parameter, with the tracing of a reference line the global average of the answer information. This diagram is essentially used to compare the importance of the main effects of the different parameters; it is a first classification
Thick yarn
Thin yarn
Figure 8. The distribution of a same quantity of dye in two different yarns diameters
IJCST 23,1
42
of the different treatments used in garment washing denim according to their respective main effects on the final garment shade. As first conclusion, we can say from Figure 9 that the effect of the softening treatment is negligible on the shade which is proven practically (K/S < constant). The special treatments, the bleach and the spray have a very important effect. However, the fabric and washing types have a fairly important effect. Analysis of the interaction plot. The interaction diagram is a representation of the answers information averages for every treatment level. The level of the second treatment remains constant. This diagram is useful to judge the presence of interaction. An interaction is present if the answer for a treatment level depends on/or the other treatment levels. In a diagram of the interaction, some parallel lines indicate the absence of interaction (Hicks, 1982). More the lines depart of the parallel; more the degree of interaction is raised. This diagram informs us on the type of model to consider in the ANOVA. As shown, in Figure 10 the detected interactions are: [T £ Ts], [T £ D], [Ts £ D], [Ts £ B], [Ts £ S] and [B £ S]. This result is going to help us in finding the considered model, so it is advisable to complete the study by the ANOVA. Analysis of the variance. The ANOVA is the most important test in this survey since it is going to permit us to judge if the effect treatments on the measured answer (K/S) are statistically significant (Miliken and Johnson, 1984; Nelson, 1983). This test consists to calculate a statistical F from the coefficients of the established model and then to compare it to statistical tables of snedecor law (Olshen, 1973), and from F we can calculate another p statistic (Table V): If p , 1 percent:
then we say that the difference is highly significant.
If 5 percent , p , 1 percent: then we say that the difference is significant. If p . 5 percent:
then we say that the difference is not significant.
ANOVA shows that the matter, launderings and special treatments have a significant effect (Table V) on cloth shade. We summarize the results of the statistical analysis in the established interrelationship equation between the different treatments and their interactions. This equation represents the effect statistically significant effect ( p , 5 percent). Main effects plot (data means) for K/S Fabric type
Special treatments
Washing type
7 6 5
Mean of K/S
4 3 1(T1)
2(T2)
3(T3)
4(T4)
1(Br)
Bleach
2(Sa)
3(Re)
1(S)
Spray
2(M) Softening
7 6 5
Figure 9. Graphic of principal effects for K/S
4 3 1(B)
2(NB)
1(S)
2(NS)
1(A)
2(NA)
Denim garment shade
Interaction plot (data means) for K/S 1
2
3
1
2
1
2
1
2
1
2 9 6
Fabric types
3 9
43
6
Special treatments
3 9 6
Washing types
3 9 6
Bleach
3 9 6
Spray
Figure 10. Graphic of interactions for K/S
3 Softening
Treatments T Ts D B S A T £ Ts T£D T£B T£S T£A Ts £ D Ts £ B Ts £ S Ts £ A D£B D£S D£A B£S B£A S£A
F
p
Conclusion
37.83 427.83 10.42 439.16 2,152.25 2.80 23.82 4.97 3.87 1.60 0.96 4.79 14.84 53.01 0.23 5.17 0.02 0.53 50.62 0.00 0.06
0.000 0.000 0.002 0.000 0.000 0.091 0.000 0.000 0.011 0.192 0.412 0.010 0.000 0.000 0.791 0.024 0.887 0.467 0.000 0.949 0.803
£££ £££ £££ £££ £££ – £££ £££ ££ – – £££ £££ £££ – £ – – £££ – –
Notes: – , absent or present interaction but negligible; £ , present interaction with the increasing importance according to the number of £
Table V. Results of ANOVA for K/S
IJCST 23,1
K=S ¼ ½T þ ½Ts þ ½D þ ½B þ ½S þ ½T £ Ts þ ½T £ D þ ½Ts £ D þ ½Ts £ B þ ½Ts £ S þ ½B £ S This model showed that the K/S variation is explained in a great part by the variation of the different treatments and their interactions kept in the model.
44
Confrontation of the statistical model and the physical survey The statistical study shows that the treatments achieved during garment washed denim have a highly significant effect on the cloth shade. Moreover, the presence and the importance of the interactions between the different treatments (washing type, special treatments, bleach, spray and softening) have a significant effect also. These statistical results are confirmed by the physical survey where we showed that the washing type (mixed or stone), the special treatments (brushing, sanding or resin-treatment), the bleach and the spray have an important effect on the cloth shade (decrease of K/S values). In the same way, we showed that the succession of the treatments decreases the shade, where we can arrive to get with distinctly lines of finish the same whiteness aspect. In conclusion, we can say that the statistical model is confirmed by the physical survey. Conclusion Garment washing is a technology incorporated by garment manufactures to be able to provide a product in response to consumer’s wants. This study of the effect of matter, washing type, special treatments (brushing, sanding or resin-treatment), and their succession on garment denim blue jeans shade provides garment manufactures with information about the methodical line of finishing to obtain the desired cloth shade. This study shows that the application of the resin-treatment before the laundering provokes the formation of a slightly colour resist stripe on the surface of garment and that the succession of finishing treatments (brushing, sanding, bleach, spray, etc.) is advisable to have an intense whiteness. Nevertheless, all these treatments causing a more worn appearance and aged look for the garment, thus, the mechanical properties are greatly reduced. For this reason, a second survey of the effect of these treatments on the mechanical properties has been achieved, to know up to what limit the fabric can support the succession of the treatments in order to choose the most suitable process to obtain the wanted cloth shade while avoiding at the same time the massive deterioration of matter. Note 1. The enzyme wash and the rinse wash not be used in the experience plan because industrially we cannot used all this these treatments with these two washing process. References Card, A., Moore, M.A. and Ankeny, M. (2006), “Garment washed jeans: impact of launderings on physical properties”, International Journal of Clothing Science & Technology, Vol. 18 No. 1, pp. 43-52. Derbyshire, A.N. and Marshall, W.J. (1980), “Value analysis of dyes a new method based on color measurement”, Journal Society of Dyers and Colorists, Vol. 96 No. 4, pp. 166-76.
Hargraves, R., Eissele, E. and Pisarczyk, K. (1991), “Innovation in pellet technology for garment dyeing”, American Dyestuff Reporter, Vol. 80 No. 5, p. 28, 30, 32. Hicks, C.R. (1982), Fundamental Concepts in the Design of Experiments, 3rd ed., CBC College, New York, NY. Higgins, L., Anand, D., Holmes, A., Hall, E. and Underly, K. (2003a), “Effect of various home laundering practices on the dimensional stability, wrinkling, and other properties of plain woven cotton fabrics. Part I: experimental overview, reproducibility of results, and effect of detergent”, Textile Res. J., Vol. 73 No. 4, pp. 357-66. Higgins, L., Anand, D., Holmes, A., Hall, E. and Underly, K. (2003b), “Effect of various home laundering practices on the dimensional stability, wrinkling, and other properties of plain woven cotton fabrics. Part II: effect of rinse cycle softener and drying method and of tumble sheet softener and tumble drying time”, Textile Res. J., Vol. 73 No. 5, pp. 407-20. Mclaren, K. and Rigg, B. (1976), “The SDC recommended colour-difference formula change to CIELAB”, Journal Society of Dyers and Colorists, Vol. 92, pp. 337-8. Miliken, G.A. and Johnson, D.E. (1984), “Analysis of messy data”, Designed Experiments, Vol. 1, Van Nostrand Reinhold, New York, NY, p. 189. Militky, J. and Bajzik, V. (1997), “Influence of washing/ironing cycles on selected properties of cotton type weaves”, International Journal of Clothing Science & Technology, Vol. 9 No. 3, pp. 193-9. Nelson, P.R. (1983), “A comparison of sample sizes for the analysis of means and analysis of variances”, Journal of Quality Technology, Vol. 15, pp. 33-9. Olshen, R.A. (1973), “The conditional level of the F-test”, Journal of the American Statistical Association, Vol. 68, pp. 692-8. Phan-Tan-Luu, R. (1993), Methodology of the Experimental Research, Edition Euskatel Estatistika, Derio, pp. 132-4. Roderick, M. (1997), Colour Physics for Industry, 2nd ed., Colorimetry and the CIE System, Woodhead, Cambridge, pp. 111-33. Shukla, S.R. and Dhuri, S.S. (1992), “A practical application of the Kubelka-Munk theory in polyester dyeing”, American-Dyestuff-Reporter, Vol. 81 No. 4, pp. 32-41. Spevack, R. (1997), “Jeans business needs to get more creative”, Daily News Record, Vol. 27 No. 128, October 24, p. 7. Vigier, M. (1991), “Pratique des plans d’expe´riences”, Taguchi et comple´ments, Les Editions d’Organisation, Paris. Corresponding author Faouzi Khedher can be contacted at:
[email protected]
To purchase reprints of this article please e-mail:
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Denim garment shade
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IJCST 23,1
Identification of female body shapes based on numerical evaluations
46 Received 10 February 2009 Revised 22 July 2010 Accepted 22 July 2010
Arzu Vuruskan Department of Fashion Design, Izmir University of Economics, Balcova, Turkey, and
Ender Bulgun Department of Textile Engineering, Dokuz Eylul University, Buca, Turkey Abstract Purpose – Identification of human body shapes has been a key issue to develop sizing standards for ready-to-wear and to develop made-to-measure applications. Current methods to identify the body shapes are mostly based on subjective/visual determination approaches. The purpose of this paper is to look for numerical evaluation parameters for an objective method in order to classify the body shapes and to build up an automated process link. Design/methodology/approach – Female subjects were chosen for the experimental design. 3D body scanning technology was integrated in the process for measurement taking and body silhouette detection of the sample group. Based on this sample data set, body shape identification was realized by referees as visual analyses, and additionally, an objective method was tried out by using body dimensions as numerical evaluation parameters. Obtained results with the sample group were inserted in a database and a body shape calculation tool was developed. Findings – Statistical analyses showed that there is mostly a good agreement between the pairs of the evaluations including the objective calculation methods and the subjective assessments of the referees. The calculation tool was designed as web-based software in order to integrate with further developments and automation purposes. Originality/value – A new automatic tool was developed to make the body shape classification objective and repeatable. By integrating this tool to the product development chain, a continuous process link can be provided for the companies through the way for better fitting clothing. Keywords Classification, Image scanners, Computer software, Garment industry Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 1, 2011 pp. 46-60 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111096732
Introduction Clothing fit has been regarded as the most important element to customers in clothing appearance (Fan et al., 2004). One of the main aspects of fit is related with the 3D body shape. Even if having the same body measurements, fitting results for different individuals can be different based on the specifications of body shapes. Thus, identification and classification of the figures for apparel has long been an important issue for researchers and the industrialists both for ready-to-wear and made-to-measure concepts. For ready-to-wear, defining the minimum number of classification groups with The authors would like to thank to Dipl.-Kff., Dipl.-Ing. Ute Detering-Koll, and Dipl.-Ing. Rudolf Haug from Niederrhein University of Applied Sciences for providing the opportunity to use the body scanner and for their valuable comments.
the most recognized shapes in the population would help for the better fitting of a greater number of consumers, whereas made-to-measure approach would need more detailed classification groups. Body shape studies are carried out in conjunction with the sizing issues, and attempts to develop sizing standards result with size surveys, formation of size groups, and body shape classifications. National and international size surveys are aiming to collect anthropometric data with the current measurements on the sizes as well as the body shapes of today’s consumers. Size USA (2003), Size UK (2003), Size Germany (2009), and French National Sizing Campaign (2006) are some latest examples. Current female body shape classifications are considered in various categories in pattern making and sizing terminologies. Geometrical figures such as triangle, inverted triangle, rectangle, oval, circle shapes are some examples as well as the letter figures as A, V, H, O, X or fruits/vegetables as pear or apple. They refer to more or less the same figures with different codes of identification and are based on the proportions of the body silhouette mostly from the front view. General looks as “young junior/teen, junior petite, junior, miss petite, miss, half-size, and woman” are also considered for current sizing development. Differentiating the size chart categories with height (medium, short, tall) or hip (average, slim, full hip) based groupings is another system for body shape classification through the aim of better fitting (Armstong, 2000; MacIntyre, 1998; DOB-Verband, 1983; Aldrich, 2004). 3D body scanning 3D body scanning is a new technology since the late twentieth century with applications in the apparel industry, human systems engineering, medical field, and the entertainment industry. 3D body scanner is an optical 3D measuring system to produce a digital copy of the surface geometry of human body by generating a very dense cloud of points. There are a variety of scanner types; however, the processes are similar to each other. Body scanning systems consist of one or more light sources, cameras or capturing devices, software, a computer system, and a monitor screen in order to visualize the data capture process. The primary types of body scanning systems are laser and light projection. For both of the systems, the light is projected onto the scanned object and the cameras detect the reflected light deformed by the objects shape. Displacement of the light is used to calculate the coordinates of 3D points on the object (Daanen and Water, 1998; Fan et al., 2004). Some recent studies regarding the body scanning and body shape issues are observed to be related with the further integration areas of body scanning into various stages of process chains mostly with the aim of automation or customization. Lu and Wang (2008) looked for an automated anthropometric data collection system by using 3D body scanner and tried to eliminate manual intervention. With the aim of customization, Daanen and Hong (2008) developed m-t-m patterns based on 3D whole body scans. Chen (2007) evaluated the fit of basic garments within the m-t-m process for various figure characteristics. Loker et al. (2005) tried to describe how size-specific analyses of body scan data can provide information that can be used to adjust ready-to-wear sizing to improve apparel fit. The study from Shin and Istook (2006) was related with pattern data format standardization between apparel computer-aided design (CAD) and 3D body scan with Extensible Markup Language. Griffey and Ashdown (2006) developed an automated process for the creation of basic skirt block pattern from
Female body shapes
47
IJCST 23,1
48
3D body scan data. Ashdown et al. (2008) worked on a method of automatically locating the side seam for torso fitting garments from 3D body scans for a variety of body types was developed and tested. Istook (2002) tried to outline the activities involved in setting up CAD systems to automatically customize garments for fit. Simmons et al. (2004) worked on a female shape sorting system programmed in Visual Basic. The process involved using the 3D body scan data for the customization procedure to ensure satisfactory fit. Connell et al. (2006) worked on a similar study by developing body shape assessment scales using experts’ knowledge. Apart from the apparel- and fitting-related studies, body shape classification is also important for various research fields such as medicine, biology, anthropometry, and ergonomics. Further research directions regarding body shape analysis and the 3D body scanner can be diversified with such various disciplines. However, limited amount of research has been noticed regarding the integration of body scanning for the use of body shape identification. Objectives and methodology Even if having the same bust, waist, and hip circumferences, it is possible to have quite different body shapes for different individuals. It is clear that these circumference measurements are not the indicators of the body shape, but the ratios and relations between these values can give clues for the identification of the shape. Current body shape identification methods are mostly based on subjective analysis. Although a quantitative method is more desirable, it is difficult to realize and does not have widespread application areas in the industry. The framework of this research was defined to explore female body shape classification groups and to look for an objective method to classify the body shapes based on body dimensions. Some body dimensions for garment construction and anthropometric surveys were chosen as the numerical evaluation parameters. Correlations between these values and the figure types were investigated. Body shape classification groups may be different for various applications and purposes. However, by choosing an arbitrary classification system, the purpose in this study was to develop an automated female body shape sorting system and to evaluate the usability of scan data for the integration of this process. Through this main objective, following research questions were set to define the objectives and the following progress steps: RQ1. How would a female body shape classification system look like, for the use of ready-to-wear and made-to-measure? What can be the assessment parameters for shape identification? RQ2. Would it be possible to find out some numerical correlation parameters in order to identify the female shapes by using a few body dimensions? RQ3. What would be the benefit to use 3D body scanner for the body shape classification process? RQ4. What are the results of visual and automatic shape identification? RQ5. How can an automated process link be realized by developing web-based software for the identification of body shapes?
Within the direction of these research questions, the methodology entailed a four-phase-progress, where both of qualitative and quantitative approaches were considered: (1) During the first phase of the research, a classification of geometrical shapes was taken into consideration for the body shape identification tool. Body dimensions were investigated for searching correlation parameters to use for classification. This introduction phase was related with the RQ1 and RQ2. (2) Second phase included the 3D body scanning process with Human Solutions Vitus Smart XXL Body Scanner. Virtual images and the necessary body dimensions were obtained from the sample set group by using the body scanner. The collected data were used for the quantitative research practices. This phase tried to look for solutions for the RQ3 by integrating the scanner for the body shape analysis process. (3) Third phase was the classification of the sample set according to the earlier defined groups and parameters in Phase 1. By visual analysis of four referees subjective assessment was realized. Subsequently, earlier defined parameters were used for automatic calculation. Two different methods were followed for the automatic calculation: first, the body shape was identified based on the correlation parameters of circumference measurements, second width-based measurements were used for evaluation. The results were compared statistically for the usability of automatic calculation methods and the visual subjective evaluations. This evaluation tried to find answers to RQ4. (4) For the final objective of this research work, the results were transformed in a database and a web-based tool was developed. The code was generated by using the body dimension parameters and a simple interface was chosen for the beginning phase. In the second part of this study, this tool will be developed for further purposes. The web-based approach aimed to integrate the shape sorting system with further automation developments. The translation of calculation steps into a software tool was done by using PHP technology and using MySQL as database. The database was used to store the data of the scanned samples and to compare the results of visual analyses. Procedures and results As defined in the methodology, the procedures in this work consisted of four phases which will be explained with the detailed procedures and related results consequently. Phase 1. Defining the body shape groups and identifying the evaluation parameters Currently there exist numerous body shape classifications. Among these alternatives, a mixed terminology with the geometrical figures and the letters as symbols was chosen to reflect the silhouette of the body shape, mainly from the front view. The body shape classification tree in this work is shown in Figure 1 and the key features of the groups were defined as given below. The important point for the general hourglass category is to have a significant waist shape. Spoon shape is a subgroup of bottom hourglass shape with a more rounded hip form. Similar to a rectangle or similar to the look of the letter H, the body shape looks
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Femal body shape classification
Rectangle - H
Hourglass
Oval - O
Triangle - A
Inverted triangle - V
50 Bottom hourglass bottom X
Top hourglass - top X
Hourglass - X
Spoon
Figure 1. Female body shape classification
straight from bust to hip for the rectangular figures. Oval shape is mostly observed with the overweight figures as a result of the allocation of fat in the body. Triangle and inverted triangle shapes show a continual increase/decrease from the bust to the hip level. Before searching for numerical parameters, these shapes were divided into groups according to the silhouette similarities as: . oval (O) shape; . triangle (A)-bottom X-spoon shapes; . rectangle (H)-hourglass (X) shapes; and . inverted rectangle (V)-top X shapes. After choosing these categories for the classification, numerical evaluation parameters were searched. The aim was to choose minimum number of body dimensions for differentiation of figures in order to make the process as simple and as quick as possible. Two different calculation methods were proposed. For the first method, circumference measurements were proposed as reference parameters, which are easier to obtain from the body. The second method included the width-based measurements. A flow chart was prepared for both of the methods. For both of the methods, below given process flows and the procedures were followed: (1) Identifying the oval body shape was the first evaluation criterion by calculating the depth of the body. (2) If the measurements of a subject did not fall into this category, then the second evaluation criteria were searched, which was looking for the differences of bust and hip measurements. Consequently, based on these comparisons with the second evaluation criteria, three different classes were built up as: . triangle (A)-bottom X-spoon shapes; . rectangle (H)-hourglass (X) shapes; and . inverted rectangle (V)-top X shapes.
(3) The third evaluation criteria were different for each of these subgroups according to the necessities. Among these groups below additional parameters were used to identify each specific body figure: . The ratio of bust to waist distinguished the triangle (A) figure from the bottom X and spoon shapes. An extra body dimension “high hip circumference/width” was used for the differentiation of spoon shape from the bottom X figure. The ratio of high hip to waist gave a clue for spoon shapes, because these figures showed a sudden increase from waist to high hip with the rounded forms. . Distinguishing the rectangle (H) shape from the hourglass (H) shapes needed extra measurements as “torso width at waist” and “width armpits”. For the rectangular shapes the difference of these dimensions were observed to be under a specific value. . The ratio of waist to hip distinguished the inverted triangle (V) figure from the top X shape, where this value was observed to be higher for inverted triangle (V) figures. Phase 2. Choosing the sample set and 3D body scanning For the body measurement taking process an experiment was designed by choosing a sample group of female students in a university by announcements, posters, and social networks. For this experiment, participants were required to be between the ages of 20-35 and were measured in their underwear, without shoes, glasses, or jewellery. Participants were informed about the procedures and signed a protocol to appraise their own rights for the confidentiality. With these procedures, 83 scans were collected by using Human Solutions Vitus Smart XXL 3D Body scanner. The time for this application for each sample was planned to be around 45 minutes. The subjects were scanned in two different postures as standard posture and the relaxed posture (Figure 2). For the measurement extraction of the scanner software ScanWorX, the standard posture was a necessity to obtain clothing relevant measurement, with feet apart and arms held at the sides but away from the body (Human Solutions GmbH, 2005). The other posture was the relaxed posture with the arms hanging at the sides of the body and the legs standing together. This posture was important to identify the body shape by visual evaluation. The ScanWorX software can acquire approximately 140 licensed body measurements that are automatically captured. Additionally, the interactive tools help to gather extra measurements depending upon the necessities for made-to-measure applications. Necessary body dimensions from the sample data set were obtained as a list in MS Office Excel sheet for the automatic shape sorting system development. These values were used to structure the numerical evaluation flow. Phase 3. Classifying the samples based on visual analysis and mathematical calculation methods Proposed evaluation parameters were tried with the sample data set and results were compared with the subjective evaluations. None of the samples fell into the triangle, inverted triangle and top hourglass body shapes. The evaluation parameters were re-checked, but with the aim of keeping the classification groups as simple as
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Figure 2. Standard posture and the relaxed posture for 3D body scanning process
possible, these categories were neglected. Triangle and inverted triangle shapes were eliminated because all the possible samples for this group had a waist shape since this was an expected specification with a sample group of young females. Consequently, the main five groups were defined as the hourglass, bottom hourglass, spoon, rectangular, and oval shapes. According to the defined key features in Phase 1, typical samples were chosen from the sample set. These typical figures were considered as the reference figures for the following visual evaluations by the referees as shown in Figure 3.
Figure 3. Typical five body shapes from the scanned samples
Note: In order: hourglass, bottom hourglass, spoon, rectangle, oval
To classify the body shapes, four referees were chosen for subjective/visual analysis. The referees were asked to classify the scanned images into five categories by taking the typical samples in Figure 3 as reference. For the 69 percent of subjects, all four referees agreed with the same body shape. For 18 percent of the subjects, one referee suggested another shape, but the other three agreed with the same shape. For the rest 13 percent of the subjects, at least two of the four referees claimed different ideas for the body shapes (Figure 4). For the objective calculation, circumference- and width-based calculation methods were followed. Width measurements were taken separately from the interactive measurement taking tools from the scanner software through the levels as shown in Figure 5. To compare the results of the width- and circumference-based calculations, 86 percent (64 þ 22 percent) of the results were matching with each other and were the same both for the width and circumference calculation methods. For 9 percent
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Subjective analysis 13% 18%
All comments are the same 69%
Only one referee claimed another figure type More than one figure type claim from the referees
Figure 4. Results of the subjective analysis of refeeres
Figure 5. Taking the width measurements from the digitized body form
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of the subjects, results of the width- and circumference-based calculations showed difference, however, subjective evaluations from the referees were also different. This was only for the subjects whose shapes are mostly at the borders between two categories. For the 5 percent of the samples the results with the calculations were different, but what the referees suggested was matching with the width-based calculations (Figure 6). The subjective and objective results were statistically evaluated by using the software SPSS 17.0 for Windows. According to the Kappa analysis technique, values of agreement were produced between the two pairs of assessments (Table I). The guidelines to evaluate the agreement levels were added accordingly (Dawson and Trapp, 2004). Since there is no sampling distribution for Kappa statistics, it was not possible to determine the exact number of the sample size to make a conclusion. Therefore, all usable sample measurements during the measurement taking process were included for evaluation. With the obtained sample size, this statistical analysis showed that there is mostly a good agreement between the pairs of the evaluations including the objective calculation methods and the subjective assessments of the referees. There are not district borders between the defined body shapes, therefore such an agreement level was a good outcome of this evaluation and it is claimed that the flow of numerical evaluation steps can be accepted as an objective method for body shape assessment. To find out the total agreement value, results of the two objective calculation methods and the four referee assessments were also evaluated for the measurement of interrater agreement by the method of multiple ratings per subject and by using an online kappa calculator. Percentage value of the overall agreement of these six values was 81,81% and the free-marginal kappa was calculated as 0.773, which was at the good agreement level (Randolph, 2008; Fleiss, 1981). Comparison with automatic calculation 9%
5%
22% 64%
All results are the same (both of the calculations and the referee comments)
Figure 6. Agreement of the referee decisions with the automatic calculation results
The results from the calculations are the same, but not all the referees claimed the same figure type The results from the calculations are different, there are also differences betweeen the referee comments The results from the calculations are different, comments of the referees are matching with the width- based calculations
0.892 0.782 0.608 0.765 Objective calculation method – width based
0.816 0.701 0.526 0.759 Objective calculation method – circumference based
0.798
0.737 Subjective evaluation – Referee 1
0.636
0.788
0.769 Subjective evaluation – Referee 2
0.702 0.702 Subjective evaluation – Referee 3
Notes: 0.93-1.00, excellent agreement; 0.81-0.92, very good agreement; 0.61-0.80, good agreement; 0.41-0.60, fair agreement; 0.21-0.40, slight agreement; 0.01-0.20, poor agreement; #0.00, no agreement
Objective calculation method – width based Subjective evaluation – Referee 1 Subjective evaluation – Referee 2 Subjective evaluation – Referee 3 Subjective evaluation – Referee 4
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Table I. Values of agreement between the pairs of evaluations
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Body shape allocation of the sample data set Considering the width-based calculation method, the results of body shape evaluations from the sample data set were analyzed. About 42 percent of the samples were belonging to the bottom hourglass category, 23 percent were in the spoon category, whereas 26 percent of the samples were calculated to be within the hourglass category. Only 5 percent of the samples fell into the oval category and 4 percent of the samples were in the rectangle category. Bust, hip, and waist measurements are the main measurements for the evaluation parameters. The ratios of these measurements show the coherency of body types. According to the sample body set, the ratios of “hip to waist” and “bust to waist” were defined. These two ratios were shown in a scatter diagram to reflect the tendency of human body proportions (Figure 7). Since the sample data set in this study includes more bottom hourglass or spoon body shapes, the points in the diagram tend to be close to the x-axis. The relationship between the bust circumference and hip circumference is shown in Figure 8 differentiated with the various body shapes. The tendency of the data points is visible in the diagram. These analyses were the re-check of the body shape sorting methods showing the coherency between the income data of the calculation tool. This kind of tendencies proved that it would be possible to find out an objective calculation method based on numerical parameters, because the body dimensions are proportional to each other and tend to show similar changes for similar body shapes and silhouettes. Phase 4. Development of the database and a web-based tool After collecting the data, the results were inserted in a database. A web-based tool was designed for the further development opportunities. This tool can be used to store the data for customer-specific orders or customer figure type classification. Since this tool was designed as a web-based instrument, this would help to integrate within the further product lifecycle units. If desired, this web-based tool can also be used to serve for individual customers as an interactive web site which provides an interface to
1.60
Bust to waist ratio
1.50
Figure 7. Body shape classification of the sample data set based on bust towaist and hip to waist ratios
1.40 1.30 1.20 1.10 1.00 1.00
1.10
1.20
1.30 Hip to waist ratio
1.40
1.50
1.60
Female body shapes
130
Bust circumference
120
110
57 Hourglass Spoon
100
Bottom hourglass Oval Rectangle
90
80
70 80
90
100
110
120
130
Figure 8. Variation of hip and bust circumferences in relation with the body shapes
Hip circumference
identify the female body shapes according to given parameters. The process of how to take the body measurements is explained by written and visual expressions. Web site is based on PHP technology and uses MySQL as database. This tool will be developed for further usage in the second part of this study. A sample interface is shown in Figure 9.
Figure 9. Screen view from the web-based tool
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Discussion and future work Body shape identification has been a key issue to develop sizing standards for ready-to-wear and the development of made-to-measure concepts. The current shape identification methods are based on subjective/visual analyses. A new calculation method was developed and tried in this work with the integration of 3D scanning. The method of objective calculations were tried with the sample data set and good levels of agreement were found in comparison with the subjective assessments. Because of the proportions in the body, correlations among the body dimensions would help to find out objective calculation parameters. Consequently, the objective evaluation method was considered to be a useful tool to achieve the research objectives: . Objective evaluation method included two different flows for calculation; either using the width based parameters or using the circumference based parameters. Among these two, width based measurements gave a better result showing better levels of agreement with the referees’ suggestions. Since the body is 3D, the circumference measurements would falsify the results passing through the contours and wrapping the depth of the body. Therefore, it was an expected outcome to have more realistic results with the width based measurements. However, the disadvantage of this method is the difficulty in measurement taking process. . To have more accuracy with the width based measurements, it might be necessary to find out landmarks on the body. By this way, measurement taking would be more standardized. . The objective evaluation parameters were tested with the sample data set in this study. It should definitely be considered that this flow of mathematical calculations may need to be adopted for various target groups. . 3D body scanning technology is a quite new technology and lots more new usage areas are yet to be discovered. With this study, it has been concluded that there is a possibility to find out objective measures of body shapes derived from the body scanning software. Current technologies and trends in the apparel business are looking for automated product lifecycle and data management systems. With a similar tool such as the proposed web-based instrument in this study, body shapes can be objectively identified for the integration of other product phases. Integrating the 3D body scanner helps for a more accurate, fast and standardized process within the process chain. A link between the 3D body scanner to upload the images and the calculation tool can help for automation. . Classifying the body shapes is a necessity both for ready-to-wear and made-to-measure approaches. The classification groups in this study were mostly based on front views of the subjects. Apart from this classification, an alternative classification system can be suggested for the further development of objective shape sorting system. A new silhouette definition for 3D body can be a step to a new classification system. It is possible to look for various classification categories according to the necessities. . Further analysis is required with the increased set of numbers. The results can be compared with the national size surveys or the research can be done with a more localized sample data set. Sorting the groups according to the age,
.
nationality, or regional differences may help to get more accurate classification parameters or more definite borders for each classification unit. The final web-based tool to assess the body shape was given as a starting concept in this part of the study. However, the method has been a base to classify the body types for further development by using a few body measurements parameters. Such software can be integrated into to the web sites of other disciplines, as medicine, biomechanics or sports so that the users/customers can get informed regarding the individual body shapes.
References Aldrich, W. (2004), Metric Pattern Cutting, 4th ed., Blackwell, Oxford. Armstong, H. (2000), Pattern Making for Fashion Design, 3rd ed., Prentice-Hall, Upper Saddle River, NJ. Ashdown, S., Choi, M.S. and Milke, E. (2008), “Automated side-seam placement from 3D body scan data”, International Journal of Clothing Science & Technology, Vol. 20 No. 4, pp. 199-213. Chen, C. (2007), “Fit evaluation within the made-to-measure process”, International Journal of Clothing Science & Technology, Vol. 19 No. 2, pp. 131-44. Connell, L.J., Ulrich, P.V., Brannon, E.L., Alexander, M. and Presley, A.B. (2006), “Body shape assessment scale: instrument development for analyzing female figures”, Clothing and Textiles Research Journal, Vol. 24 No. 2, pp. 80-95. Daanen, H. and Hong, S. (2008), “Made-to-measure pattern development based on 3D whole body scans”, International Journal of Clothing Science & Technology, Vol. 20 No. 1, pp. 15-25. Daanen, H. and Water, G.J. (1998), “Whole body scanners”, Displays, Elsevier Science, Vol. 19 No. 3, pp. 111-20. Dawson, B. and Trapp, R. (2004), Basic & Clinical Biostatistics, 4th ed., Lange Medical Books, New York, NY. DOB-Verband (1983), DOB-Gro¨ßentabelle, DOB-Verband, Cologne. Fan, J., Yu, W. and Hunter, L. (2004), Clothing Appearance and Fit: Science and Technology, Woodhead, Cambridge. Fleiss, J. (1981), Statistical Methods for Rates and Proportions, 2nd ed., Wiley, New York, NY. Griffey, J. and Ashdown, S. (2006), “Development of an automated process for the creation of a basic skirt block pattern from 3D body scan data”, Clothing and Textile Research Journal, Vol. 24 No. 2, pp. 112-20. Human Solutions GmbH (2005), Scanwizard Directions and ScanWorX User Guide, Version 2.9, Human Solutions GmbH, Kaiserslautern. Istook, C. (2002), “Enabling mass customization: computer-driven alteration methods”, International Journal of Clothing Science & Technology, Vol. 14 No. 1, pp. 61-76. Loker, S., Ashdown, S. and Schoenfelder, K. (2005), “Size-specific analysis of body scan data to improve apparel fit”, Journal of Textile and Apparel Technology and Management, Vol. 4 No. 3, pp. 1-15. Lu, J.M. and Wang, M. (2008), “Automated anthropometric data collection using 3D whole body scanners”, International Journal: Expert Systems with Applications, Vol. 35 Nos 1-2, pp. 407-14. MacIntyre, L. (1998), Easy Guide to Sewing Pants, Taunton Press, Newtown, CT.
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Randolph, J.J. (2008), Kappa calculator, available at: http://justus.randolph.name/kappa (accessed July, 2009). Schneider, B. (2006), French National Sizing Campaign, paper presented at IMB Fair, May 12, Cologne, Germany. Shin, S.H. and Istook, C. (2006), “Pattern data format standardization between apparel CAD and 3D body scan with Extensible Markup Language”, Journal of Textile and Apparel, Technology and Management, Vol. 5 No. 1, pp. 1-15. Simmons, K., Istook, C. and Devarajan, P. (2004), “Female figure identification technique (FFIT) for apparel. Part II: development of shape sorting software”, Journal of Textile and Apparel, Technology and Management, Vol. 4 No. 1, pp. 1-15. Size Germany (2009), available at: www.sizegermany.de (accessed July, 2009). Size UK (2003), available at: www.size.org (accessed July, 2009). Size USA (2003), available at: www.sizeusa.com (accessed July, 2009). Corresponding author Arzu Vuruskan can be contacted at:
[email protected]
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Effect of enzyme treatments on interlock knitted fabric
Enzyme treatments
Simona Jevsˇnik Academy of Design, Ljubljana, Slovenia
61
Zoran Stjepanovicˇ Faculty of Mechanical Engineering, University of Maribor, Maribor, Slovenia
Lea Heikinheimo
Received 27 January 2010 Revised 3 June 2010 Accepted 3 June 2010
Faculty of Technology, Lahti University of Applied Sciences, Lahti, Finland, and
Karl Gotlih Faculty of Mechanical Engineering, University of Maribor, Maribor, Slovenia Abstract Purpose – Enzyme treatment technologies are frequently applied in textile processing for the modification of fabric handle appearance and other surface characteristics in regard to cotton and cotton blended fabrics. The purpose of this paper is to understand the impact of enzyme treatments on fabric preparation, dyeing, and finishing processes of woven fabrics. In particular, certain mechanical and surface properties of 100 percent cotton interlock knitted fabrics after treatment with a cellulase enzyme. Design/methodology/approach – Interlock knitted fabrics were used for this research. These cotton fabrics were treated with experimental Trichoderma reesei cellulases containing different cellulase profiles and treatment was carried out under laboratory conditions. The effects of cellulase treatment on weft knitted fabric regarding mechanical and surface properties were evaluated using the KES-FB Kawabata evaluation system. The influence of enzyme treatments, friction, and geometrical roughness on the face and reverse side of interlock knitted fabrics were discussed in comparison with untreated interlock knitted fabric. Findings – After each of the enzyme treatments, the interlock knitted fabrics lost part of their weight and, therefore, they became thinner. Furthermore, the extension properties become higher in both directions with regard to the untreated knitted fabric for all used enzymes and carried out treatments. Originality/value – The paper usefully analyzes changes in the extension and surface properties of enzyme-treated interlock knitted fabrics by investigating the influence of whole or enriched endoglucanases celullases of Trihoderma reesei under different treatment conditions. Keywords Cotton, Textile technology, Fabric production processes, Proteins Paper type Research paper
1. Introduction Knitted fabrics have a certain speciality when compared to woven fabrics, particularly in their complicated yarn structures and bent stitches. They are more flexible, with a much wider usable deformation range than other textile materials and, in general, recover more easily from wrinkling than woven fabrics, easily mould and fit to body shapes, and move easily during body movements (Xiaoping and Chou, 1996). Furthermore, they are elastic, porous, yet light and warm, can be bulky but light, and may possess good draping qualities. Numerous investigations into the mechanical properties and hand evaluation of woven fabric have been performed, while only limited research has been reported on knitted fabric. The quality of produced knitted fabric depends on the technological knitting process and the kinds of chosen knitting yarn, as
International Journal of Clothing Science and Technology Vol. 23 No. 1, 2011 pp. 61-73 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111096741
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well as the finishing treatments. Finishing treatments usually change the mechanical properties of a knitted fabric, which are important during the production process, and these surface properties are significant for the hand of a knitted fabric. In comparison to woven fabric, the behaviour of knitted fabrics is very specific (high extensibility in both course and wales directions) due to their complex geometrical yarn structure when subjected to low deformation (Xiaoping and Chou, 1996; Bishop, 1996). Recently, enzymes are widely used in the textile industry for improving the quality and functionality of fabrics or to achieve a desired finishing effect with low environmental impact. Currently, the most commanding industrial enzyme applications are detergents with a $500 million market share. The textile field rates second with its $150 million market share (Cavaco and Gu¨bitz, 2003). Enzymes are proteins with specific catalytical (biological) reactions. They are principally classified and named according to the chemical reactions they catalyse, as this is the specific property that distinguishes one enzyme from another. Enzyme treatments can be included during various wet processes using existing equipment (Verstraete, 1994) and carried out under mild conditions such as ambient pressures, mild temperatures, and often at neutral pH. The most commonly used enzyme applications in the textile area are desizing, denim finishing, bio-finishing/bio-polishing with cellulases, removal of residual peroxide with catalases, and bioscouring (Heikinheimo, 2002). Currently, approximately 26 percent of all textile enzymes are used during bio-finishing processes (Ojapalo, 2002). Enzymatic process applications have increased substantially due to developments in genetic engineering, as specific enzymes can be efficiently modified for targeted applications. Cellulase enzymes are usually applied as multi-component enzyme systems and most commercial cellulases contain a variety of different activities, often causing unacceptable losses in fabrics’ strengths and weights (Verstraete, 1994). Trichoderma reesei is the most commonly used fungus for cellulase production in the textile industry. The cellulolytic system of T. reesei is composed of two cellobiohydrolases (CBH I, CBH II), at least six endoglucanases (EGs) and two b-glucosidases (Verstraete, 1994). Cellulase enzymes are mainly applied as a cellulase mixture for economic reasons, although a monocomponent product has proved to be successful in many applications. Most of the commercial cellulases contain a variety of different activities and may cause unacceptable losses in fabric strength and weight (Cavaco and Gu¨bitz, 2003; Verstraete, 1994). The effectiveness of different enzymatic treatments for determining the following mechanical and surface properties: extension, thickness, weight, friction, and geometrical roughness of the interlock knitted cotton fabric was evaluated during this research. 2. Experimental work The aim of this research was to analyze changes in the extension and surface properties of enzyme-treated interlock knitted fabrics by investigating the influence of whole or enriched EGs celullases of T. reesei under different treatment conditions. The experimental stages of this work are shown in Figure 1. 2.1 Materials The material used for the measurements was a 100 percent cotton brushed interlock knitted fabric, having a weight of 258.5 g/m2, and suitable for upper garments such as T-shirts and similar clothing products. The horizontal density (Dh) of the investigated sample was 15.6 stitches/cm and the vertical density (Dv) of the investigated sample’s
Measuring properties
Enzyme treatments Interlock knitted cotton fabric
Four different cellulases Different treatment condition
Tensile properties EMT – Tensile strain/% WT – Tensile energy/Nm/m RT – Resilience/% Compression properties T – Thickness of fabric/mm WC – Compression work/Nm/m2 RC – Resilience/%
Surface properties MIU – Coefficient of friction/– SMD – Geometrical roughness/µm
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Figure 1. Plan of experimental work
fabric was 13.2 stitches/cm. The structural parameters were determined according to standard DIN 53884 (1976) and DIN 53883 (1983). The reverse side of the fabric was brushed so that the effects of the enzymes were better seen on the surface of the fabric. Interlock is one of the four primary structures from which all weft knitted fabrics and garments are derived. Interlock was originally derived from the rib structure but requires a special arrangement of needles knitting back-to-back in an alternate sequence of two sets, so that the two courses of loops show wales of face loops on each side of the fabric, exactly in line with each other, thus hiding the appearance of reverse loops. Interlock relaxes by about 30-40 percent or even more, compared with its knitted width. It is a balanced, smooth, stable structure that lies flat without curling. Like 1 £ 1 rib, it will not unravel from the first end knitted, but it is thicker, heavier and narrower than the rib of an equivalent gauge, and requires a finer, better yarn. Two methods of presenting the structure of interlock knitted fabric, are shown in Figure 2. The structural parameters of interlock knitted fabrics have an important influence on extension properties because of their simple loop structure regarding course and wales directions (Spencer, 2001; Stjepanovicˇ and Karba, 2005).
Dial loops
1. 2. Course
Figure 2. Two presentations of interlock knitted fabric structures Cylinder loops
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2.2 Enzyme treatments The interlock knitted fabric was treated with four different enzymes at different concentrations. Enzymes A and D are T. reesei whole cellulase with varied side activities. Enzymes B1 and B2 are (engineered) enriched EGI II and C enriched EGI I. Exo-activities (both CBH I and CBH II) were removed for B1, B2, and C enzymes. The dosages of treatments varied from 0.1 to 5.0 g/l. The reference sample was treated with a silicone softener without enzyme addition. Treatments were carried out in a pilot scale jet machine. The treated interlock knitted samples were kindly provided by Genencor International (2004). The way samples were coded, the different concentrations, and other treatment conditions are presented in Table I. 2.3 Measuring procedure Changes in the extension and surface properties of the enzyme-treated interlock knitted fabrics were evaluated using the Kawabata evaluation system (KES)-FB measuring system from Kato Tech Co. Ltd, which consists of four different instruments (Kawabata, 1980). In our investigation tensile, compression, and surface testers were used, Figure 3. Samples having the size of 20 cm in course, and 20 cm in wales directions were used for all measurements. The measurements were performed in both course and wales directions except diagonally measured compression measurements. Surface friction and geometrical roughness measurements were carried out on the fabric’s face and reverse-side due to variations in the surface appearance of the fabric’s reverse side after enzyme treatments. The sample’s weight was determined as the differences in weight between the referenced samples and the treated sample (DIN 53854). The measurements were carried out under standard laboratory climatic conditions at 20 ^ 28C and 65 ^ 2 percent relative humidity.
Sample code Reference
Table I. Application conditions of enzymatic treatments
KF-A-1 KF-A-2 KF-A-3 KF-A-4 KF-B1-1 KF-B1-2 KF-B1-3 KF-B1-4 KF-B2-5 KF-B2-6 KF-B2-7 KF-C-1 KF-C-2 KF-C-3 KF-C-4 KF-D-1 KF-D-2 KF-D-3 KF-D-4 KF-D-5
Untreated Temperature (8C)
Enzyme
Dosage (g/l)
pH
A
1.0 2.0 3.0 5.0 1.0 2.0 3.0 5.0 1.0 3.0 5.0 0.4 0.7 1.1 1.8 0.7 1.4 2.1 3.6 5.0
4.8
55
5.5
45
5.5
30
4.8
60
4.8
55
B1
B2 C
D
Treatment time (min) 30
KES-FB 1 Tensile tester
KES-FB 3 Compression tester
KES-FB 4 Surface friction and geometrical roughness tester
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65
Figure 3. Used KES-FB measuring testers
3. Results and discussion Interlock knitted fabric was treated under different conditions with whole and enriched EGs (engineered) cellulases from T. reesei (Table I). In order to evaluate the effects of different enzymatic treatment conditions on 100 percent cotton brushed interlock knitted fabrics, they were measured according to tensile strain, weight loss, thickness loss, as well as surface properties concerning compressional properties, friction, and geometrical roughnesses on the faces and reverse sides. The analyzed properties of treated interlock knitted fabrics were compared with untreated. The dosages for the treatments of all chosen enzymes were 0.1-5.0 g/l, and the treatment time was 30 minutes. 3.1 Effect of enzymatic treatments on weight and thickness of interlock knitted fabric The effects of different enzymes, enzyme concentrations, and treatment conditions on the weight of the knitted interlock, are shown in Figure 3. Enzymes A and D T. reesei whole cellulase with varied side activities had the greatest effect on weight loss regarding the interlock knitted fabrics. The highest weight loss of 5.1 percent was measured for sample KF-D-4 treated with enzyme dosage of 3.6 g/l whole cellulase D. A very similar result for weight loss of 4.97 percent was measured for KF-A-4, treated with dosage 5.0 g/l whole cellulase A. The remaining enzymes’ treatments with enriched EGs (engineered) cellulases from T. reesei EGI II and EGI I had lower impact on weight reduction. The smallest change of weight loss was determined for sample KF-B2-6, where we used enzyme B2. Furthermore, the amount of weight loss that occurred after enzymatic treatments was connected to the fabric’s thickness. The higher the weight loss, the thinner the interlock knitted fabric, became, Figure 4. 3.2 Effect of enzymatic treatments on the compression properties of interlock knitted fabric Compression properties are an important parameter for fabric hand, especially for expressing a feeling of fullness. Knitted fabrics are characterised by their smooth and soft touches. The compression properties of knitted fabrics depend on yarn fineness, structural parameters and, the linear density of the yarn. During the effects of transverse load on knitted fabric, loop movements appear in plain fabrics and, at the same time,
Weight loss %
Enyzme A
18.00
Enyzme B1
Thickness loss %
Enyzme B2
Enyzme C
Enyzme D
14.00
9.66 10.23
7.95
2.41
3.17
3.21
2.27
2.09
3.42
3.41
2.20
2.67
2.81
5.19
4.81
KF-D-5
2.00 0.90
2.34
1.66
3.98 3.53 2.81
KF-D-4
3.28
4.00
6.25
6.25
KF-D-3
6.37 4.97
KF-D-2
6.00
13.07 11.36 11.93
10.00
9.66
5.68
0.97
0.90
KF-C-3
KF-C-2
KF-C-1
KF-B2-7
KF-B2-6
KF-B2-5
KF-B1-4
KF-B1-3
KF-B1-2
KF-B1-1
KF-A-4
KF-A-3
KF-A-2
0.00 KF-A-1
Figure 4. Comparison of weight loss percentage with thickness loss percentage obtained by different treatments’ conditions on interlock knitted cotton fabric
9.09
10.00 8.00
13.64
12.50
12.00 %
17.05 17.05
15.34
16.00
KF-D-1
66
friction arises regarding the lengths of the knitted loops. Compression according to the KES is defined as that exerted in a direction perpendicular to the surface of the analyzed sample and not as the stress, which is the inverse of tensile stress (known as longitudinal compression) (Bishop, 1996; Kawabata, 1980). The compression properties were measured under a known pre-tension. The recovery properties were measured by keeping the compressive load at the same rate at which it was applied. As a reference value, the thickness T0 measured at a pretension of 0.5 cN/cm2 is taken and the measuring test is continued up to a maximum pressure Fp of 50 cN/cm2, and after that the corresponding fabric thickness is denoted as Tm. Thickness is highly correlated with compression energy WC in cNcm/cm2, which represents the energy required to compress the sample to the prefixed maximum load level, Figure 5. The used compression energy WC and compressional resilience RC during the measuring process are calculated in the following way (Bishop, 1996; Kawabata, 1980):
KF-C-4
IJCST 23,1
Code of farbric
50
30
20
10
Figure 5. KES-FB3 pressure-thickness curve of interlock knitted fabric
2.0
1.6
To
1.2
Tm
0.8
Thickness T/mm
0.4
0.0
Fp/cNcm–2
40
WC ¼
Z
T0
F · dT
ð1Þ
WC 0 £ 100 WC
ð2Þ
Tm
RC ¼
where WC0 - is the recovery energy given by the pressure of the recovering process: Z T0 0 P 0 · dT WC ¼
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67
Tm
The gained results have shown the loss of compression energy WC of knitted fabrics during enzymatic treatments when increasing the dosage. The higher the thickness loss of the knitted fabric, the lower compression force WC was needed for all kinds of enzymes’ treatments, Table II. Higher compression force WC rather than referenced was measured for all treated samples at dosage 1.0 g/l; however, with increasing dosages of enzymes, the compression force became smaller. The sample KF-B2-4 treated with enriched EGI I enzyme with a dosage of 5.0 g/l needed smaller compression energy WC, having 0.48 Nm/m2, than for the referenced, with 0.53 Nm/m2. The similar appearance was found out in knitted sample KF-C-4 treated with 1.8 g/l enriched EGI I cellulose. The enzymes A and D T. reesei whole cellulase with varied side activities had a lower influence on the compressional energy WC of used knitted fabrics. Furthermore, the measured values of compressional resilience RC decreased when increasing the enzymes’ dosage. Therefore, the treated knitted fabric becomes less capable of relaxation.
Dosage (g/l) Reference KF-A-1 KF-A-2 KF-A-3 KF-A-4 KF-B1-1 KF-B1-2 KF-B1-3 KF-B1-4 KF-B2-5 KF-B2-6 KF-B2-7 KF-C-1 KF-C-2 KF-C-3 KF-C-4 KF-D-1 KF-D-2 KF-D-3 KF-D-4 KF-D-5
0.0 1.0 2.0 3.0 5.0 1.0 2.0 3.0 5.0 1.0 3.0 5.0 0.4 0.7 1.1 1.8 0.7 1.4 2.1 3.6 5.0
WC (Nm/m2) Measurement Deviation (%) 0.53 0.74 0.62 0.61 0.58 0.63 0.63 0.52 0.48 0.66 0.64 0.61 0.71 0.62 0.55 0.50 0.77 0.75 0.62 0.53 0.53
– 39.62 16.98 15.09 9.43 18.87 18.87 2 1.89 2 9.43 24.53 20.75 15.09 33.96 16.98 3.77 2 5.66 45.28 41.51 16.98 0.00 0.00
RC (%) Measurement Deviation (%) 50.23 43.05 43.43 40.73 42.10 42.55 40.85 40.65 46.34 45.63 41.19 39.79 40.11 43.77 44.12 43.00 39.01 38.21 42.97 40.37 48.45
– 214.29 213.54 218.91 213.54 215.30 218.67 219.07 27.74 29.16 218.00 220.79 220.14 212.87 212.16 214.39 222.34 223.94 214.45 219.64 23.55
Table II. The change of compression force and compression resilience for different cellulose enzymatic treatments
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3.3 Effect of enzymatic treatments on the extension of interlock knitted fabric Knitted fabrics, unlike woven fabrics, are also very extensible under low tensile load thanks to their structure. Tensile testing, using KES-FB, is very useful measuring test because it is undertaken within 0-10 percent strain, instead of 490 cN/cm, as suggested for woven fabrics. With reference to the load-elongation diagram in Figure 6, the maximum relative extensibility, marked as EMT (percent) is directly measured. The deformational work WT (cNcm/cm2), linearity LT (2 ), and tensile resilience RT (percent) are then calculated (Kawabata, 1980). Linearity is a measurement regarding any deviation in the load-extension curve from a straight line. Smaller values (less than 5 percent) represent a less elastic and softer knitted fabric. Lower values (up to 35 percent) for tensile resilience promote fabric softness, but the values usually increase during fabric finishing as a result of interfibrial force reduction. The extension properties of interlock knitted cotton fabric after treatment with different enzymes, enzyme concentrations, and treatment conditions were measured using the KES-FB1 measuring system and were evaluated as tensile strain EMT percent, in both wales and course directions at a tensile force of 49 cN/cm. The results are shown in Figure 7(a) and (b). The obtained results for tensile strain in comparison with the non-treated (referenced), and enzyme-treated knitted fabrics show different changes in tensile strain EMT after enzymatic treatment against tensile force in both the course and wales directions. By increasing the dosage of any kinds of enzymes the tensile strain became higher when compared to untreated knitted fabric. The lowest increase in tensile 50 WARP
F cN/cm
40 30
WEFT
20 10
Figure 6. KES-FB load-elongation curve for interlock knitted fabric
4.0
8.0
12.0 E (strain) %
19 15
EMT-2 (%)
EMT-1 (%)
17 13 11 9 7
Figure 7. Tensile strain of different enzyme-treated interlock knitted fabric
5 0.0
0.5
1.0
1.5
A
2.0 2.5 3.0 3.5 Enyzme dosage (g/l) B1
B2
C
4.0
4.5
5.0
16.0
20.0
24.0
65 60 55 50 45 40 35 30 25 20 0.0
0.5
1.0
D
(a) Notes: (a) In course; (b) in wales directions after enzymatic treatments
1.5
A
2.0 2.5 3.0 3.5 Enyzme dosage (g/l) B1
B2
(b)
C
4.0
D
4.5
5.0
strain from 8.13 percent (untreated) to 8.81 percent in wales and from 27.9 percent (untreated) to 30.9 percent in course directions had enzyme A under all selected treatment conditions. The highest increase of up to 17.9 percent in wales and 62.3 percent in course directions was determined in connection with enzyme D. The remaining enzymes’ treatment had a more or less unpredictable impact on tensile strain, therefore additional research work is needed. 3.4 Effect of enzymatic treatments on the surface properties of interlock knitted fabrics Fabric friction, which is defined as the resistance to motion, can be detected when a fabric is rubbed mechanically against itself or tactually among the fingers. The fiction properties of knitted fabrics have considerable importance in the fields of both technological and subjective assessments. Friction measurement using KES-FB4 provides a mean value of friction coefficient and between static and dynamic coefficients of friction metal to the friction (Bishop, 1996). The coefficient of friction is dimensionless and is calculated using equation (3) (Figure 8): Z 1 X R MIU ¼ m ¼ mðxÞdx ¼ ð3Þ X 0 N Where: x – displacement of the contactor on the surface of the specimen; X – the measurement area; 2 cm is taken in this measurement; m – coefficient of friction; R – friction force; and N – normal force.
Enzyme treatments
69
The knitted structures are not absolutely flat and smooth. The knitted loop structure may not always be noticeable because of the effect of structural fineness, fabric distortion, additional pattern threads, or the masking effect of the finishing process (Spencer, 2001). Surface roughness influence on fabric hand and plays a significant role in the end use of the fabric. The geometrical-roughness probe is sufficiently sensitive to any response to surface rugosities due to differences in yarn and fabric structure (Bishop, 1996). These properties are studied using the KES-FB4 tester from a physical (coefficient of friction (MIU) and its absolute deviation mean deviation in the frictional force), and a geometrical (geometrical roughness (SMD)) point of view. The geometrical roughness is calculated using the equation (4) (Figure 9): 0.4
MIU
0.2 0.0 –0.2 –0.4 0
1 L (cm)
2
Figure 8. Coefficient of interlock knitted fabric’s friction
IJCST 23,1
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SMD ¼
1 X
Z
X
jTðxÞ 2 Tjdx
ð4Þ
0
where: T – thickness, mm; and T – mean value of T. The surface properties of knitted interlock were measured in courses and wales as well as on the face and reverse side of the sample, because knitted interlock used in the study was brushed on to the reverse side of the fabric. They were evaluated as a coefficient of friction MIU and geometrical roughness SMD using the KES-FB3 measuring system. The structured yarn on the reverse-side of the knitted fabric is brushed and so is less resistant to enzyme treatments. After enzyme treatment these fabrics obtain more rugosity and have a predisposition to pilling. Arising from this, the knitted fabric has a higher value of friction coefficient on the reverse side as against the face side, Figure 10. Moreover, after the fabric was treated with any of the enzyme, the coefficient of friction is reduced on the face and reverse sides when compared to the referenced sample. Increase in the coefficient of friction on both sides of the fabric occurs in samples treated with a dosage of 1.0 g/l by enzyme B1 enriched EGI II, and samples treated with enzyme dosages 1.0 and 3.0 g/l by enzyme B2. SMD
40
mm
20 0 –20
Figure 9. Geometrical roughness of interlock knitted fabric
–40 0
1 L (cm)
MIU-1-face side
2
MIU-1-reverse side
0.3000 Enyzme B1
Enyzme B2
Enyzme C
Enyzme D
0.2000 0.1500 0.1000 0.0500
Code of fabric
KF-D-5
KF-D-4
KF-D-3
KF-D-2
KF-D-1
KF-C-4
KF-C-3
KF-C-2
KF-C-1
KF-B2-7
KF-B2-6
KF-B2-5
KF-B1-4
KF-B1-3
KF-B1-2
KF-B1-1
KF-A-4
KF-A-3
KF-A-2
KF-A-1
0.0000 R
Figure 10. Effects of different cellulose treatments on friction coefficients in the wales direction of investigated interlock knitted fabrics
Coefficient of friction
Enyzme A 0.2500
The measuring sensor, consisting of five U-formed wires, slides on the surface of the fabric, thus measuring the friction coefficient using the KES-FB system. The coefficient of friction is equivalent to fabric embossment in front of the measuring sensor because of the knitted fabric’s surface topography during measuring. This is especially characteristic for thicker and easily compressible materials, knitted fabric in this case. When the coefficient of friction is measured in a wales direction the measuring sensor slides over the courses and the above-mentioned phenomenon is more pronounced. The face side of the unbrushed knitted fabric has a higher value of friction coefficient in the course direction, while the sensor slides over the knitted fabric’s surface, Figure 11. The coefficients of friction in the course direction change unpredictably in comparison with the untreated knitted fabric. It is, therefore, hard to evaluate why these changes occur. The answer could be connected with the manner of measuring the friction coefficient or the influence of the enzymes’ treatment conditions. Geometrical roughness gives information about the surface in connection with their macro structure and, thus, the quality of treatment. The measured roughness presents a deviation from the straight line of the fabric’s surface, when a measuring sensor made from one U-formed wire of diameter 5 mm slides over the knitted fabric’s surface. Higher values for geometrical roughness on the reverse side are obtained when comparing the face and reverse sides of the investigated knitted fabrics. Higher values for geometrical roughness are obtained using all enzymatic treatments because of pilling appearing on the reverse side in all enzymatic treatments. Higher modification is observed for samples treated in concentrated 1.0 g/l enzymes without any kinds of enzymes, and treatment time, Figure 12. An identical phenomena also arises for an embossed fabric when measuring geometrical roughness. The measuring sensor slides over the course, as well. The given measured values in the wales direction are much higher than in the course direction. According to the referenced sample of knitted fabric, the lowest changes in surface roughness in the course direction occur for samples treated with T. reesei cellulases A, and the highest obtained changes are apparent in samples treated with enzyme enriched EGI II marked as B2, Figure 13. MIU-2-face side Enyzme A
Enyzme B1
71
MIU-2-reverse side
Enyzme B2
Enyzme C
Enyzme D
0.3000 0.2500 0.2000 0.1500 0.1000 0.0500
Code of fabric
KF-D-5
KF-D-4
KF-D-3
KF-D-2
KF-D-1
KF-C-4
KF-C-3
KF-C-2
KF-C-1
KF-B2-7
KF-B2-6
KF-B2-5
KF-B1-4
KF-B1-3
KF-B1-2
KF-B1-1
KF-A-4
KF-A-3
KF-A-2
KF-A-1
0.0000 R
Coefficient of friction
0.3500
Enzyme treatments
Figure 11. Effects of different cellulose treatments on friction coefficients in the course direction of a knitted fabric
IJCST 23,1
Enyzme A
Enyzme B1
Enyzme B2
Enyzme C
Enyzme D
2.50 2.00 1.50 1.00 0.50
KF-D-4
KF-D-5 KF-D-5
KF-D-3
KF-D-4
KF-D-2
KF-D-1
KF-C-4
KF-C-3
KF-C-2
KF-C-1
KF-B2-7
KF-B2-6
KF-B2-5
KF-B1-4
KF-B1-3
KF-B1-2
KF-B1-1
KF-A-4
KF-A-3
KF-A-2
R
0.00 KF-A-1
Figure 12. Effects of different cellulose treatments on geometrical roughness in the wales direction of interlock knitted fabric
SMD-1-reverse side
3.00 Geometrical roughness (mm)
72
SMD-1-face side
Code of fabric
SMD-2-face side Enyzme A
Enyzme B1
Enyzme B2
Enyzme C
Enyzme D
7.00 6.00 5.00 4.00 3.00 2.00 1.00 KF-D-3
KF-D-2
KF-D-1
KF-C-4
KF-C-3
KF-C-2
KF-C-1
KF-B2-7
KF-B2-6
KF-B2-5
KF-B1-4
KF-B1-3
KF-B1-2
KF-B1-1
KF-A-4
KF-A-3
KF-A-2
R
0.00 KF-A-1
Figure 13. Effects of different cellulose treatments on geometrical roughness in the course direction of interlock knitted fabric
Geometrical roughness (mm)
8.00
SMD-2-reverse side
Code of fabric
4. Conclusions The aim of this research was to investigate the effects of different enzymes of T. reesei whole cellulase with varied side activities, and engineered enzymes that enrich EGI II EGI I, suitable for cotton knitted fabrics using different treatment conditions on the tensile, compression, and surface properties of interlock knitted fabric. After each of the enzyme treatments, the interlock knitted fabrics lost part of their weight and, therefore, they became thinner. Furthermore, the extension properties become higher in both directions with regard to the untreated knitted fabric for all used enzymes and carried out treatments. Some difficulties were found in obtaining the exact answer to the question as to how the surface properties of knitted fabrics change after different enzyme treatments when using the KES-FB measuring system. The fabric structures are too rough in contrast with the sensibility of sensors when measuring friction coefficient and geometrical roughness. Therefore, other measuring equipment is recommended for further investigations. References Bishop, D.P. (1996), “Sensory and mechanical properties”, Textile Progress, Vol. 26 No. 3, pp. 1-62. Cavaco, P. and Gu¨bitz, G.M. (2003), Textile Processing with Enzymes, Woodhead, Cambridge.
DIN 53884 (1976), Testing of textiles, determination of mass of knitted fabrics, Deutsches Institut Fur Normung E.V. DIN 53883 (1983), Testing of textiles, determination of the number of courses, wales and stitch density of knitted fabrics, Deutsches Institut Fur Normung E.V. Genencor (2004), “Denim brochure”, available at: www.genencor.com (accessed 10 April 2009). Heikinheimo, L. (2002), “Trichoderma reesei cellulases in processing of cotton”, doctor thesis, Tampere University of Technology, VTT Biotechnology, Espoo, December. Kawabata, S. (1980), The Standardization and Analysis of Hand Evaluation, 2nd ed., Textile Machinery Society of Japan, Osaka. Ojapalo, P. (2002), “Commercial applications”, paper presented at the VTT Textile Seminar, Tampere. Spencer, J.D. (2001), Knitting Technology: A Comprehensive Handbook and Practical Guide, 3rd ed., Woodhead, Cambridge. Stjepanovicˇ, Z. and Karba, M. (2005), Development of the Technology for Production of High-quality Knitted Fabrics, University of Maribor, Maribor. Verstraete, D. (1994), “Knitting technology for technical applications”, paper presented at the 46th Congress of International Federation of Knitting Technologies, Centexbel, Ghent. Xiaoping, R. and Chou, T.W. (1996), “Experimental and theoretical studies of the elastic behaviour of knitted-fabric composites”, Composite Science and Technology, Vol. 56 No. 12, pp. 1391-403. About the authors Simona Jevsˇnik is an Assistant Professor for Clothing Engineering. Her research interests include garment production processes, processing properties of textile fabrics, and simulation of textile forms. Simona Jevsˇnik is the corresponding author and can be contacted at: simona.jevsnik@ vsd.si Zoran Stjepanovicˇ is an Associate Professor for Textile Technology and Computer-based Information Systems for Textile Applications. His research interests include mechanical textile technologies, above all knitting and spinning, machine learning, and computer graphics. Lea Heikinheimo is a Principal Lecturer at Lahti University of Applied Sciences. Her research interests comprehend finishing and modification of textile materials, above all enzyme treatments on woven, and knitted fabric structures. Karl Gotlih is an Associate Professor at the Faculty of Mech. Engineering in Maribor. His research interests are in the field of mechanical properties of viscoelastic materials, the multi-body dynamics, and robotics.
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Application of design for disassembly in men’s jacket
Sustainable apparel design
A study on sustainable apparel design Hae Jin Gam Department of Family and Consumer Sciences, Illinois State University, Normal, Illinois, USA
Huantian Cao
83 Received 16 March 2010 Revised 8 June 2010 Accepted 8 June 2010
Department of Fashion and Apparel Studies, University of Delaware, Newark, Delaware, USA
Jaclyn Bennett and Caroline Helmkamp Department of Family and Consumer Sciences, Illinois State University, Normal, Illinois, USA, and
Cheryl Farr Department of Apparel, Educational Studies and Hospitality Management, Iowa State University, Ames, Iowa, USA Abstract Purpose – Combining of natural and synthetic materials in apparel products caused problems with material recovery, reuse, recycling, or composting at the end of product life. The purpose of this paper is to investigate the application of design for disassembly methods in the design and construction of men’s jacket. With this type of design, consumers and manufacturers can easily compost, recycle, or reuse different materials and components at the end of the garment’s usable life. Design/methodology/approach – After analyzing the men’s jackets available in the market and identifying obstacles to disassembly, the authors designed and constructed a man’s jacket that can be easily disassembled. The jacket design for disassembly focused on material selection, jacket design, and stitch evaluation and selection. The disassembly time was also measured. Findings – It was found that minimizing material diversity and sewing similar materials together whenever possible, replacing fusible interfacing with blind hemming stitches under the collar and on the backside of the lapel, and using an appropriate low density stitch to sew the wool outer shell and polyester lining together, can make the jacket disassemble easily into a compostable outer shell and recyclable lining within 1.5 min. Originality/value – This research provided a pilot study demonstration of applying “design for disassembly” in apparel design and construction. The findings could be employed in different apparel products to help reduce environmental pollution and resource depletion problems related to the apparel industry. Keywords Sustainable design, Recycling, Clothing, Textiles Paper type Research paper
The work was funded by The US Environmental Protection Agency under a STAR Research Assistance Agreement No. SU833517 (P3 Award: A National Student Design Competition for Sustainability Focusing on People, Prosperity, and the Planet). The authors thank Dr Lauren Heine for the help in material assessment and Mr John Bishop of Pendleton Woolen Mills (Portland, Oregon, USA) for providing the Cradle to Cradle CertifiedCM wool fabric.
International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 83-94 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107289
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Introduction Behind fast-changing fashion trends, the apparel industry creates substantial environmental and resource depletion problems, which are consequences of the entire textile lifecycle, from production of materials to disposal of clothing. An average consumer in the UK throws away 30 kg of clothing and textiles each year, according to a University of Cambridge (2006) study. Similarly, Americans throw away, on average, 68 pounds of clothing per person per year (Claudio, 2007). When used apparel products are disposed of in a landfill, large quantities of valuable materials and resources are lost. As environmental impacts from the textile and apparel industry have begun to receive public attention, the designers’ role in sustainability has also been emphasized. In the 1990s, some apparel companies, such as Esprit and Patagonia, implemented sustainable apparel design and production processes. Their practices have intensified during the current decade, employing renewable materials and natural energy (Solomon and Rabolt, 2004). In the last few years, a more holistic approach toward sustainability has been emphasized, and the green movement has been extended to more and smaller apparel companies (Black, 2008). Poole et al. (2009) suggested that employing renewable materials, using environmentally friendly and commercially viable processes, and having biodegradable or recyclable qualities are essential characteristics for environmentally friendly apparel. To combat resource depletion and provide product designers a new way to design, that eliminates many environmental problems, McDonough and Braungart (2002) developed a “cradle to cradle” design model. In the “cradle to cradle” model, materials are considered “nutrients.” Every material is classified as either a “biological nutrient” that will easily biodegrade without depositing toxins, or a “technical nutrient” that will continuously circulate as valuable material within “closed-loop” industrial cycles. Gam et al. (2009) incorporated the “cradle to cradle” model into existing apparel design models (May-Plumlee and Little, 1998; LaBat and Sokolowski, 1999) to develop a sustainable apparel design model, called “Cradle to cradle apparel design” (C2CAD). The C2CAD model was implemented in the design and production of children’s knitwear using organic cotton yarns and environmentally friendly dyes (Gam et al., 2009). Within the area of apparel design, natural textile fibers are typically classified as biological nutrients, meaning they can biodegrade, and synthetic fibers are typically technical nutrients that can be recycled through industry. Though it is possible to use 100 percent biological nutrients, e.g. cotton yarns to produce children’s knitwear, most apparel products use a combination of different materials. McDonough and Braungart (2002) called a mixture of biological nutrients and technical nutrients a “monstrous hybrid,” causing waste and pollution because neither nutrient can be salvaged after use. To design an eco-friendly product in which both biological and technical nutrients are used, McDonough and Braungart (2002) suggested the concept of “design for disassembly” as a strategy for aiding material recovery, reuse, recycling, or composting. Products that are designed for disassembly are easily broken down into their separate biological and technical nutrients. Design for disassembly was also incorporated into the C2CAD model by Gam et al. (2009), for apparel products composed of both natural and synthetic fibers. The concept of design for disassembly was first established during the 1970s (Bogue, 2007). In the past few decades, environmental pollution and resource depletion have gained public awareness, and product lifecycle analysis has become more and more important in industry of all kinds. Because product materials have a significant recycled value only when they can be divided into clean, separate types, interest in design for
disassembly has been growing (Jovane et al., 1993; Harjula et al., 1996; Sodhi and Knight, 1998). Bogue (2007) investigated different manufactured products and concluded that successful design for disassembly requires thorough consideration of three critical stages: selection and use of materials; design of components and product architecture; and selection and use of joints, connectors, and fasteners. Currently, most of the research and industrial applications of design for disassembly are related to automotive components and electronic equipment (Duflou et al., 2008). The purpose of this study was to investigate the application of design for disassembly in apparel production, so that consumers and manufacturers can easily compost, recycle, or reuse different materials and components at the end of the garment’s life. Jackets are usually made from both natural and synthetic fabrics using complex sewing and assembly techniques. According to the International Fabricare Institute, the average of life expectancy of suits was from two to four years depending on the fabric types and quality (Brown and Rice, 2000). Owing to rapid fashion changes, consumers may purchase and dispose of men’s jackets even more often. Without effective material management for these used apparel products, the apparel industry causes a huge environmental impact related to solid waste and depletion of valuable resources. Because of its complexity, the researchers selected the men’s blazer as the sample apparel product. In this study, the researchers first evaluated the disassembly obstacles inherent to men’s blazers available in the market and then applied design for disassembly to the jacket design and construction.
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Obstacles to disassembling the blazers The researchers purchased three used men’s blazers of different brands and examined them to identify the traditional construction process of a jacket and the obstacles that make it difficult to disassemble. Each of the three blazers had a similar design with the basic notch/lapel collar; three button closure; armhole princess line; welt pocket with flat, two piece sleeve; and vent at the end of sleeve and center back, as shown in Figure 1. Basic notch/lapel collar
3 buttons Armhole princless line
Welt pocket with flap Two piece sleeve Vent
Figure 1. The design of a man’s jacket
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The researchers identified the materials in the outer shell and lining fabrics, threads, buttons, interfacing, and places where biological and technical nutrients jointed together. Because, in most places, the biological and technical nutrients were sewn together, the researchers identified the stitch sizes of the three blazers. To separate all possible components of the blazers, researchers used a seam ripper to cut the sewing threads. The outer shell and lining fabrics were separated starting at the bottom hemline of the jacket and moving up the side seam and sleeve hemline. Then, researchers separated polyester buttons from the outer shell fabric and removed fabrics details, such as pockets. Finally, shoulder pads, sleeve headers, and chest pieces, each of which were constructed with two or three different material types, were separated from the outer shell, but these pieces could not be further disassembled because adhesive was used to combine the layers together. While dissembling the jackets, researchers timed each phase of work. The results are summarized in Table I, and the components present after disassembly are shown in Figure 2. The researchers identified the following obstacles to disassembling the three blazers: (1) Two of the jackets used fiber blends – a rayon/polyester blend in the lining of jacket 2 and a wool/elastane blend in the outer shell of jacket 3. These blends are a mixture of biological and technical nutrients and cannot be separated in disassembly, a “monstrous hybrid” according to McDonough and Braungart (2002). (2) Stitches combining the outer shell and lining were too dense for easy disassembly. All three jackets used nine to 14 stitches per inch for the side and neckline seams and eight to nine stitches per inch for the bottom hem. Jackets 1 and 3 used similar sized stitches for the sleeve hem, but jacket 2 used relatively bigger stitches, 5 per inch. The times required to separate the biological and technical nutrients for each jacket were between 20 min 57 s and 23 min 27 s. (3) Material contaminations, a mixture of biological and technical nutrients, existed in all three jackets after disassembly. Polyester threads (technical nutrients) remained in wool fabrics (biological nutrients) in button holes and other sewing points. Fusible interfacing material (technical nutrients) remained in outer shell wool fabric (biological nutrients), shoulder pads, sleeve headers, and chest pieces. Because fusible interfacing was used, it was not possible to separate the interfacing from the wool fabric, and material contamination could not be avoided. A men’s jacket designed for disassembly To combat the disassembly obstacles in conventional jacket construction, the researchers focused on the three critical stages suggested by Bogue (2007): material selection, jacket design, and selection and use of joints. The researchers’ goals were to minimize disassembly effort, time, and material contamination. Material selection According to the 12 principles of green engineering (Anastas and Zimmerman, 2003), material diversity in multi-component products should be minimized to promote disassembly and value retention. To minimize material diversity and facilitate disassembly, the jacket was designed with two main components, a natural outer shell (biological nutrients) and a synthetic lining (technical nutrients), shown in Figure 3.
Fabrics and materials Outer shell
Jacket 1
Jacket 2
100 percent wool
100 percent wool
Jacket 3
Lining
100 percent acetate
Thread
100 percent polyester Fusible non-woven 100 percent polyester
97 percent wool, 3 percent elastane 54 percent rayon, 46 percent 100 percent polyester; sleeve: 100 percent polyester acetate 100 percent polyester 100 percent polyester Fusible non-woven Fusible non-woven 100 percent polyester 100 percent polyester
75.500 41.2500 1400
7700 4300 13.500
Interfacing Buttons Length of seam line Side seam Bottom hem Sleeve hem Stitch size (stitches per inch) Side and neckline Bottom Sleeve Pocket Places where biological and technical nutrients mixed or jointed
Time to separate biological Shell/ and technical nutrients lining Buttons/ shell Pockets Shoulder pads Total
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74.500 4200 13.500
14 10 9 8 10 9 8 5 9 14 10 9 Blend fabrics were used in lining ( jacket 2) and outer shell (jacket 3) Polyester thread was used to assemble wool or blended wool fabrics in outer shell 100 percent polyester buttons were attached to outer shell (wool or wool blend) Welts and pockets were made of wool or wool blend outer shell and polyester or (rayon/polyester blend) lining sewn to wool outer shell using polyester thread Fusible interfacing was used in outer shell 9 min 10 s 10 min 27 s 9 min 20 s 1 min 36 s
1 min 57 s
1 min 10 s
6 min 16 s 3 min 55 s
6 min 48 s 4 min 15 s
6 min 15 s 5 min 48 s
20 min 57 s
23 min 27 s
22 min 33 s
Wool fabric was chosen as the outer shell for the men’s jacket. As a biological nutrient, the wool material should return to nature without depositing synthetic materials or toxins (McDonough and Braungart, 2002). After consulting with an external specialist, the researchers found that Pendleton Woolen Mills (Portland, Oregon, USA) produces 100 percent wool flannel fabrics that are certified as “cradle to cradle” biological nutrients by McDonough Braungart Design Chemistry (MBDC, Charlottesville, Virginia, USA). The Cradle to Cradle Certification warrants that fabric production, including dyes and chemicals used, has passed rigorous testing and evaluation protocols
Table I. Obstacles for easy disassembly of men’s sport jackets
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2
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5
6 7
4
3
8
Figure 2. Components after disassembling a conventional man’s jacket
Notes: 1 outer shell 2 lining 3 chest pieces 4 shoulder pads 5 sleeve headers 6 buttons 7 pocking facing 8 pocket lining; Contaminated parts: 1 front bodice, lapel, collar, bodice hem, sleeve hem, flaps were contaminated by fusible interfacing; 3 two layers of interfacing used adhesive and they are different fabrics; 4 two layers were attached with adhesive to the pad; 5 Two of three layers used adhesive
Inside of jacket
Figure 3. Design for disassembly man’s jacket
Outer shell Lining Outer shell and lining assembly place
and has been deemed safe for human and environmental health. The researchers decided to use Pendleton Cradle to Cradle CertifiedCM wool fabric for the outer shell of the jacket. According to the “cradle to cradle” model (McDonough and Braungart, 2002), the most effective recovery method for biological nutrients is composting to return the nutrients to the soil. Because a mixture of natural materials can be biodegraded
in the composting process, different types of biological nutrients were affixed to the outer shell of the 100 percent wool fabric. Organic cotton threads, also biological nutrients, were used in sewing the wool fabric outer shell. The buttons affixed on the wool outer shell were natural Tagua wood buttons. Tagua nuts, an ecologically sustainable product of the rain forest, are harvested from palm trees and are known as an alternative to elephant ivory (Smith, 1990). For the lining of the jacket, 100 percent satin polyester fabric, a synthetic material, or technical nutrient, was used. According to the “cradle to cradle” model, the best method of recovering technical nutrients is recycling. In order to recover the same quality technical materials after recycling rather than “downcycling” to lower quality materials, it is important to maintain the purity of the material and avoid mixing different types of synthetic materials (McDonough and Braungart, 2002). Therefore, 100 percent polyester threads were used to sew the lining. In this design, the only points at which biological and technical nutrients are joined are the sewing lines between the outer shell and lining (dotted lines in Figure 3). Organic cotton threads were used to sew the outer shell and lining together. The design for disassembly focused on the easy separation of the outer shell and lining, while maintaining a wearable product during use. Jacket design The basic blazer design was the same as that shown in Figure 1. To minimize material use, contamination, and effort for disassembly, the researchers decided not to use buttons on the sleeves, shoulder pads, sleeve headers, or chest pieces. Researchers decided that the jacket prototype without these additions still retained an attractive appearance. The fusible interfacing material on the wool fabric was a major obstacle in the conventional men’s jacket disassembly. In a suit jacket, interfacing is applied to the collar and lapel for a crisp finished edge (Armstrong, 2006). To avoid material contamination and maintain the biological nutrient nature of the wool fabric, interfacing had to be removed from the design. At first, the omission of the interfacing made the collar and lapel have an unfinished appearance. This problem was solved by using blind stitches under the collar and on the backside of the lapel. Figure 4 shows that blind stitches can give the collar and lapel a crisp finished appearance without interfacing. Organic cotton threads were used in the blind stitches and a mixture of organic cotton and wool does not change the biological nutrient nature of the material. Evaluation of sewing stitches ( joints) As mentioned, organic cotton threads were used to sew the wool outer shell and polyester lining together. The stitches in this type of design must be durable during consumer use but easy to separate at the end of the product’s life. After visually inspecting and manually pulling three hand stitching types – blind hemming stitch, catch stitch, and slip stitch – and three machine stitching types – fagot stitch, normal straight stitch in different stitch sizes, and blind hemming stitch – the researchers decided to focus on the machine – sewn, normal straight stitch in different sizes and the blind hemming stitch for further investigation in the design process. A sewn durability test was conducted in accordance with the ASTM method D 1683-04 (ASTM International, 2006), a standard test method for failure in sewn seams of woven apparel fabrics, using a Thwing-Albert EJA universal materials testing instrument
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Figure 4. Blind stitches to replace fusible interfacing
Note: Black color thread in the left image was used for visibility
(Thwing-Albert Instrument Co., West Berlin, New Jersey, USA). The samples were made by sewing two pieces of Pendleton wool fabrics together using organic cotton thread. The stitch types and ANOVA result for sewn strength are summarized in Table II. Fisher’s LSD test showed that there was no significant difference in the sewn strength between the two normal straight stitches, while the sewn strength of the two normal straight stitches were significantly higher than the blind hemming stitch. Therefore, it was determined that using a normal straight stitch with a size of six stitches per inch to sew the outer shell to the lining of the jacket will not reduce the durability. Construction The researchers used organic cotton thread and normal straight stitches with a size of ten stitches per inch to sew wool fabrics together, and polyester thread and a normal straight stitch with ten stitches per inch to sew the polyester lining together. The normal straight stitch with ten stitches per inch was also used in detail areas, such as the pockets, to improve durability. To avoid material contamination, organic cotton threads were used to make the three button holes and sew three Tagua buttons to the wool fabric in the front of the jacket. Owing to the thickness of the wool flannel fabric, the assembly method of the pockets had to be adjusted, and the flap of the pocket had to be lengthened for an improved appearance. Blind stitches were used under the collar and on the backside of the lapel to replace fusible interfacing. Finally, the outer shell and lining were sewn together using organic cotton thread. The finished jacket is shown in Figure 5. Stitch type Table II. ANOVA result of sewing strength test
n
Normal straight stitch (ten stitches/inch) 8 Normal straight stitch (six stitches/inch) 10 Blind hemming stitch 9
Mean (lbs) s (lbs) F-value p-value Fisher’s LSD 60.6 52.6 8.2
8.9 13.8 2.2
73.52
0.00
1 1 2
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Figure 5. The design for disassembly man’s jacket
Disassembly of the men’s jacket Owing to a careful avoidance of material mixture and contamination in design, the men’s jacket can be disassembled in one step by separating the biological nutrients outer shell and technical nutrients lining. The disassembly started with cutting three to four sewing stitches at the bottom hemline of the jacket using a seam ripper or small scissors and then tearing the outer shell and lining apart by hands, as shown in Figure 6. Three different stitches – a normal straight stitch with ten stitches per inch, a normal straight stitch with six stitches per inch, and a blind hemming stitch – were used to sew the outer shell and lining together. The researchers measured the time it look to separate the outer shell and lining sewn with different stitches. The ANOVA result is in Table III. There was no significant difference in disassembly time between normal stitch with six stitches per inch and blind stitch to sew the outer shell and lining. However, the disassembly time was significantly longer if the outer shell and lining was sewn by normal stitch with ten stitches per inch. Therefore, using a normal stitch with the size of six stitches per inch
Figure 6. Disassembly process
Stitch type
Mean s n (seconds) (seconds) F-value p-value Fisher’s LSD
Normal straight stitch (ten stitches/inch) 5 Normal straight stitch (six stitches/inch) 5 Blind hemming stitch 5
210 70 75
12 10 15
121.06
0.00
1 2 2
Table III. ANOVA result of disassembly time evaluation
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to sew the biological nutrient outer shell and the technical nutrient lining will have a shorter disassembly time while maintaining good durability during use. Within 1.5 minutes, our man’s jacket can be disassembled into two big “nutrient” components (Figure 7): the biological nutrients of the wool outer shell, organic cotton thread, and Tagua buttons, and the technical nutrients of the polyester lining and polyester thread. The disassembly time was only about 7 percent of the time it took to disassemble the jacket made with conventional methods. For the most effective material management, some valuable components, such as the wool outer shell and Tagua buttons, can be recovered and reused in another product. To reuse these components, the integrity of the components must be retained during disassembly, and the disassembly time will increase. A slight contamination of organic cotton thread in the polyester lining fabric did occur on the sewing edge of the outer shell and lining. However, the material cross contamination after disassembly was reduced significantly compared to the conventional jackets. Conclusion It was found that the men’s jackets produced by conventional processes were difficult to disassemble with numerous material cross contaminations, which made it very tough to reclaim valuable materials through reuse, recycling, or composting. This study applied the concepts of cradle to cradle (McDonough and Braungart, 2002), design for disassembly (Bogue, 2007), and the C2CAD model (Gam et al., 2009) to men’s jacket production. Through apparel design and construction, the researchers demonstrated a strategy for minimizing the time and effort required to disassemble the apparel and maximize material recovery. Therefore, the researchers propose the following suggestions for this type of jacket design: . minimize material diversity, and aim to sew similar materials together whenever possible to reduce the required disassembly steps and time; . replace fusible interfacing, a permanent bond, with blind hemming stitches under the collar and on the backside of the lapel; and
Figure 7. Components after disassembling the jacket
Notes: Left – biological nutrients (wool fabrics, organic cotton threads, tagua buttons); right – technical nutrients (polyester fabrics, polyester threads)
.
use an appropriate larger size stitch, i.e. a normal straight stitch with six stitches per inch, to sew biological nutrients (outer shell) and technical nutrients (lining) together.
Following the above suggestions, a men’s jacket, with acceptable durability, was produced, which could be disassembled within 1.5 min to reclaim biological nutrients and technical nutrients with minimum cross contamination. These findings could be applied in different apparel products to help solve environmental pollution and resource depletion problems related to the apparel industry. Though the jacket can be easily disassembled by either consumers or apparel companies using the process is shown in Figure 6, the authors suggest that apparel companies take the leading role. Environmentally driven apparel companies could collaborate with retailers to recover used jackets from consumers and then disassemble them. After disassembly, apparel companies could collaborate with fiber manufacturers to recycle technical nutrients and investigate methods to reuse or compost biological nutrients. In this way, the closed-loop material flow can be accomplished. Future studies should investigate consumers’ acceptance of apparel designed for disassembly, consumers’ willingness to return the used apparel to retailers, and the development of an apparel reclaiming infrastructure with collaborations among industry stakeholders. References Anastas, P.T. and Zimmerman, J.B. (2003), “Design through the 12 principles of green engineering”, Environmental Science & Technology, Vol. 37, pp. 95A-101A. Armstrong, H.J. (2006), Patternmaking for Fashion Design, 4th ed., Prentice-Hall, Upper Saddle River, NJ. ASTM International (2006), “ASTM D 1683-04: standard test method for failure in sewn seams of woven apparel fabrics”, Annual Book of ASTM Standards, 07.01, ASTM International, West Conshohocken, PA, pp. 408-15. Black, S. (2008), Eco-Chic: The Fashion Paradox, Black Dog, London. Bogue, R. (2007), “Design for disassembly: a critical twenty-first century discipline”, Assembly Automation, Vol. 27 No. 4, pp. 285-9. Brown, P. and Rice, J. (2000), Ready to Wear: Apparel Analysis, 3rd ed., Prentice-Hall, Milford, NJ. Claudio, L. (2007), “Waste couture: environmental impact of the clothing industry”, Environmental Health Perspectives, Vol. 115 No. 9, pp. A449-54. Duflou, J.R., Seliger, G., Kara, S., Umeda, Y., Ometto, A. and Willems, B. (2008), “Efficiency and feasibility of product disassembly: a case-based study”, CIRP Annals – Manufacturing Technology, Vol. 57 No. 2, pp. 583-600. Gam, H.J., Cao, H., Farr, C. and Heine, L. (2009), “C2CAD: a sustainable apparel design and production model”, International Journal of Clothing Science and Technology, Vol. 21 No. 4, pp. 166-79. Harjula, A., Rapoza, B., Knight, W.A. and Boothroyd, G. (1996), “Design for disassembly and the environment”, Annals of the CIRP, Vol. 45 No. 1, pp. 109-14. Jovane, F., Alting, L., Armillotta, A., Eversheim, W., Feldmann, K., Seliger, G. and Roth, N. (1993), “A key issue in product life cycle: disassembly”, Annals of the CIRP, Vol. 42 No. 2, pp. 651-8.
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LaBat, K.L. and Sokolowski, S.L. (1999), “A three-stage design process applied to an industry-university textile product design project”, Clothing and Textiles Research Journal, Vol. 17 No. 1, pp. 11-20. McDonough, W. and Braungart, M. (2002), Remarking the Way We Make Things: Cradle to Cradle, North Point Press, New York, NY. May-Plumlee, T. and Little, T.J. (1998), “No-interval coherently phased product development model for apparel”, International Journal of Clothing Science and Technology, Vol. 10 No. 5, pp. 342-64. Poole, A.J., Church, J.S. and Huson, M.G. (2009), “Environmentally sustainable fibers from regenerated protein”, Biomacromolecules, Vol. 10 No. 1, pp. 1-8. Smith, E. (1990), “Will these buttons help save the rainforests?”, Business Week, Vol. 24, p. 137. Sodhi, M. and Knight, W.A. (1998), “Product design for disassembly and bulk recycling”, Annals of the CIRP, Vol. 47 No. 1, pp. 115-18. Solomon, M.R. and Rabolt, N.J. (2004), Consumer Behavior in Fashion, Prentice-Hall, Upper Saddle River, NJ. University of Cambridge (2006), “Well dressed?: the present and future sustainability of clothing and textiles in the United Kingdom”, available at: www.ifm.eng.cam.ac.uk/sustainability/ projects/mass/UK_textiles.pdf (assessed 12 June 2009). Corresponding author Hae Jin Gam can be contacted at:
[email protected]
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Craniofacial measurements of full-term neonates
Craniofacial measurements of neonates
Yong-Mei Deng Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, People’s Republic of China and Apparel and Art Design College, Xi’an Polytechnic University, Xi’an, People’s Republic of China
Kit-lun Yick and Yi-lin Kwok
95 Received 10 August 2009 Revised 12 July 2010 Accepted 12 July 2010
Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, People’s Republic of China, and
Siu-chun Wong Department of Paediatrics, Queen Mary Hospital, Faculty of Medicine, The University of Hong Kong, Hong Kong, People’s Republic of China Abstract Purpose – The purpose of this paper is to measure the craniofacial dimensions of 41 full-term neonates nursed in the Special Care Baby Unit of Queen Mary Hospital in Hong Kong, so as to develop a good-fitting and secure eye-patch protector for protecting neonatal eyes from the strong light in phototherapy. Design/methodology/approach – In total, 14 craniofacial dimensions were measured using a new, safe and non-intrusive method with a close-range photogrammetric system and two dimensions of head circumference and facial arc were measured using manual method with a disposable paper tape in the hospital environment. Birth information of gestation, age, gender, present weight and present length has been recorded. A descriptive statistics was produced based on the measured data. Correlations between each pair of dimensions were investigated and factor analysis was conducted for application on an eye-patch protector development. Findings – Head circumference was identified as the most desirable key dimension of a sizing system for an eye-patch protector. Two head circumferences with the sizes of 310-349 mm and 350-389 mm, respectively, could effectively cover all full-term neonates. Design guidelines were generated according to the measurement of the craniofacial dimensions. Originality/value – This paper presents the craniofacial dimensions of head, eye, nose and ear parts of full-term neonates. Keywords Phototherapy, Eyes, Protective clothing, Head (anatomy) Paper type Research paper
1. Introduction A full-term neonate is defined as an infant born after the 37th week of gestation. About 50-60 per cent of them suffer from jaundice during the first week of their life (Melton and Akinbi, 1999). The main clinical treatment of jaundice is phototherapy which, however, has an inherent problem caused by the strong light it uses, that is, it is potentially harms the cornea and/or retina of the patients (Sisson et al., 1970). Such hazards have normally The research is supported by a grant from the Research Grant Council of the Hong Kong Special Administrative Region, China (No. POLYU 5299/04E).
International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 95-106 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107298
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been mitigated through the use of eye-patch protectors (Dicken et al., 2000). Nevertheless, clinical evidence shows that the existing eye-patch protectors have such drawbacks as ill-fitting and easily displaced. Thus, there is a strong need for developing a type of good-fitting and secure eye-patch protector to minimize the hazard to neonatal eyes. Craniofacial measurements of neonates are essential for the development of an eye-patch protector that can be securely held in place with maximum eye protection and fit to different head shapes and sizes of the neonates. Anthropometric data of neonates typically involves the gross measurements of body weight and length, limb length and the circumferences of chest, head, abdomen and limb, etc. and those measurements can only be obtained manually (Kwok, 1992). However, few researches have been documented in making craniofacial measurements for neonates due to the critical safety requirement, the lack of the subjects’ cooperation and the low-level of psychological acceptance (Merlob et al., 1984). The objectives of the study are to collect the craniofacial data using a new developed close-range photogrammetric system and to present statistical results for developing a new eye-patch protector for neonates (Deng et al., 2007). 2. Experimental design 2.1 Subjects A total of 41 full-term neonates nursed in the Special Care Baby Unit (SCBU) of Queen Mary Hospital (QMH) in Hong Kong were selected in this study. All their ages were less than ten days as jaundice occurred at the first week of his/her life mostly. The study was carried out after their parents/guardians signed a patient consent form, which had been reviewed and approved by the Institutional Review Board of The University of Hong Kong of Hospital Authority Hong Kong Wet Cluster. 2.2 Measured contents The basic information of the 41 full-term neonates including their gestations (B1), ages (B2), present weights (B3), present lengths (B4) and genders (B5) were collected from their clinical records. The craniofacial measurements were determined under the assumption that an eye-patch protector is symmetrical. Based on clinical investigation and theoretical analysis, 16 craniofacial dimensions which are potentially correlated to the development of size system, style design and pattern construction were created from the 13 landmarks (Table I), which are defined in Farkas’ landmark system (Farkas, 1994). The description of the craniofacial dimensions, M1-M2 and P1-P14, is given in Table II and the locations of these craniofacial dimensions are shown in Figures 1-4. 2.3 Instrumentations A newly developed close-range multi-webcam convergent photogrammetric system (CRP system) was used for the measurements of the 14 short-distance dimensions (P1-P14). As shown in Figure 5, the hardware of this system comprises a personal computer and four web cameras (640 £ 480 pixels) with the geometric design of a distance of 300 mm between the subject and the cameras, and the convergence of the cameras’ axes at an angle of 408. This arrangement enables all the critical landmarks to be recognized in at least three photographs. These landmarks fall within two-thirds of the whole craniofacial area covering the neonate’s eyes, nose and right ear area. An image capture programme was developed using Visual Basic 6.0 to guarantee that these photographs
Landmarks
Abbreviations
Glabella Opisthocranion Exocanthion Endocanthion Orbitale superius Orbitale Nasion Pronasale Subnasale Alar curvature point Otobasion superius Tragion Otobasion inferius
G Op Ex En Os Or N prn sn ac obs T obi
Code
Measuring dimensions
M1 M2 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14
Head circumference Facial arc (obsL-g-obsR) The binocular width (exL-exR) The intercanthal width (enL-enR) The height of orbits (os-or) Bridge length (n-prn) The length of the ala (prn-ac) Distance from subnasale to alar curvature point (sn-ac) Nasal tip protrusion (sn-prn) Distance from nasion to alar curvature point (n-ac) Nose height (n-sn) Distance from exocanthion to otobasion superius (exR-obs) Distance from right exocanthion to otobasion inferius (exR-obi) Width of the ear insertion to the head (obs-obi) Distance from right exocanthion to tragion (exR-t) Distance from otobasion superius to tragion (obs-t)
for a living subject were captured simultaneously. A commercially available software, PhotoModeler Version 5.2, was used to mark the features/targets on the obtained photographs, and then, identify the identical features/targets. Based on the mathematic principle of close-range photogrammetry, the coordinates of features/targets can be calculated. With mass coordinated features/targets, a 3D model of the subject could be created. Measurements could be carried out using either the coordinates of features/targets or the 3D model. The CRP system was validated by the Steinbichler Comet optical scanner, whose accuracy is ^0.04-0.07 mm. It was proved that the CRP system was not only accurate with both the systematic and random errors of measurements of craniofacial dimensions being less than 0.5 mm, but also space-saving, portable and convenient to be used in the neonatal units. More importantly, measurements focusing on the eye area of the neonates could be conducted without danger and disturbance to the subject. Apart from the CRP system, a disposable 920 mm-long paper tape was also used in this research for measuring the head circumference (M1) and the facial arc (M2). It is routinely
Craniofacial measurements of neonates 97 Table I. Craniofacial landmarks of neonate related to develop an eye-patch protector
Table II. Description of the craniofacial dimensions
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M1
op
g obs
M2
Figure 1. Locations of craniofacial dimensions M1 and M2
P2
os
enR
P8
exR
P4
n
enL
P6
ac
prn sn
Figure 2. Locations of craniofacial dimensions P1-P4, P6 and P8
P5
Prn
P7
ac sn
Figure 3. Locations of craniofacial dimensions P5, P7 and P9
P9
n
P3
P1
exL or
Craniofacial measurements of neonates
exL
obs P13
P11
99
P12
P14
P10
obi
Figure 4. Locations of craniofacial dimensions P10-P14
3 4
Camera
1
2
40°
300 mm
Computer
Figure 5. The network design of the web-cam CRP system
Neonatal head
used in SCBU in QMH to measure the gross measurement of body length and head circumference for health evaluation. 3. Craniofacial measurement results and discussion 3.1 Univariate analysis A total of 41 neonates, 25 males and 16 females, participated this study. The range, minimum, maximum, mean, standard deviation and coefficient of variation of gestation, age, present weight and present length are summarized in Table III.
Code
Information
Range
Min
Max
X
SD
CV (%)
B1 B2 B3 B4
Gestation (week) Age (day) Present weight (g) Present length (mm)
4.0 10.0 2,230.0 120.0
37.1 0.0 2,265.0 440.0
41.7 10.0 4,495.0 560.0
39.5 3.4 3,214.6 500.0
1.3 2.9 482.0 23.9
35.5 3.2 84.2 15.0
Table III. Basic information of neonates selected for craniofacial anthropometry study
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Based on the measured results of 16 craniofacial dimensions, the univariate analysis including range, minimum, maximum, mean, standard deviation, coefficient of variation and selected percentiles (5th, 50th and 95th) is conducted and reported in Table IV. 3.2 Multiple correlation and factor analysis In order to investigate the relationship between the craniofacial dimensions, correlation analysis was carried out based on following formula: P ðx 2 xÞð y 2 yÞ R ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ð1Þ P P ðx 2 xÞ2 ð y 2 yÞ2 The matrix of correlation coefficients (R) is presented in Table V. The results show: . There is strong correlation amongst the three integral body parameters of B3, B4 and M1 (RB3 *B4 ¼ 0.823, RB3 *M1 ¼ 0.827, RB4 *M1 ¼ 0.756), which are regularly used in the hospital to monitor the growth of the neonates. . Each pair of transverse dimensions including head circumference (M1), facial arc (M2), transverse dimensions of eye (P1, P2) and distance between eye and ear (P10, P11 and P13) has strong-to-mild correlations. Noticeably, correlation coefficients of M1 and other transverse dimensions are significant at 0.01 level (RM1 * M2 ¼ 0.551, R M1 * P1 ¼ 0.701, RM1 * P2 ¼ 0.634, RM1 *P10 ¼ 0.600, RM1 *P11 ¼ 0.753, RM1 *P13 ¼ 0.636). . Each pair of the longitudinal dimensions of nose (P4, P8 and P9) has high correlations, while the longitudinal dimensions of ear (P12 and P14) have mild correlations. . No significant relationship exists between longitude dimensions of eye, ear and nose. Significantly, eye has no significant correlation with other longitude dimensions. . No significant relationship exists between longitudinal and transverse dimensions.
Dimensions
Table IV. Summary of univariate analysis of craniofacial dimensions
M1 M2 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14
Range (mm) Min (mm) Max (mm) X (mm) 62.0 86.0 35.3 8.4 10.4 14.9 7.1 8.7 6.1 14.9 17.8 15.9 14.5 12.5 16.0 7.3
318.0 149.0 55.1 20.7 13.6 13.3 12.5 8.8 8.3 20.1 19.2 36.2 40.8 18.7 35.7 7.8
380.0 235.0 90.4 29.1 24.0 28.1 19.6 17.5 14.4 35.0 37.0 52.1 55.3 31.2 51.7 15.1
346.7 171.0 68.7 24.1 19.5 16.0 15.7 12.6 10.3 23.9 22.8 44.4 46.8 24.6 43.4 12.0
SD
CV (%)
Percentiles (mm) 5th 50th 95th
13.3 14.3 5.9 1.9 2.1 2.6 1.3 1.4 1.4 2.7 3.0 4.0 3.7 2.9 3.8 1.6
3.8 8.4 8.6 7.9 10.7 16.6 8.1 11.4 13.5 11.5 13.1 9.1 7.9 12.0 8.8 13.5
320.1 349.0 367.0 150.0 170.0 189.7 56.8 68.7 76.4 21.0 24.1 27.7 16.0 19.8 23.3 13.6 15.2 21.6 14.0 15.4 17.8 10.6 12.7 15.4 8.4 10.2 13.8 20.3 23.3 29.1 19.8 22.2 27.7 36.6 44.1 51.9 41.1 47.0 54.5 19.8 24.8 29.5 37.0 43.3 49.9 8.8 11.9 14.8
0.823 * * 0.827 * * 0.650 * * 0.734 * * 0.813 * *
B4 M1 M2 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14
1.000 0.756 * * 0.595 * * 0.555 * * 0.572 * * 0.216 0.073 0.335 * 0.240 0.270 0.292 0.203 0.465 * * 0.608 * * 0.388 * 0.511 * * 0.044
B4
M2
P1
P2
1.000 0.551 * * 1.000 0.701 * * 0.563 * * 1.000 * * 0.634 0.662 * * 0.565 * * 1.000 0.204 0.055 0.018 0.128 0.084 2 0.083 0.385 * 0.096 0.304 0.161 0.300 0.307 0.091 0.123 0.179 0.011 0.157 0.406 * * 0.109 0.070 * * * 0.371 0.092 0.505 0.299 * * 0.214 0.003 0.435 0.118 * * * * * * 0.600 0.414 0.496 0.482 * * * * * * * * 0.753 0.443 0.636 0.499 * * 0.492 * * 0.196 0.310 * 0.431 * * 0.636 * * 0.457 * * 0.607 * * 0.489 * * 0.184 0.064 0.036 0.151
M1
P4
P5
P6
1.000 0.185 1.000 0.226 0.390 * 1.000 * 0.315 0.306 0.646 * * 1.000 0.228 2 0.079 0.267 0.313 * * * * * 0.215 0.846 0.630 0.283 0.241 0.932 * * 0.432 * * 0.382 * * 0.320 0.120 0.124 0.032 0.239 0.145 0.270 0.190 0.321 * 2 0.096 0.221 0.176 0.225 0.127 0.255 0.132 0.009 2 0.253 2 0.068 2 0.105
P3
Note: Correlation is significance at: *0.05 level (two-tailed) and * *0.01 level
0.131 0.147 0.318 * 0.176 0.293 0.421 * * 0.275 0.584 * * 0.697 * * 0.312 * 0.657 * * 0.014
B3
R
P8
P9
P10
1.000 0.078 1.000 0.174 0.864 * * 1.000 0.107 0.274 0.214 1.000 * 0.160 0.331 0.270 0.770 * * 0.052 0.060 2 0.027 0.378 * 0.272 0.332 * 0.251 0.898 * * 0.098 2 0.251 2 0.205 0.274
P7
P12
P13
1.000 0.529 * * 1.000 0.843 * * 0.337 * 1.000 0.257 0.514 * * 0.263
P11
Craniofacial measurements of neonates 101
Table V. The correlation coefficient between each pair of craniofacial dimensions
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Factor analysis with varimax rotation was conducted in order to further detect the structure of the relationship between different variables and to find a small number of factors that explain most of the data variability. Table VI shows that the first six factors account for 84.65 per cent of the total variability in the data set. The six factors of the craniofacial anthropometric data of neonates are classified as: . Factor 1 has 21.57 per cent loading on the longitudinal dimensions of nose. . Factor 2 has 18.70 per cent loading on the transverse dimensions of head and eyes. . Factor 3 has 17.00 per cent loading on the transverse dimensions between eyes and ears. . Factor 4 has 9.94 per cent loading on the longitudinal dimensions of ears. . Factor 5 has 9.81 per cent loading on the transverse and vertical dimensions of nose. . Factor 6 has 7.62 per cent loading on the longitudinal dimensions of eye. Factor analysis results in Table VI show that craniofacial features are classified into different groups according to transverse and longitudinal directions of head, eye, ear and nose, respectively. Amongst the six factors, longitudinal dimensions of nose (Factor 1) and transverse dimensions of head and eyes (Factor 2) obtain high loading values. Correlation coefficient shows that transverse dimensions of head and eyes have significant and mild relationship with those between eye and ear, whereas the longitudinal dimensions of nose have low correlations with other dimensions. It indicates that transverse craniofacial dimensions of neonates in all groups have highly relationships. However, longitudinal craniofacial dimensions of neonates just have relationships within each group. Thus, transverse dimensions can be represented by one or some of outstanding dimensions, whereas there is not a dimension for representing others in longitudinal direction.
Table VI. Factor analysis
Variable
Factor 1
Factor 2
Factor 3
Factor 4
Factor 5
Factor 6
M1 M2 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 Variance (%)
0.151 20.145 0.407 0.074 0.119 0.943 0.585 0.423 20.051 0.908 0.922 0.094 0.192 20.033 0.154 20.254 21.566
0.703 0.780 0.661 0.851 2 0.018 2 0.038 0.329 0.083 0.041 0.228 2 0.017 0.308 0.450 0.359 0.353 2 0.083 18.700
0.448 0.264 0.390 0.191 0.222 0.080 20.199 20.206 0.223 0.143 0.209 0.847 0.691 0.156 0.830 0.319 17.002
0.217 20.142 0.065 0.134 0.036 20.124 0.263 0.207 20.069 20.068 20.102 0.139 0.302 0.769 0.151 0.792 9.941
0.015 0.363 0.038 2 0.059 0.138 2 0.083 0.436 0.604 0.892 0.022 0.123 2 0.022 0.069 2 0.040 0.172 0.063 9.813
0.091 20.065 20.177 0.076 0.912 0.037 0.191 0.321 0.026 0.073 0.045 0.195 0.118 0.318 0.053 20.182 7.624
Note: The italic values are significant at: 0.05 level
4. Applications of measurements in eye-patch protector 4.1 Development of a sizing system for a new eye-patch protector Based on the above discussions, key dimensions of a sizing system for a new eye-patch protector in transverse direction can be determined first. Among the transverse dimensions, M1 (head circumference) has some outstanding features as follows: . M1 has strong correlation with all the other transverse dimensions. . M1 is an integrated craniofacial dimension of a neonate. . M1 is routinely measured in the hospital for neonatal growth evaluation.
Craniofacial measurements of neonates 103
Obviously, M1 is an outstanding representative for all transverse dimensions. Furthermore, the values of M1 are convenient to be obtained without any additional measurement on neonates. Medical staff is familiar with the head circumference (M1) during medical practice and thus it is easy for them to select an eye-patch protector with suitable size for the neonates. Accordingly, M1 was determined as one of the key dimensions for developing a new sizing system. Considering the longitudinal dimensions, the values of their correlations are low and disperse into different factors, and no dimension in this regard can represent the others. Therefore, no key longitudinal dimension was generated. Consequently, only M1 was confirmed as the key dimension for developing a new sizing system for the eye-patch protector. Evidently, head circumference is the only key dimension in most of the current eye-patch protectors. Distribution of the head circumference of neonates is shown in Figure 6. It is reported that current eye-patch protectors offer two different sizes for full-term neonates. One is used for neonates whose head circumferences fall within the range of 230-340 mm and another is provided for them whose head circumferences are within the range of 300-350 mm. In this study, the mean (range) of the head circumferences of the full-term is 346.73 mm (318-380 mm) and the apex is located at 350-360 mm. Figure 6 shows that 41.5 per cent of the full-term neonates whose head circumferences are over Histogram 15
Frequency
12
9
6
3 Mean = 346.73 Std Dev. = 13.317 N = +1
0 310
320
330 340 350 360 370 Head circumference (mm)
380
Figure 6. Histogram of the head circumference (M1) of 41 neonates
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350 mm and exceed the size range of the eye-patch protectors provided to the full-term neonates. As a result, a new sizing system is in compelling need for eye-patch protector to cover all the full-term neonates that can provide maximum protection from potential retinal or corneal damage. In this respect, the target population of the full-term neonates was further divided into two size groups according to the measurement of their head circumferences. Because the distribution of the head circumference is nearly normal, 99.7 per cent measured data are included within the range of x ^ 3s. The range of head circumferences is calculated to be 306.7-386.7 mm and divided into two ranges of 310-349 mm and 350-389 mm. The mean, 5 percentile and 95 percentile of these two groups were calculated, respectively, to generate a size chart. The protective function of an eye-patch protector demands that its area be large enough to cover the eyes of almost all neonates from strong light. Thus, the value of 95 per cent of P1 and P3, and value of 5 per cent of P2 were selected to design the eye-patch part. For the other dimensions, the mean was selected. The size chart is presented in Table VII. 4.2 Recommendations for eye-patch protector design Light protection is the primary function of an eye-patch protector. To block off the all-pervasive light, accurate sizes are needed for the shape of the eye-patch protector. Meanwhile, other requirements such as safety, security, comfort and appearance also should be considered. In this sense, measured craniofacial dimensions will provide a scientific foundation for the eye-patch development. The recommendations for EP design were generated as follows: . The length of EP is governed by the head circumference (M1). . The shape of the EP panel should be rectangular or ellipse. . Binocular width (P1) , length of EP panel , facial arc (M2). . Height of orbits (P3) , width of EP panel , 2 * nose height (P9). Sizes
Table VII. Size chart of eye-patch protector for full-term neonates
Median of size (mm) Range of size (mm) Dimensions P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 M2
Small size
X(mm) 65.6 23.4 19.3 16.0 15.6 12.6 10.2 23.5 22.4 42.4 44.2 23.1 41.3 11.3 166.2
330 310-349 5% (mm)
Medium size
95% (mm) 72.2
20.8 23.2
X(mm) 71.9 25.8 19.7 16.0 15.7 12.6 10.5 24.4 23.2 46.5 49.5 26.2 45.6 12.6 176.0
370 350-389 5% (mm)
95% (mm) 89.7
22.8 23.9
.
.
.
.
.
The concave shape of EP panel for nose accommodation is governed by nose dimensions (P4-P9) and width of intercanthal width (P2). The joint of eye-patch panel and fastening panel is governed by the distance between eye and ear (P10, P11 and P13). The angle of location of fastening bands are governed by ear dimensions (P12, P14) and the distance between eye and ear (P10, P11 and P13). The width of fastening panel at ear location is governed by the width of ear insertion to head (P12). The width of fastening panel at ear location is governed by the width of ear insertion to head (P12).
5. Limitations of this research and further improvements 5.1 Limitations of this research Main limitations are located in the following two aspects: (1) Since the subjects in this study were the neonates in the SCBU of QMH, the sample size is rather limited. Their health condition must be examined carefully and reviewed periodically so as to reduce any adverse effects, potential dangers and disturbances in their weakest period of life. Owing to the psychological acceptance, it is also difficult to seek parents’ consent for their babies’ participation in this research. Thus, the sample size in this research was not governed by exact statistic principles but by an acceptable study period. (2) As conditioned by the critical requirements for safety and comfort of the neonates, and also restricted by the hospital environment, only linear dimensions were measured by the CRP measuring system in the research. This system limits its application to EP design, development and evaluation and further numerical simulation. 5.2 Suggestions for future work Although laser scanner is widely used for measurement in clothing industry, the photogrammetric measuring system developed in this research has significant advantages in terms of safety, comfort and portability. This system is useful to take measurements with critical requirements for safety and comfort and/or in a complex field condition. For example, it is applicable in the study for predicting the girdle pressure of intimate apparel. In future research the function and quality of the measuring system can be improved using digital cameras or web cameras with higher resolution. Infrared projectors can be assembled to generate 3D profiles of the subjects when safety is still guaranteed. The function of the 3D model creation helps not only design products, but also develop digital 3D human bodies and products. It is benefits for further studies such as simulating wear effects of products numerically. 6. Conclusions In this study, 16 craniofacial anthropometric dimensions were designed and measured on 41 neonates nursed in the SCBU of QMH for the development of a new eye-patch protector. A newly developed non-intrusive close-range photogrammetric system was applied for safe, convenient and accurate measurements on the neonates. Based on collected data,
Craniofacial measurements of neonates 105
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the univariate analyses and factor analysis, correlations between each pair of dimensions and factor analysis were investigated. Upon above analysis, head circumference was identified as the key dimension for the sizing system. By dividing the population into two groups with the different head circumferences of 310-349 mm and 350-389 mm, a size chart was developed for efficient design and construction of the eye-patch protector. Recommendations for eye-patch protector design involved the integration of dimensions of whole eye-patch protector, shape of eye-patch panel and fastening panel and the joint location of eye-patch panel and fastening panel. References Deng, Y.M., Yick, K.L., Kwok, Y.L., Wong, S.C. and Ng, S.P. (2007), “Development of a three-dimensional measuring system for neonate’s head and facial morphology”, Journal of Donghua University (English Edition), Vol. 24 No. 3, pp. 309-12. Dicken, P., Grant, L.J. and Jones, S. (2000), “An evaluation of the characteristics and performance of neonatal phototherapy equipment”, Physiological Measurement, Vol. 21, pp. 493-503. Farkas, L.G. (1994), Anthropometry of the Head and Face, Raven Press, New York, NY. Kwok, Y.L. (1992), “The design of garments for premature infants to wear in a hospital environment”, PhD thesis, The University of Leeds, Leeds. Melton, K. and Akinbi, H.T. (1999), “Neonatal jaundice”, Postgraduate Medicine, Vol. 106 No. 6, pp. 167-78. Merlob, P., Sivan, Y. and Reisner, S.H. (1984), Anthropometric Measurements of the Newborn Infant (27 to 41 Gestational Weeks), March of Dimes Birth Defects Foundation, New York, NY. Sisson, T.R.C., Glauser, S.C., Glauser, E.M., Tasman, W. and Kuwabara, T. (1970), “Retinal changes produced by phototherapy”, The Journal of Pediatrics, Vol. 77, pp. 221-7. Corresponding author Kit-lun Yick can be contacted at:
[email protected]
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Study of the influence of matter and finishing treatments on the denim garment shade
The influence of treatments on shade denim
Faouzi Khedher, Soufien Dhouib, Slah Msahli and Faouzi Sakli
107
Textile Research Unit, ISET Ksar-Hellal, Ksar-Hellal, Tunisia
Received 27 April 2010 Reviewed 24 September 2010 Accepted 24 September 2010
Abstract Purpose – The purpose of this paper is to study the effect of matter, laundering types, special treatments and their succession applied during the manufacturing process of garment washing on the cloth shade. Design/methodology/approach – Denim garment manufacturers are interested in finishing cloth to characterizes the aging look of the cloth. The effect of matter, laundering, special treatments and their succession were studied. The treatments have been done on manufactured trousers. One rigorous statistical study is achieved to validate the experimental results. Findings – The mixed washing is the most degrading for the shade of cloth and appearance of the garment’s surface and the succession of special treatments of finishing is demanded to have an increasing whiteness. The finishing resin-treatment realized before any washing process (stone washing or mixed washing) provokes a slight increase of garment colour resistance. Practical implications – Information from this study will aid manufacturers of garment washing jeans in selecting the finishing method that suits their marketing/manufacturing plants. Originality/value – Garment washing is a technology incorporated by garment manufacturers to be able to provide a product in response to consumer’s wants. This study of the effect of matter, washing type, special treatments and their succession on garment denim blue jeans shade provides garment manufacturers with information about the methodical line of finishing to obtain the wanted cloth shade. Keywords Cotton, Clothing, Textile manufacturing processes, Colours technology Paper type Research paper
Introduction Denim jeans evolved into a part of the fashion range, its success is due to its ability to change with every social and cultural evolution (Spevack, 1997, p. 7). Denim garment manufacturers are interested in finishing cloth that consumers want to purchase. Consumer demand for jeans with aged look began a revolution in denim processing (Hargraves et al., 1991). To characterizes the ageing look of the cloth, it is very important to start by quantifying the visual aspect (shade, etc.). Launderings and special treatments are the most important parameters influencing the cloth shade and the final aspect of denim jeans. In spite of the increasing of the product development process in finishing garment denim blue jeans, studies in this subject are not as numerous as the one on fabrics and the more parts among them treat the influence of the home laundering on some mechanical properties (Higgins et al., 2003; Militky and Bajzik, 1997; Card, et al., 2006). Indeed, studies led on finishing garment denim blue jeans that treat the effect of special treatments in the industrial conditions are very limited or nearly hopeless.
International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 107-118 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107306
IJCST 23,2/3
Thus, we were interested first to study the effect of matter, types of launderings (stone wash, enzyme wash, mixed wash and rinse), special treatments (brushing, sanding, resin-treatment, bleach-treatment, permanganate-spray and softening) and their succession applied during the manufacturing process of garment washing on cloth shade. In a second part a rigorous statistical study is achieved to validate the experimental results.
108 Experimental method Four types of Denim fabrics were selected for this study. The selected fabrics differ by their weight (medium weight fabric and heavy weight fabric), the fabric finishing process (mercerized fabric and no mercerized fabric) and the matter composition (cotton and cotton elastane). The fabrics were finished with the same line of finishing (mercerization, skewness, sanforization). A summary of the fabric properties used in this study is given in Tables I and II. The treatments have been done on manufactured trousers from these four fabrics according to a well definite experience plan (Phan-Tan-Luu, 1993) (Table III). So each sample was finished by different processes of washing and some special treatments before ending with a cationic softening (Tables III and IV). The measures of the colour coordinates (L, a *, b *) (Roderick, 1997; Mclaren and Rigg, 1976) and the reflectance spectrum have been achieved on a dual-beam spectrophotometer “SPECTRAFLASH 300 (SF 300) of Datacolor International”. L, a *, b * values of a treated sample are obtained by the relationships between Xn, Yn and Zn where:
Table I. Fabric specifications
Table II. Dyeing of warp yarn
Fabric code
Composition
T1 T2 T3 T4
95% cotton, 5% elastane (on weft) 100% cotton 100% cotton 100% cotton
Mass/area (g/m2)
Fabric finishing
350 350 350 421
Concentration of dyeing bath (g/l) Indigo Sulfur
Fabric code
Dyeing of warp yarna
T1 T2
Seven Indigo baths One sulfur bath and seven Indigo baths
0.46 0.61
T3
One sulfur bath and seven Indigo baths
0.61
T4
One sulfur bath and seven Indigo baths
0.45
– C1: 1.15 C2: 3.50 C3: 5.00 C1: 1.15 C2: 3.50 C3: 5.00 C1: 25 C5: 25
Mercerized No mercerized Mercerized No mercerized
Colors Sulfur – C1: C2: C3: C1: C2: C3: C1: C5:
Black greenness Blue redness Green yellowness Black greenness Blue redness Green yellowness Black greenness Clear Blue redness
Note: aWe recall in this level that the weft yarn of denim fabric are not dyed and that the warp yarn are dyed ring-shaped and not in mass
Y 1=3 216 Yn " 1=3 # X 1=3 Y * a ¼ 500 2 Xn Yn L* ¼ 116
ð1Þ
The influence of treatments on shade denim
ð2Þ
109 Levels/ factors
Type of Special fabric treatments
1 2 3
T1 T2 T3
4
T4
Brushing (Br) Sanding (Sa) Resintreatment (Re)
Washing types
Bleachtreatment
Permanganate spray
Stone (S) Bleach (B) Spray (S) Mixed (M) No bleach (NB) No spray (NS) Enzyme (E)
Cationic softening Soften (A) No soften (NA)
Rinse (R)
Treatments
Conditions
Sanding (Sa)
Nature: manual with gun Type of sand: contains at least 5 per cent of SiO2 Pressure ¼ 5 bars Angle of attack ¼ 458 Number of passage ¼ 3 Nature: automatic (robot) Rotational speed: 120 tr/mn Linear Speed of the brushes: 20 m/mn Nature of product: DMDHDEU Concentration: 25% Pulverization: 5 ml of resin/1 kg of merchandise Nature of product: potassium permanganate Concentration: 50-65 ml for a surface of (0.2 m2) Distance of pulverization: 40-50 cm Pressure ¼ 2.5 bars Number of passage ¼ 3 Product: 6.5 ml/l of gavel water of (128 chlorinate) Report of the bath ¼ 1/5 Temperature ¼ 508C Time of washing ¼ 45mn Stone: new stones and worn-out stones (80 kg for a load of 140 trousers) Report of the bath ¼ 1/5 Temperature ¼ 508C Time of washing ¼ 45 mn Enzyme: acidic enzyme (pH ¼ 5), 800 g of enzyme for a load of 80 kg of the merchandise Report of the bath ¼ 1/5 Temperature ¼ 508C Time of washing ¼ 45 mn Enzyme: acidic enzyme (pH ¼ 5), 800 g of enzyme for a load of 80 kg of the merchandise Stone: new stones and worn-out stones (20 kg for a load of 140 trousers)
Brushing (Br) Resin-treatment (Re) Permanganate-spray (S)
Bleach (B) Stone washing (S)a
Enzyme washing (E)a
Mixed washing (stone þ enzyme) (M)a
Note: aAll types of washing start with a preparation and end by a soaping, softening, wring and drying
Table III. Experience plan
Table IV. Conditions of finishing treatments
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b* ¼ 200
"
Y Yn
1=3 1=3 # Z 2 Zn
ð3Þ
Xn, Yn and Zn are the tristimulus values, for a particular standard illuminant and observer, for a sample reflecting 100 per cent of the light at all wavelengths. The lightness of the sample is represented by L * on a scale running from zero for black to 100 for white. The other attributed can be represented on a plot of b * against a *. Neutral colours plot close to the origin for any illuminant (a * ¼ b * ¼ 0) (Figure 1). The dyestuff concentration of the dyed fabric samples where calculated by the relationships between K and S (Mclaren and Rigg, 1976; Shukla and Dhuri, 1992; Derbyshire and Marshall, 1980): Kl t ð 1 2 R l Þ 2 ð 1 2 R l t Þ 2 ¼ 2 Sl 2Rl 2Rlt
ð4Þ
where: Rl
Reflectance of dyed sample.
Rlt Reflectance of no dyed sample. Klt Absorption coefficients (light absorbance). Sl
Scattering coefficients (light reflectance).
K/S Dyestuff concentration of the dyed fabric samples. We completed our work by one statistical study while using the factorial experience plan presented in Table III. The choice of these treatments (factors) as well as their mode, drives us to make a factorial experience plan (complete) with only two processes of washing (stone wash and mixed wash)[1] 4 £ 3 £ 2 £ 2 £ 2 £ 2 (Vigier, 1991), containing 192 lines or experiences. This plan is repeated three times, we obtain a factorial plan of 576 experiences. Statistics generated by “ MINITAB ” were used to investigate the differences in K/S for the most important parameters of finishing garment washed denim. 100 L*
White Yellowness b* >0
Black
Greenness
Figure 1. Rectangular axes of general opponent color space (verbal axis labels) and CIELAB color space (L * a * b *)
a* <0
O = [000]
b* <0 Blueness
Redness a* >0
Results and discussion Physical survey Influence of types of laundering. In the first part of this study, it is appropriate to assume that when comparing different types of laundering, the different responses observed in the same sample that have the same finishing would be due to different types of laundering. Therefore, we could make comparisons of each laundering in this investigation. When denim blue jeans garments are laundered, colour changes will be influenced by several parameters of types of laundering. Figures 2 and 3 show the effect of different launderings (stone wash (S), enzyme wash (E), mixed wash (M), rinse wash (R)) on the L *, a *, b * parameters and K/S values. In the case of rinse wash, when no enzyme or no stone were used, L *, b * decrease and a * remains constant. The shade of untreated sample is whiter than the treated one. The cloth shade of the untreated sample is influenced by the presence of glue on weft yarns. During a rinse wash a part of the glue becomes soluble in the bath and it facilitates the dye bleeding. After, there is a dye redeposition on the not dyed weft yarns. Then, the cloth shade became darker than the untreated sample.
The influence of treatments on shade denim 111
39 37 35 33 31 29 27 25 23 21 19 17 15
2 T2
T3
T4
a* on the top and b* on the bottom
T1
0 –2 –4 T1
–6
T2
T3
–10
Figure 2. Evolution of L * and (a *, b *) according to different types of laundering
–12 –14 –16 –18
Wt
R
E
S
T4
–8
M
Washing types
25 T1
T2
T3
T4
20
15 K/S
L*
Wt R E S M Wt R E S M Wt R E S M Wt R E S M
Washing types
10
5
0 Wt
R
E Washing types
S
M
Figure 3. Evolution of K/S according to different types of laundering
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The washing rinse is the softest since the bath contains only an enzyme amylase and a surfactant that do not risk damaging the matter. However, the attenuation of cloth shade by stone washing is more important comparing to enzyme washing proving that stone abrasion is more aggressive than the enzyme one. In fact, when fabrics are laundered with stone or enzyme wash, the surface fibres are aggressively removed from the fabric surface by the stone or enzyme action thereby lower yarn surfaces can be worn away further. If the stones and enzyme are combined in the same laundering as in the mixed wash, the fibre’s degradation become more important causing an intensive aged look which explain the high increase of L * values as shown in Figure 2. Moreover, all types of fabrics show a similar shade evolution with different launderings. Only a little shade intensity variation is detected between them. Influence of special treatments. To investigate the effect of special treatments, current treatments frequently used in denim manufacturers (brushing (Br), sanding (Sa) and resin-treatment (Re)) are chosen. The application of these special treatments has been done on untreated garments before stone or mixed washing. The shade evolution after washing treatments is shown in Figures 4 and 5.
Wt S Br+S Sa+S Re+S Wt S Br+S Sa+S Re+S Wt S Br+S Sa+S Re+S Wt S Br+S Sa+S Re+S
Special treatments 45 T1
T2
T3
T4
a* on the top and b* on the bottom
40 35
L*
30 25 20 15
Figure 4. Evolution of L * and (a *, b *) according to special treatments, before a stone washing (stone (S))
10 5 0 Wt
S
Br+S
Sa+S
2 0 –2 –4 –6 –8 –10 –12 –14 –16 –18 –20
T1
T2
T3
T4
Re+S
Special treatments
15
15
T1
T2
T3
T4
T1 T3
10 K/S
K/S
10
5
Figure 5. Evolution of K/S according to different special treatments before has washing
T2 T4
5
0
0 wt
S
Re Br Special treatments
Sa
Note: Stone (S) on the left and mixed (M) on the right
wt
M Re Br Special treatments
Sa
These figures illustrate that, after different treatments, the measured shades of the different samples evolve with the same way for all cloths. Moreover, an increasing of L * values and a decreasing of K/S are observed when fabrics are treated with brushing or sanding before laundering. Moreover, the effect of these two special treatments on obtaining more whiteness and aged look was very important but, in this case, the effect of the sanding is more intense than the brushing due to the big pressure of the sand projection. Brushing effect will be more intensive by increasing the pressure and the number of passages or by choosing harder hair brushes. On the other hand, if the fabric is treated with resin before laundering, the colour fastness to washing and bleeding during stonewash and mixed wash treatments are slightly increased because of the formation of a slightly colour resist film on the surface of the garment. In our survey, we use a reticulating resin DMDHEU (dimethylol dihydroxyethylene urea) as a crosslinking agent for the cellulose chains that develop hydrophobic effect on the treated fabrics. This resin is often applied on cotton fabrics to fix a defined form (crimp adjustment or ironed aspect) either to avoid the attenuation of cloth shade in washing jean garments. Influence of the succession of special treatments. While choosing a line of succession of finishing treatments, we can notice from the two Figures 6 and 7 that, for the
The influence of treatments on shade denim 113
1=M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad 1=M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad 1=M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad 1=M 2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad
Special treatments
70 T1
T2
T3
T4
0 a* on the top and b* on the bottom
60 50 L*
40 30 20 10 0 Wt
1=M
–2 –4 –6
T1
T2
T3
T4
–8 –10
Figure 6. Evolution of L * and (a *, b *) according to the succession of the treatments before a mixed washing (mixed (M))
–12 –14 –16 –18
2 = Br+1 3 = 2+B 4 = 3+Sp 5 = 4+Ad Special treatments
16 T1
14
T2
T3
T4
12 K/S
10 8 6 4 2 0 Wt
1=M
2 = Br+1 3 = 2+B Special treatments
4 = 3+Sp
5 = 4+Ad
Figure 7. Evolution of K/S according to the succession of the treatments before a mixed washing (mixed (M))
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different types of fabrics, K/S decreases continuously up to ten times and L * increases about 100 per cent after ending the finishing treatments. The decrease of K/S values is due to the high level of mechanical abrasion generated progressively on the fabrics by the succession of the washing (stone or mixed) and mechanical special treatments (brushing or sanding) and the chemical action of the enzyme and chemical special treatments (bleach or spray). Moreover, except of the softening, b * values increases progressively after each treatment which means that the blueness intensity decreases. Compared to the other fabrics, the heaviest fabric T4 shows the most attenuation of K/S values after the mixed washing and finishes with a weak value of K/S after the succession of treatments as the middle weight fabrics T2 and T3. In fact, supposing that all things are equal otherwise, the dyed thickness of a thick yarn will be weaker than thinner yarn having a weaker diameter since the same quantity of dye will be distributed in the two yarns (Figure 8). Statistical study Statistics generated by “ MINITAB” were used to investigate the effect of fabric types, washing types, special treatments, bleach, spray and softening on the cloth shade (K/S) (Figure 9). The choice of these treatments (factors) as well as their mode, drives us to make a factorial experience plan (complete) (Table III) with only two processes of washing (stone wash and mixed wash)[1] 4 £ 3 £ 2 £ 2 £ 2 £ 2 (Vigier, 1991), containing 192 lines or experiences. Through repeating this plan three times, we obtain a factorial plan of 576 experiences.
Figure 8. The distribution of a same quantity of dye in two different yarns diameters
Thick yarn
Thin yarn
Main effect plot (data means) for K/S Special treatments
Mean of K/S
Fabric type
Figure 9. Graphic of principal effects for K/S
Washing type
7 6 5 4 3 1(T1)
2(T2)
3(T3)
4(T4)
1(Br)
Bleach
2(Sa)
3(Re)
1(S)
Spray
2(M) Softneing
7 6 5 4 3 1(B)
2(NB)
1(S)
2(NS)
1(A)
2(NA)
The main effect, the interaction plot and the Analysis of variance (ANOVA) were used to determine the presence of significant differences of treatments. The statistical results showed: . Justification of the model. By the test of the adjusted regression coefficient, the K/S model is justified because it presents a coefficient of 0.9537 that is very near to 1. . Analysis of the main effects plots. The main effects plot represents the averages of the answers for every level of every parameter, with the tracing of a reference line the global average of the answer information. This diagram is essentially used to compare the importance of the main effects of the different parameters; it is a first classification of the different treatments used in garment washing Denim according to their respective main effects on the final garment shade.
The influence of treatments on shade denim 115
As first conclusion, we can say from Figure 9 that the effect of the softening treatment is negligible on the shade which is proven practically (K/S < constant). The special treatments, the bleach and the spray have a very important effect. However, the fabric and washing types have a fairly important effect. Analysis of the interaction plot. The interaction diagram is a representation of the answers information averages for every treatment level. The level of the second treatment remains constant. This diagram is useful to judge the presence of interaction. An interaction is present if the answer for a treatment level depends on/or the other treatment levels. In a diagram of the interaction, some parallel lines indicate the absence of interaction (Hicks, 1982). More the lines depart of the parallel; more the degree of interaction is raised. This diagram informs us on the type of model to consider in the analysis of variance. As shown, in Figure 10 the detected interactions are: [TXTs], [TXD], [TsXD], [TsXB], [TsXS] and [BXS]. This result is going to help us in finding the considered model, so it is advisable to complete the study by the analysis of variance. Interaction plot (data means) for K/S 1
2
3
1
2
1
2
1
2
1
2 9
Fabric types
6 3 9 6 3 9
Special treatments
6 3 9 6
Washing types
Bleach
3 9 6 3
Spray Softneing
Figure 10. Graphic of interactions for K/S
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Analysis of the variance. The analysis of variance is the most important test in this survey since it is going to permit us to judge if the effect treatments on the measured answer (K/S) are statistically significant (Miliken and Johnson, 1984; Nelson, 1983). This test consists to calculate a statistical F from the coefficients of the established model and then to compare it to statistical tables of snedecor law (Olshen, 1973), and from F we can calculate another p-statistic (Table V): . If p , 1 per cent: then we say that the difference is highly significant. . If 5 per cent , p , 1 per cent: then we say that the difference is significant. . If p . 5 per cent: then we say that the difference is not significant. Analysis of variance shows that the matter, launderings and special treatments have a significant effect (Table V) on cloth shade. We summarize the results of the statistical analysis in the established interrelationship equation between the different treatments and their interactions. This equation represents the effect statistically significant effect (p , 5 per cent): K ¼ ½T þ ½Ts þ ½D þ ½B þ ½S þ ½T £ Ts þ ½T £ D þ ½Ts £ D S þ ½Ts £ B þ ½Ts £ S þ ½B £ S This model showed that the K/S variation is explained in a great part by the variation of the different treatments and their interactions kept in the model.
Treatments
Table V. Results of analysis of the variance for K/S
T Ts D B S A T £ Ts T£D T£B T£S T£A Ts £ D Ts £ B Ts £ S Ts £ A D£B D£S D£A B£S B£A S£A
F
p
Conclusion
37.83 427.83 10.42 439.16 2,152.25 2.80 23.82 4.97 3.87 1.60 0.96 4.79 14.84 53.01 0.23 5.17 0.02 0.53 50.62 0.00 0.06
0.000 0.000 0.002 0.000 0.000 0.091 0.000 0.000 0.011 0.192 0.412 0.010 0.000 0.000 0.791 0.024 0.887 0.467 0.000 0.949 0.803
xxx xxx xxx xxx xxx – xxx xxx xx – – xxx xxx xxx – x – – xxx – –
Notes: –, Absent or present interaction but negligible; x, present interaction with the increasing importance according to the number of x
Confrontation of the statistical model and the physical survey The statistical study shows that the treatments achieved during garment washed denim have a highly significant effect on the cloth shade. Moreover, the presence and the importance of the interactions between the different treatments (washing type, special treatments, bleach, spray and softening) have a significant effect also. These statistical results are confirmed by the physical survey where we showed that the washing type (mixed or stone), the special treatments (brushing, sanding or resin-treatment), the bleach and the spray have an important effect on the cloth shade (decrease of K/S values). In the same way, we showed that the succession of the treatments decreases the shade, where we can arrive to get with distinctly lines of finish the same whiteness aspect. In conclusion, we can say that the statistical model is confirmed by the physical survey. Conclusion Garment washing is a technology incorporated by garment manufactures to be able to provide a product in response to consumer’s wants. This study of the effect of matter, washing type, special treatments (brushing, sanding or resin-treatment), and their succession on garment denim blue jeans shade provides garment manufactures with information about the methodical line of finishing to obtain the desired cloth shade. This study shows that the application of the resin-treatment before the laundering provokes the formation of a slightly colour resist stripe on the surface of garment and that the succession of finishing treatments (brushing, sanding, bleach, spray, etc.) is advisable to have an intense whiteness. Nevertheless, all these treatments causing a more worn appearance and aged look for the garment, thus, the mechanical properties are greatly reduced. For this reason, a second survey of the effect of these treatments on the mechanical properties has been achieved, to know up to what limit the fabric can support the succession of the treatments in order to choose the most suitable process to obtain the wanted cloth shade while avoiding at the same time the massive deterioration of matter. Note 1. The Enzyme wash and the rinse wash not be used in the experience plan because industrially we cannot used all this these treatments with these two washing process. References Card, A., Moore, M.A. and Ankeny, M. (2006), “Garment washed jeans: impact of launderings on physical properties”, International Journal of Clothing Science and Technology, Vol. 18 No. 1, pp. 43-52. Derbyshire, A.N. and Marshall, W.J. (1980), “Value analysis of dyes a new method based on color measurement”, Journal society of Dyers and Colorists, Vol. 96 No. 4, pp. 166-76. Hargraves, R., Eissele, E. and Pisarczyk, K. (1991), “Innovation in pellet technology for garment dyeing”, American Dyestuff Reporter, Vol. 80 No. 5, pp. 28-30, 32. Hicks, C.R. (1982), Fundamental Concepts in the Design of Experiments, 3rd Ed., CBC College, New York, NY. Higgins, L., Anand, D., Holmes, A., Hall, E. and Underly, K. (2003a), “Effect of various home laundering practices on the dimensional stability, wrinkling, and other properties of plain woven cotton fabrics, Part I: experimental overview, reproducibility of results, and effect of detergent”, Textile Res. J., Vol. 73 No. 4, pp. 357-66.
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Higgins, L., Anand, D., Holmes, A., Hall, E. and Underly, K. (2003b), “Effect of various home laundering practices on the dimensional stability, wrinkling, and other properties of plain woven cotton fabrics, Part II: Effect of rinse cycle softener and drying method and of tumble sheet softener and tumble drying time”, Textile Res. J., Vol. 73 No. 5, pp. 407-20. Mclaren, K. and Rigg, B. (1976), “The SDC recommended colour-difference formula change to CIELAB”, Journal society of Dyers and Colorists, Vol. 92, pp. 337-8. Miliken, G.A. and Johnson, D.E. (1984), Analysis of Messy Data, Designed Experiments, Van Reinhold, New York, NY, p. 1. Militky, J. and Bajzik, V. (1997), “Influence of washing/ironing cycles on selected properties of cotton type weaves”, International Journal of Clothing Science and Technology, Vol. 9 No. 3, pp. 193-9. Nelson, P.R. (1983), “A comparison of sample seizes for the analysis of means and analysis of variances”, Journal of Quality Technology, Vol. 15, pp. 33-9. Olshen, R.A. (1973), “The conditional level of the F-test”, Journal of the American Association, Vol. 68, pp. 692-8. Phan-Tan-Luu, R. (1993), Methodology of the Experimental Research, Edition Euskatel Estatistika, Spain, pp. 132-4 . Roderick, M. (1997), Colour Physics for Industry, 2nd ed., Colorimetry and the CIE System, pp. 111-33. Shukla, S.R. and Dhuri, S.S. (1992), “A practical application of the Kubelka-Munk theory in polyester dyeing”, American-Dyestuff-Reporter, Vol. 81 No. 4, pp. 32-41. Spevack, R. (1997), “Jeans business needs to get more creative”, Daily News Record, Vol. 27 No. 128, October 24, p. 7. Vigier, M. (1991), Pratique des Plans d’expe´riences, me´thodes Taguchi et Comple´ments, les e´ditions d’organisation, Paris. Corresponding author Faouzi Khedher can be contacted at:
[email protected]
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The transport phenomena of semi-permeable membrane for sport cloth Antonin Havelka and Zdeneˇk Ku_ s Department of Clothing, Faculty of Textile Engineering, Technical University of Liberec, Liberec, Czech Republic
Semi-permeable membrane for sport cloth 119 Received 10 August 2010 Revised 7 October 2010 Accepted 7 October 2010
Abstract Purpose – This paper aims to investigate the comfort properties of modern functional clothing, such as moisture and heat transport. Transport properties are evaluated for real barrier membrane clothes for sport application, under real weather conditions in Middle Europe. Design/methodology/approach – The different combination of functional clothing, with barrier membrane, were investigated under different temperatures and relative moistures inside and outside clothing layers. Water vapour permeability was measured under the steady-state conditions, by sweating guarded-hotplate test. Findings – This paper describes the theoretical analysis of moisture transport, and its influence on thermal conductivity; the paper investigates various barrier fabrics for sport apparel, and their ranges of water vapour transport ability under real weather conditions. Research limitations/implications – All received results are based on the transport of water vapour through a semi-permeable membrane and are supposed to be conducted mainly within a process of diffusion. Originality/value – This paper is focused on the theoretical analysis of transport by diffusion of water vapour through porous semi-permeable barrier textile material, and evaluates the real possibilities for sport applications. The level of transport is limited and mainly depends on the difference of the partial pressures of water vapours outside and inside the porous clothing material. Keywords Clothing, Membranes, Thermal efficiency, Moisture Paper type Research paper
1. Introduction Comfort of a clothing material is one of the most important aspects for all producers and users, especially for the sport apparel branch. Physiological comfort is influenced by: moisture of air under clothing, skin moisture, temperature of air under clothing, skin temperature and the content of carbon oxide under clothing. This article describes the theoretical analysis of this problem and the results of measurements of different smart-barrier fabrics for sport apparel. This contribution deals with a comparison of the basic measurable physiological properties of sandwich materials with real water vapour transport, as it happens within apparel produced from these materials. In the article, there are presented the results of the theoretical analysis of the transport properties of the smart clothing material, a comparison with the real physiological properties of barrier textile materials, and the real possibilities for sport applications. The article is focused on the theoretical analysis of transport by a diffusion of water vapour through a porous semi-permeable barrier textile material. The wear comfort is important not only for the good feeling when wearing sport apparel, but it is also important for the real performance, while transporting moisture and heat. The comfort of a fabric is important for producers and it is a major sales aspect.
International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 119-130 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107315
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1.1 Physiological comfort cloth consists of . Thermophysiological wear comfort – influences a person’s thermoregulation; it comprises of heat and moisture transport processes through the wear. . Skin sensorial wear comfort – depends on the sensorial characteristics when being in direct contact with skin. . Ergonomic wear comfort – deals with the freedom of movement, it is mainly dependent on the garment construction and elasticity of fabrics. . Psychological wear comfort – affected by fashion, tradition [. . .]. The most important of these parts of the physiological comfort is the thermophysiological wear comfort. The area of a good comfort for a human being is quite small. The temperature under fabric must be of 32 ^ 18C, relative humidity 50 ^ 10 per cent, air flow 25 ^ 15 cm· s2 1 – as shown in Figure 1. For sport-ware, three properties are very important: thermal insulation and breathability and moisture transport, but these properties are well in correlation. 2. Theoretical analysis of heat and moisture transfer Transport of heat and moisture through clothing materials is a very complicated question dependant on body temperature, human activity, number of clothing layers and environmental conditions. The transport is a dynamic process, which is possible to describe as a heat conduction and moisture transport in porous bodies. Modern apparel materials for sport and leisure time must fulfil the demands on a good organism protection against cooling and on low water permeability, but, on the other hand, they have to fulfil nearly opposite properties – good air permeability and good permeability of water vapour. Modern functional clothing, which fulfils physiological properties, consists of: (2.1) First layer – underwear – the main function of this layer is to transport sweat from skin to other layers. This layer is in a direct contact with body skin and is produced from hydrophobic fibres, for example POP.
Humidity (%RH)
90 80 70 60 50 40
Figure 1. Area of clothing comfort
Not comfortable
Comfortable Partly comfortable 30 31 32 33 34 Temperature (°C)
35
36
(2.2) Second layer – works as a thermal insulation layer. It is a special structure, i.e. fleece, which contains static air, which has a thermal insulation function. Some of the latest fleece materials have membrane, thereby partially resist to wind flow and moisture. In this case the second layer holds at the same time protective function and it is not necessary to use any third layer.
Semi-permeable membrane for sport cloth
(2.3) Third layer – works as a barrier between a human organism and environment. The most important property is its air impermeability and water resistance. Simultaneously, this layer must be, as much as possible, permeable for water vapour (Figure 2).
121
All these layers have an influence on the transport of heat, humidity and on the air penetration. The third layer, made from a barrier-membrane, is the most important layer for moisture transport and also protection against water in its liquid form, as it does not transport the liquid in both directions. The water vapour permeability has been investigated, Ret, which must be the lowest possible, and which determines the real possibilities of the third layer to transport water vapour. The previously used system of clothing was composed of cotton underwear, cotton shirts and impermeable protective layers. This did not work because it had poor physiological properties. The modern clothing system is composed of functional underwear, thermal insulation layer and a protective layer, as shown and described below. A barrier, semi-permeable membrane is very often used as the third layer. Barrier textiles – the semi-permeable textiles represent a recent material, which works as a barrier resistant to water in a liquid form and at the same time permits a water vapour transport. The basic principle is in a laminar membrane with small holes, about 1-2 mm, or with hydrophilic areas. The water vapour molecules are transported through the membrane out of the cloth. But no water (in a liquid form) is able to enter the membrane from the outside (Goretex, 2008). All types of barrier textiles work only in a case of different partial pressures (water vapour) on both sides of a textile. In such a condition, when the difference between the partial pressures on both sides assumes zero value, these textiles are not able to work properly as the barrier textiles and, thus, clothing made from them works as a very expensive raincoat. Barrier textiles must protect against water, but it also must have a good permeability and transport of vapour properties. Skin surface
First layer
Second layer
Third layer Transport of heat, humidity and air
Organism Environment I
II Air layers
III
Figure 2. Functional clothing
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3. Heat transfer Heat transfer between a person and the environment is conducted through three well know methods: conduction, convection and radiating (Sˇesta´k and Rieger, 2005). They all participate on heat transport and it is very difficult to determine, which one dominates, because heat transfer depends on many factors, for instance on heat generation, movement of a human, type of clothing and air flow. In the following text only the process of heat transfer via conduction will be discussed, as it could be supposed the most important one. Heat transport is possible to describe by Fourier hypothesis about heat propagation in a body. The flow of thermal energy is given by: qcond ¼ 2a · 7 r · cv · q ð1Þ where: qcond ¼ heat conduction flow [W · m2 2]. a
¼ heat conductance [m2 · s2 1].
7
¼ Laplace’s operator.
r
¼ partial mass density [kg · m2 3].
cv
¼ specific heat [J · kg2 1K2 1].
q
¼ temperature [K]. a · r · cv ¼ l a¼
l r · cv
where l coefficient of thermal conductivity [W · m2 1K2 1]. Then it is possible to write: qcond ¼ 2l · 7:q
ð2Þ ð3Þ
ð4Þ
from the above-mentioned relation it is evident that the intensity of a heat transfer is given by the particular value of the coefficient of thermal conductivity l, which is influenced by the type of a clothing material, number of clothing layers and particularly by the air closed inside the clothing material. This air is a significant heat insulating material, but it depends on humidity. The insulating ability of the clothed air decreases with an increasing moisture of the clothing material. This is the reason why it is very important to transport moisture from all layers of the clothing materials. This is important not only for the conductivity, but as well for the heat transfer by convection. Figures 3 and 4 show a great influence of coefficient of thermal conductivity and relative humidity on the whole system of clothing layers. The value of the thermal conductivity l influences the heat transport, therefore the delivery of moisture from clothing layers affects the whole heat transfer greatly and thereby physiological comfort clothing. 4. Water vapour permeability For prestigious types of barrier textiles it is possible to determine a value of resistance to the water vapour penetration (Ret ¼ 7.96 m2 · Pa · W2 1) (Havelka, 2007). It is possible
Apparent thermal conductivity (mW(m.k))
Semi-permeable membrane for sport cloth
100
123 50
0
Porous acrylic Polypropylene Wool Cotton
0
50
Figure 3. Relation of the heat conductivity and humidity
100 Regain (%)
900
840
780
720
660
600
540
480
420
360
240
180
120
0
300
Technopile 170 (g · m–2)
180 160 140 120 100 80 60 40 20 0 60
Thermal conductivity (λ × 103)
Source: Ukponmwan (2006)
Humidity of fabrics (%) Note: Humidity of fabric is expressed as a content of liquid water in a fabric in percentage Source: Kocurová (2009)
to use this value for a simplified model of the moisture transfer, and water vapour permeability is given by: 1 Wd ¼ ð5Þ Ret · FT m where: Wd ¼ water vapour permeability [g · m2 2 · hod2 1 · Pa2 1]. FTm ¼ latent heat of evaporation [W · g2 1] at the temperature of the measured components. Tm ¼ 358C (FTm ¼ 0.672 W· hod2 1 · g2 1).
Figure 4. Influence of humidity of fabrics on the thermal conductivity l
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In our case we get: Wd ¼
1 1 ¼ ¼ 0:1869 g · m22 · hod21 · Pa21 7:96 · 0:672 5:349
ð6Þ
Let us assume the temperature of the microclimate between a human body and a windcheater (sport apparel), with an estimated area of A ¼ 2.5 m2, is T1 ¼ 358C and relative humidity w1 ¼ 80 per cent, the partial pressure of water vapour is p1 ¼ 4,212.3 Pa; the outer temperature is T2 ¼ 208C and relative humidity w2 ¼ 40 per cent, the corresponding partial pressure of water vapour is p2 ¼ 893.1 Pa. Under such conditions, the total moisture transport per one hour is: W d total ¼ W d · Dp · A ¼ 0:2 · 3; 319:2 · 2:5 ¼ 1; 550:9 g · hod21 ð7Þ This is a simplified estimation provided that the moisture transport is steady in all parts of the sport windcheaters and that the moisture transport is based on the diffusion principle over the clothing layers. We can count that it is necessary to transport 1,000 g of moisture/hour during a hard work or intensive sport (Wiszczorova´, 2008). Production of moisture for various body loads is listed in Table I. In such a case that the outer temperature and the relative moisture are both increased, i.e. T2 ¼ 248C and w2 ¼ 55 per cent, the moisture transport decreases by approximately 30 per cent. When T2 ¼ 248C and w2 ¼ 80 per cent, the moisture transport decreases by approximately 50 per cent. Conversely, when the outer temperature and relative moisture decrease to value of T2 ¼ 58C and w2 ¼ 30 per cent, the moisture transport increases by approximately 20 per cent. From the previous calculations it results, that the barrier materials work, in relation to the moisture transport, only in such cases, when the difference between the partial water vapour pressures on both sides of a windcheater made from the barrier textile is sufficient. 5. Moisture transport The moisture transport proceeds generally also by other mechanisms (capillary, sorption), but at the barrier textiles we can suppose, that the diffusion way will be the more dominant. It is possible to describe moisture transport by a relation (Sˇesta´k and Rieger, 2005) for mass transport: qdif i ¼ 2Di · 7 · ri
ð8Þ
where: Di
¼ coefficient of diffusion transport of mass for the ith – component [m2 · s2 1].
7ri ¼ gradient of partial mass density for the ith – component [kg · m2 3]. Load of man
Table I. Production of moisture at various loads
1 2 3 4 5
Slow walking Hiking with a small load Skiing, snowboarding Trekking at a middle load Extreme load
Production of moisture (g · m2 2 · 24 h) 1,000 3,500 4,000 10,000 24,000
For a unit flow of moisture as a compound of gaseous environs with a partial pressure of pi0 ( pi0 , partial pressure inside of porous clothing material, pi00 , partial pressure outside the porous clothing material) it is possible to use a relation: M i pi 0 2 pi 00 qdif i ¼ Di ð9Þ RmT s where: Rm
¼ universal gas constant [kJ · kmol · K2 1].
Mi
¼ molar mass [mol].
T
¼ temperature [K].
S
¼ layer thickness [m].
Semi-permeable membrane for sport cloth 125
From this relation it is possible to determine a coefficient of diffusion transport of a mass, which determines the diffusion transport of the water vapour in a fabric. In our modelled case (T1 ¼ 358C, w1 ¼ 80 per cent, T2 ¼ 208C, w2 ¼ 40 per cent) the diffusion coefficient is: Di ¼ qdif i
RmT s 620 · 8:32 · 103 · 290:5 · 0:005 ¼ 0:0348 m2 · s21 ¼ 0 00 M i pi 2 pi 18 · ð4; 212:3 2 893:1Þ
ð10Þ
For example, was count a diffusion rate of vapour was evaluated for a case, when the temperature under a barrier fabric was T1 ¼ 358C (w1 ¼ 100 per cent, w1 ¼ 50 per cent – that is humidity of a human skin at extreme sport (100 per cent) and at a normal light sport (50 per cent)), and the outer temperature was T2 ¼ 0-508C (w2 ¼ 30-100 per cent). (Figures 5-7) This example was evaluated for various membrane textiles; for more see (Havelka, 2007). The results show that: . At a diffusion rate ¼ 0 the partial pressures are well-balanced and no diffusion flow moisture proceeds. T1 ϕ1
T2 ϕ2
Heat and moisture transfer
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Figure 5. Heat and moisture transfer
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At positive values of the diffusion flow the moisture is conducted over a barrier textile into the environment and the smart textile functions well. At negative values of the diffusion flow on the contrary the moisture is coming from the environment into the clothing, which is an evident defect given by a negative difference between the partial pressures. Even at low surrounding temperature (0, 108C) the diffusion flow is always limited. The moisture transport proceeds generally also by other mechanisms (capillary, sorption), but at the barrier textiles we can suppose, that the diffusion way will be the more dominant.
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Figure 8 summarizes the results depending on the average outdoor temperature (in our case Liberec, Czech Republic, 508470 north latitude and 148580 eastern longitude). The average temperature is stated according to months. The average relative humidity corresponds with this temperature. On the basis of these values and supposed required clothing comfort T1 ¼ 358C, w1 ¼ 50 per cent, there are calculated values of the moisture transport by diffusion for three clothing types – systems: . A – 1st layer membrane 2v windcheater Ret ¼ 6.56 [m2 · Pa · W2 1]. . B – 1st layer membrane 2v windcheater þ 2nd layer soft shell sweatshirt Ret ¼ 13.1 [m2 · Pa · W2 1]. . C – 1st layer membrane 2v windcheater þ 2nd layer polartec sweatshirt Ret ¼ 18.2 [m2 · Pa · W2 1]. The transport of moisture depends on different partial pressures of the water vapour in the environment and air, on partial pressures of the water vapour under the cloth and on Ret – resistance to water vapour penetration (equation (9)). Owing to different average exterior temperatures the partial pressure of water vapour changes and therefore changes also the amount of moisture transported. The strongest transport of moisture occurs obviously in winter. System A sufficiently fulfils the condition of 1,000 g· h2 1 in months four to nine. System B fulfils the condition only for light sports and it is not suitable for use for extreme exercise. System C does not comply the condition with the moisture transport during any sport activity even in the winter season. It is possible to apply this system only for light tourism. It can be assumed, that: . the moisture transport over barrier textiles is based mainly on a diffusion mechanism; . the transport intensity is mainly dependant on the difference between the partial pressures of water vapour under clothing and on the outer side of the garment, and on Ret;
Figure 7. Transfer of water vapour for T1 ¼ 358C, w1 ¼ 50 per cent and different T2, w2
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the difference between the partial pressures is limited and therefore the range of moisture transport over the barrier textiles also; as the temperature decreases below the dew-point, drops of sweat may be formed which leads to a rapidly worse moisture transport over the barrier textile. This results from the principle of a membrane fabric; when the partial pressure of the water vapour in the surroundings is higher than the one under a garment (barrier textile), moisture from surrounding will be transported to the garment!!! and
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however, despite big benefits this system cannot be overestimated and when doing an active sport or hard labour or under a load, it is better to use other clothing alternative – for example soft shell.
6. Conclusions The presented contribution deals with a comparison of the basic measurable physiological properties of sandwich materials as they are used in real clothing made from a smart-barrier textile. In the article, there are presented results of the theoretical analysis of transport properties of smart clothing material, a comparison with real physiological properties of barrier textile materials and real possibilities for users – sportsmen. Previously used system, composed of cotton underwear, cotton shirts and impermeable protective layer, does not work, because it does not have good physiological properties. Modern working systems are composed of functional underwear, thermal isolation layer and a protective barrier membrane layer, as shown and described in the article. This system is much better, but the amount of transport of water vapour is also limited. References Goretex (2008), “Gore-tex guaranteed to keep you dry”, available at: www.goretex.cz (accessed 16 July 2008). Havelka, A. (2007), “The physiological properties of sports apparel made from barrier textile”, Proceedings of 6th International Conference Texsci in Textile Faculty, Technical University of Liberec, Liberec, Czech Republic. ˇSesta´k, J. and Rieger, F. (2005), Prˇenos Hybnosti Tepla a Hmoty, CˇVUT of Prague, Prague. Wiszczorova´, Z. (2008), “The influence of thermal insulating features of clothing materials sandwich structures on the degree of compression”, Diploma thesis, Technical University of Liberec, Liberec. Further reading Havelka, A. and Halasova´, A. (2005), “The heat and moisture transport through clothing material”, Proceedings of 4th Central European Conference in Technical University of Liberec, Liberec, Czech Republic, pp. 141-2. Havelka, A. and Kus, Z. (2008), “Transport properties of semi-permeably-barrier textile for modern sports”, Proceeding of the 86th Textile Institute World Conference, Hong Kong, China, 18-21 November, pp. 1514-23. International Standards Office (1993), ISO 11092-Textiles-Physiologycal Effects-Measurement of Thermal and Water-Vapour Resistance Under Steady-State Condition, ISO, Geneva. Kocurova, M. (2009), “Thermal comfort of sport clothes with concern to perspiration influence”, Diploma thesis, Technical University of Liberec, Liberec. ˇSorin, S.N. (1968), Sdı´lenı´ tepla, SNTL/ALFA, Prague. Ukponmwan, J.O. (2006), “The thermal-insulation properties of fabrics”, The Textile Institute, Textile Progress, Vol. 24 No. 4, p. 29. About the authors Antonin Havelka, Doc. Ing. CSc, studied at the Technical University of Liberec, Faculty of Engineering; 1970-1975 he worked at Research center Preciosa where he focused on glass fibers;
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1975 he started to teach at Technical University of Liberec, in the Faculty of Textile Engineering. 1980 he finished PhD study in Czech CSc. In 1984 he become Associate Professor in the Department of Clothing, Technical University of Liberec. His main research interest is application automation in clothing industry, shaping and ironing clothing fabrics, physiological comfort of clothing fabric and application of smart textile. He has published over 140 papers. Zdeneˇk K_us, Prof. Dr Ing. is interested in the development of the measuring devices for clothing and textile, automation, computer simulation. He has been Head of the Department of Clothing at the Faculty of Textile Engineering since 1996, and Vice-Rector of the Technical University of Liberec since 2004. Zdeneˇk K_us is the corresponding author and can be contacted at:
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Profiled fiber cross-sectional shape characterization for identification Zhaoli Wang, Yueqi Zhong and Shanyan Wang College of Textiles, Donghua University, Shanghai, China Abstract
Fiber identification
131 Received 5 May 2010 Revised 13 August 2010 Accepted 13 August 2010
Purpose – The purpose of this paper is to show how shape analysis and quantitative characterization of fiber cross sections, with the aid of image analysis techniques, provide a quick, powerful approach to automated profiled fiber identification. Design/methodology/approach – In this paper, an effective method of cross-sectional shape characterization for profiled fiber identification is reported with extraction of the distance fluctuation curve of fiber cross-sectional boundary to the centroid. By calculating their cross-correlations using signal processing techniques, the authors tackle the problem of calibrating the starting points of fiber objects orientated arbitrarily in image successfully, which are difficult to deal with by means of image processing, to finish the normalization of distance fluctuation curves. For two fiber cross-sections, the similarity degree of their boundary fluctuation curves normalized can effectively reflect the similarity degree of themselves. Findings – Based on this, the method presented extracts the curves of all fiber cross-sections in one sample, compares the similarity degrees between each other, and creates clusters to identify profiled fiber. Originality/value – Experimental results validate that this curve can effectively characterize profiled fiber cross-sectional contour for profiled fiber identification and the normalization method is feasible. Keywords Textile fibres, Image processing, Identification Paper type Research paper
1. Introduction Quantitative characterization and feature extraction of fiber cross-sections is an extraordinarily important part of profiled fiber identification. There have been many basic geometric descriptors of fiber cross-sections, such as area, perimeter, roundness, ellipticity (Xu et al., 1993), circularity (Hebert et al., 1979), modification ratio (Hild et al., 2004), etc. which were defined for the sake of easy to measure. However, a wide range of profiled fiber cross-sectional shapes (currently there are trilobal, triangle, polygonal, multilobal, cross, flat shape, dumbbell-shaped, T-shaped, C-shaped, H-shaped, V-shaped, W-shaped, etc. Kajiwara et al., 2000; Yamazaki and Okamoto, 1997.) make it difficult to quantitatively characterize profiled fiber cross-sections by these simple geometric measures for discriminating them. This hinders profiled fiber automatic identification from the microscopic image. At present, profiled fiber identification is accomplished by human observation with the aid of microscopes, time-assuming and the results are subjective. With image processing techniques we can get more appropriate descriptors and accomplish automated measurements (Xu and Huang, 2004; Xu and Ting, 1996a, b; This work is supported by The Ministry of Education outstanding doctoral dissertation special funds of China (No. 2003035). The authors are grateful for the anonymous reviewers who made constructive comments.
International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 131-141 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107324
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Bao et al., 2004; Berlin et al., 1981; Li et al., 2005). Xu et al. (1993) presented to use Fourier descriptors which derived from the Fourier series for the cumulative angular function of the cross sectional boundary to characterize fiber cross-sectional shapes by using image processing techniques. Fourier descriptors are very robust in characterizing shape complexity and lobe components. However, it is founded by experiments that for two cross-sections of the same shape and different orientation, the difference of descriptors is big and it may bring about big recognition errors. Although in recent years there have been important developments in fiber cross sectional quantitative characterization and automatic measurements, the developments are mainly for cotton fiber maturity measurement (Matic-Leigh and Cauthen, 1994; Thibodeaux and Evans, 1986; Thibodeaux and Price, 1988; Hequet et al., 2006), two given fibers identification (Xu et al., 2007; Li, 1997; Chiu and Liaw 2005), the researches on profiled fiber cross-sectional shape analysis and profiled fibers identification are very few and immature (Li et al., 2005). In our experiments of seeking methods of fiber shape factor characterization, the fluctuation curve of profiled fiber cross-sectional boundary relative to the fiber center of mass had been obtained. When tackled the task of feature extraction for identifying profiled fiber, we found that a cross-sectional shape corresponding to such a determined curve, and it can be reconstructed only by the curve. This shows that the curve also contains enough information of fiber cross-sectional contours. Enlightened by this curve, we present an effective method of cross-sectional shape characterization for profiled fiber identification. In this paper, we describe the feature extraction of cross sectional contour detailedly. Since many publications have presented techniques of fiber cross-sectional image capture (Berlin et al., 1981; Thibodeaux and Evans, 1986; Thibodeaux and Price, 1988; Hequet et al., 2006) and image processing (Xu and Ting, 1996a; Xu et al., 2007; Xu et al., 1999), we commence with the topic of feature extraction. 2. Methodology Feature extraction is very key to pattern recognition. It strongly affects the classifier’s design and performance. If the characteristics of different types of samples differ significantly, it is easier to design a high performance classifier. In this paper, we aimed at seeking the most remarkable differences actually existed in the different types of profiled cross-sections and quantifying them. It should be noted that different from geometric shape identification, profiled fiber identification needs not only the shape information but also the size information, since two fibers with the same shape but different sizes belong to two different categories. 2.1 Extraction of distance fluctuation curves For a profiled fiber cross section, as Figure 1(a) shows, we calculate the distance between the boundary pixels to the centroid, taking the upper left pixel as the starting point, along the clockwise direction, obtain a discrete sequence. Taking the sequence as y-coordinate, the fiber object boundary pixels’ serial numbers as the abscissa, we can get a curve as Figure 1 (b) shows. Easy to understand that this boundary distance fluctuation curve contains enough information both of the shape and the size of the cross section. Then we successfully transform the two-dimensional image information to the one-dimensional wave signal; extract the most useful information for characterizing fiber cross-sectional contour.
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Figure 2 shows boundary fluctuation curves of 24 types of profiled fiber cross sections. It is quite evident that boundary fluctuation curves of different types of profiled cross sections differ significantly with each other. This curve can be the parameters of cross-sections for profiled fiber identification. For two fiber cross-sections, the similarity degree of their boundary fluctuation curves normalized can effectively reflect the similarity degree of themselves. Whether the two cross-sections belong to one category or not can be determined by comparing the similarity degree of the two curves. 2.2 Normalization of distance fluctuation curves In order to compare the curves’ similarity degree between each other, the original distance fluctuation curves should be normalized in advance. Since the numbers of cross-sectional boundary pixels are not identical, the numbers of discrete sequences are different. For convenient comparison of the similarity degree between each other, the sequence number must be regulated to be the same. Furthermore, according to the nature of fiber’s random distribution and arbitrary orientation, the starting points of the initial curves are not corresponding correctly, even for cross-sections which belong to one category. A direct comparison often caused great error. Regarding the curves as the discrete-time signals, we must solve the delay problem. Therefore, calibration of the starting point is necessary. (1) Regulating the number of discrete distance sequences. Fit the discrete sequence with a function curve, resample the fitting curve equidistantly N points to make a new discrete sequence which the number is normalized to N, as shown in Figure 3. Here, take N ¼ 400. (2) Calibrating the starting point. Since the distribution of fiber is random, the orientation can be arbitrary and fiber deformation is inevitable, it is very difficult to find their real corresponding starting points by means of image processing techniques, even for the same shapes. We successfully tackle this problem by calculating their cross-correlations using signal processing techniques. For two cross-sections, regarding their curves as discrete time signals, calculate their cross-correlation function, record the maximum to find the most relevant phase, we can correctly adjust the starting points. Suppose two boundary fluctuation curves which the number are normalized to N, x(t) and y(t), are both the sequences with the period N. Regarding them as discrete time signals, the cross-correlation function can be described by:
Figure 1. (a) A fiber cross-section object and (b) the original boundary distance fluctuation curve
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yðt þ n0 Þ is the curve which the starting point is corresponding correctly to that of x(t), as shown in Figure 4. Compare the similarity degree between yðt þ n0 Þ and x(t), we can get the similarity degree between the cross-sections represented by y(t) and x(t). 2.3 Calculation of the similarity degree of two curves The Euclidean distance between the two curves normalized is used to measure the similarity degree of the two waveforms. The smaller the Euclidean distance the higher the similarity degree and the bigger the possibility of the two cross-sections’ belonging to one category. The Euclidean distance between yðt þ n0 Þ and x(t) is given by: vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u N uX ð2Þ D ¼t ðxðtÞ 2 yðt þ n ÞÞ2 : xy
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2.4 Profiled fiber identification A read-in image, after undergoing the image preprocessing, can be converted to a binary image which the fiber and the background separate completely as Figure 5 shows. The values of each fiber object’s pixels all are 1, the values of the background’s pixels are 0. For each Fiber cross-section object, calculate the distance between the cross-sectional boundary pixels to the centroid, get the initial boundary fluctuation curve. Curves of
Figure 3. Illustrations of regulating the number of discrete distance sequences
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Fiber identification
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2.4.1 Achievement steps of pattern recognition. Suppose N fiber objects are obtained from binary images of one sample, objectð1Þ; objectð2Þ; . . .objectðN Þ. Their initial boundary fluctuation curves are object(1).feature, object(2).feature,. . . object(N).feature: . Step1. Compare the curves normalized with each other by calculating their similarity degrees. According to the statistical distribution of the similarity degree values, make the threshold T, which used to separate the distance between categories from the distance in categories. Figure 7 shows the distribution of the similarity degree values. . Step2. Take the first object as the first cluster centre, center(1). feature ¼ object(1).feature.Record the present number of cluster centers by centerNum. At this time, centerNum ¼ 1.center(i ).index ¼ i, (1 # i # centerNum). . Step3. For all the objects Calculate the distances between object(i ) and center( j), find the minimum Dj :ð1 # i # N ; 1 # j # centerNumÞ. If Dj , T this object belongs to category j, patternði Þ:category ¼ centerð jÞ:index N j is the number of category j. Since the new object belongs to category j, Njþ þ , revise the value of cluster centre j: 120 100 80 T 60 40 20 0
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Step4. Output the result of classification. Figure 8 shows the result image of fiber classification.
3. Validity test of parameters In the experiments of profiled fibers identification, five types of profiled fiber: triangular, trilobal, cross-shaped, pentagonal, dumbbell-shaped cross-sections are selected. Their fineness specifications are shown in Table I. Mutually mix these five types to make five samples, as shown in Table II. Cross-sections of the sample are prepared by one microtome. Five specimen slices are selected for each of these samples, a total of 25 specimen slices. Table II gives the results of profiled fiber identification. In this experiment, the accuracy of image processing is not considered, in order to reasonably analysis the effectiveness of the boundary fluctuation curve as parameters for fiber identification. In Table II, the results of recognition by the human eye are obtained by observing the binary images, and the numbers recorded in automatic identification results are just refer to the numbers of fibers identified correctly. 2
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Fiber identification
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Table II. The results of profiled fiber identification
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The average correct recognition rate of 25 slices is 96 percent. This certificates the validity of the boundary fluctuation curve as profiled fiber cross-sectional parameters for fiber identification. In the course of experiments, we found that, when the fiber cross-sectional area in image are too small, their boundary pixels are very little, original boundary fluctuation curves for describing the cross-section are too rough, the accuracy of species identification would be affected. The results of samples which contain cross-shaped or pentagonal fibers show this phenomenon. Fiber cross-sectional area are bigger in image, such as the experiments of samples which contain dumbbell cross-sections, original boundary fluctuation curve for describing the cross-section are more accurate, the results of identification are better. 4. Conclusions This paper has described in detail a method of fiber cross-sectional shape feature extraction for profiled fiber identification which is based on distance fluctuation curve. This curve contains enough information both of the shape and the size and can be the valid parameter of fiber identification. However, calibrating the starting point is an arduous task by mean of image processing since the distribution of fiber is random and fiber deformation is inevitable. By calculating their cross-correlations using signal processing techniques, we have successfully tackled the problem to finish the normalization of distance fluctuation curves. Experiments have proved the validity of the boundary fluctuation curve as profiled fiber cross-sectional parameters for fiber identification and the feasibility of the normalization method. A phenomenon should be noted that, fiber cross-sectional area are bigger, original boundary fluctuation curve for describing the cross-section are more accurate, the results of identification are better. Magnification used in capturing images of samples cannot be too small to meet the requirements of extracting accurate boundary fluctuation curves. Generally, the boundary pixels of a cross-section object should not less than 100. The method of pattern recognition which based on the similarity degree measurement should be improved in future for large amount of calculation when fiber numbers in one sample are very great. References Bao, N., Shen, L., Feng, X., Lu, X. and Yanagisawa, K. (2004), “Shape and size characterization of potassium titanate fibers by image analysis”, Journal of Materials Science, Vol. 39, pp. 469-76. Berlin, J.D., Worley, S., Jr, Ramey, H.H., Jr, and Linkous, S.S. (1981), “Measuring the cross-sectional area of cotton fibers with an image analyzer”, Textile Research Journal, Vol. 51 No. 2, pp. 109-13. Chiu, S.-H. and Liaw, J.-J. (2005), “Fiber recognition of PET/rayon composite yarn cross-sections using voting techniques”, Textile Research Journal, Vol. 75 No. 5, pp. 442-8. Hebert, J.J., Boylston, E.K. and Wadsworth, J.I. (1979), “Cross-sectional parameters of cotton fibers”, Textile Research Journal, Vol. 6, pp. 540-2. Hequet, E.F., Wyatt, B., Noureddine, A. and Thibodeaux, D.P. (2006), “Creation of a set of reference material for cotton fiber maturity measurements”, Textile Research Journal, Vol. 76 No. 7, pp. 386-576.
Hild, D.N., Obendorf, S.K. and Fok, W.Y. (2004), “Mapping of spin finish oils on nylon 66 fibers”, Textile Research Journal, Vol. 74 No. 3, pp. 187-92. Kajiwara, K., Nori, R. and Okamoto, M. (2000), “New fibers from Japan”, Journal of the Textile Institute, Part, Vol. 3, pp. 32-78. Li, Y. (1997), “Research on the application of image treatment on silk and wool blending ratio testing”, Journal of China University of Textile, Vol. 23 No. 4, pp. 31-8. Li, Z., Du, S., Zhang, D., Zhang, F. and Su, X. (2005), “Shape characterization and recognition of cross-section of profiled fibre by microscopy and image analysis”, Proceedings of 2005 International Conference on Advanced Fibers and Polymer Materials, pp. 197-200. Matic-Leigh, Rose and Cauthen, Debra A. (1994), “Determining cotton fiber maturity by image analysis, part I: direct measurement of cotton fiber characteristics”, Textile Research Journal, Vol. 64, pp. 534-44. Thibodeaux, D.P. and Evans, J.P. (1986), “Cotton fiber maturity by image analysis”, Textile Research Journal, Vol. 56, pp. 130-9. Thibodeaux, D.P. and Price, J.B. (1988), “Reference method for determination of the maturity of cotton fibers”, Melliand Textilber, Vol. 70 No. 4, pp. 243-6. Xu, B. and Huang, Y. (2004), “Image analysis for cotton fibers part II: cross-sectional measurements”, Textile Research Journal, Vol. 74 No. 5, pp. 409-16. Xu, B. and Ting, Y. (1996a), “Fiber image analysis part I: fiber image enhancement”, Journal of the Textile Institute, Vol. 87 No. 2, pp. 274-83. Xu, B. and Ting, Y. (1996b), “Fiber image analysis part II: measurement of general geometric properties of fiber”, Journal of the Textile Institute, Vol. 87 No. 2, pp. 284-95. Xu, B., Pourdeyhimi, B. and Sobus, J. (1993), “fiber cross-sectional shape analysis using image processing techniques”, Textile Research Journal, Vol. 63 No. 12, pp. 717-30. Xu, B., Wang, S. and Su, J. (1999), “Fiber image analysis part III: a new segmentation algorithm for autonomous separation of fiber cross-sections”, Journal of the Textile Institute, Vol. 90 No. 3, pp. 288-97. Xu, B., Dong, B. and Chen, Y. (2007), “Neural network technique for fiber image recognition”, Journal of Industrial Textiles, Vol. 36 No. 4, pp. 329-36. Yamazaki, K. and Okamoto, M. (1997), “A review of new directions in Shingosen and synthetic-fiber textiles for sportswear”, Journal of the Textile Institute, Vol. 88 No. 3, pp. 5-31. Corresponding author Yueqi Zhong can be contacted at:
[email protected]
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Pattern classification of fabric defects using support vector machines
142
A. Ghosh and T. Guha
Received 29 June 2010 Accepted 9 November 2010
Government College of Engineering & Textile Technology, Berhampore, India
R.B. Bhar Department of Instrumentation, Jadavpur University, Kolkata, India, and
S. Das Government College of Engineering & Textile Technology, Berhampore, India Abstract Purpose – The purpose of this paper is to address a solution to the problem of defect recognition from images using the support vector machines (SVM). Design/methodology/approach – A SVM-based multi-class pattern recognition system has been developed for inspecting commonly occurring fabric defects such as neps, broken ends, broken picks and oil stain. A one-leave-out cross validation technique is applied to assess the accuracy of the SVM classifier in classifying fabric defects. Findings – The investigation indicates that the fabric defects can be classified with a reasonably high degree of accuracy by the proposed method. Originality/value – The paper outlines the theory and application of SVM classifier with reference to pattern classification problem in textiles. The SVM classifier outperforms the other techniques of machine learning systems such as artificial neural network in terms of efficiency of calculation. Therefore, SVM classifier has great potential for automatic inspection of fabric defects in industry. Keywords Pattern classification, Fabric defects, Vector machines Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 142-151 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107333
1. Introduction Recently, fabric defect identification from images is becoming progressively more significant since it can able to automate the inspection of fabric defects during weaving. In the present work, a multi-class support vector machines (SVM) algorithm has been used to construct a pattern recognition system for inspecting fabric defects under different categories such as neps, broken ends, broken picks and oil stain. A SVM is trained with a learning algorithm from optimization theory and it utilizes the dual representation of the hypothesis resulting in extremely efficient algorithm. For a binary classification, a SVM algorithm uses a nonlinear mapping to transform the original training data into a high dimension feature space within which it searches for the linear optimal separating hyperplane or decision boundaries to separate the tuples of on class from another. The SVM finds the best separating hyperplane using ‘support vectors’ (SV) and ‘margins’. For multi-class classifications, commonly a set of binary classifiers is constructed, each trained to separate one class from the rest, and combine them by doing the multi-class classification. The SVM is a very powerful and computationally efficient method for classification and it has already outperformed other systems such as rule
based classifier, back propagation classifier, etc. in a wide variety of application (Critanini and Shawe-Taylor, 2000). In this work, one-leave-out cross validation technique has been applied to assess the efficiency of the multi-class SVM classifier for classification of various types of fabric defects. 2. Support vector machines SVM (Critanini and Shawe-Taylor, 2000; Vapnik, 1995, 1998; Schlkopf and Smola, 2001) are learning systems that use a hypothesis space of linear functions in a high dimensional feature space, trained with a learning algorithm from optimization theory that implements a learning bias derived from statistical learning theory (Vapnik, 1995, 1998). The aim of SV classification is to devise a computationally efficient way of learning good separating hyperplanes in a high dimensional feature space. Consider the problem of separating the set of training vectors belonging to two separate classes, ðX i ; y i Þ; X i [ Rn ; y i [ { 2 1; þ1}; i ¼ 1; 2; . . . ; N as shown in Figure 1. Theoretically, infinity number of hyperplanes in Rn which are parameterized by w and a constant b can be conceived thatcan separate the data into two classes. Our objective is to find a hyperplane f ðXÞ ¼ sign hw:X i þ b that correctly classify the data. The optimal hyperplane H should be such that: w:X i þ b $ þ1; when y i ¼ þ1
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and: w:X i þ b # 21; when y i ¼ 21 This corresponds to optimal separating hyper plane: H:
hw:X i þ b ¼ 0
ð1Þ
H2 x2
H H1
d+ d
–
Support vectors
x1
Figure 1. Optimal separating hyperplane with support vectors highlighted
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And the corresponding margins are defined as: H 1 : hw:X i þ b ¼ þ1 and:
ð2Þ
hw:X i þ b ¼ 21
ð3Þ
H2 :
144
It is desirable to have a classifier with as big margin as possible for optimal separation of data points. The distance between H and H1is given by: 1 : kwk2 Therefore, the total margin, which is the distance between H1 and H2 is: 2 : w k k2 In order to maximize the margin we need to minimize kwk2 . Under this condition there are no data points between H1 and H2, hence: w:X i þ b $ þ1; when y i ¼ þ1 and: w:X i þ b # 21; when y i ¼ 21: These two equations can be combined as y i w:X i þ b $ 1. The maximum margin classifier can be obtained by solving the following optimization problem: ð4Þ Minimize hw:wi y i w:X i þ b $ 1; i ¼ 1; 2; . . . ; N w;b
Formulating the Lagrangian, the primal Lagrangian is obtained as: Lðw; b; aÞ ¼
N X 1 ai y i w:X i þ b 2 1 hw:wi 2 2 i¼1
ð5Þ
where ai $ 0 are Lagrangian multipliers. The corresponding dual is found by differentiating with respect to w and a constant b and imposing stationarity: N X ›Lðw; b; aÞ ¼w2 y i ai X i ¼ 0 ›w i¼1 N ›Lðw; b; aÞ X ¼ y i ai ¼ 0 ›b i¼1
Simplifying the relations, we have: w¼
N X i¼1
y i ai X i
N X i¼1
y i ai ¼ 0
Classification of fabric defects
Resubstituting back in the primal Lagrangian we get: Lðw; b; aÞ ¼ ¼
¼
1 hw:wi 2 2 N X N 1X
2
N X
ai y i w:X i þ b 2 1
i¼1
N X N N X X y i y j ai aj X i :X j 2 y i y j ai aj X i :X j þ ai
i¼1 j¼1
N X i¼1
ai 2
i¼1 j¼1
145
i¼1
N X N 1X y i y j ai aj X i :X j 2 i¼1 j¼1
Hence, the dual problem becomes: N N X N X 1X Max a 2 y i y j ai aj X i :X j i a 2 i¼1 i¼1 j¼1
subject to
N X
i
y ai ¼ 0;
ð6Þ
ai $ 0; i ¼ 1; 2; . . . ; N
i¼1
The dual problem can be easily solved by readily available quadratic programming solvers to give a *. The weight vector that realizes the maximal margin hyperplane is given by: N X w* ¼ y i a*i X i ð7Þ i¼1
The value of b does not appear in the dual problem and so b * is found from primal constraints: max w * :X i þ min w * :X i y i ¼1 y i ¼21 ð8Þ b* ¼ 2 2 The corresponding Karush-Kuhn-Tucker complementarity condition is given by: h i a*i y i ð, w*i X i . þb * Þ 2 1 ¼ 0; i ¼ 1; 2; . . . ; N ð9Þ where a *, w * and b * are the optimal solutions. In the dual solution it turns out that most of the a * are zero. Non-zero values occur for the points that are closest to the hyperplane. These are known as the SV. The optimal hyperplane is given by: N X y i a*i X i :X þ b * f ðXÞ ¼ i¼1
X y i a*i X i :X þ b * ¼
ð10Þ
i[SV
In the case where a linear boundary is inappropriate the SVM can map the input vector, X i, into a high dimensional feature space. Among acceptable mappings are polynomials,
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Gaussian radial basis functions and certain sigmoid functions. In case of non-linear mapping into a high dimensional feature space, the optimization problem becomes: Maximize a
N X
ai 2
i¼1
146
subject to
N X N 1X y i y j ai aj KðX i ; X j Þ 2 i¼1 j¼1
N X
ð11Þ
y i ai ¼ 0
i¼1
ai $ 0;
i ¼ 1; 2; . . . ; N
The corresponding optimal hyperplane is given by: f ðXÞ ¼
N X i¼1
y i a*i KðX i ; X j Þ þ b *
¼
X
y i a*i KðX i ; X j Þ þ b *
ð12Þ
i[SV
The function KðX i ; X j Þ is a kernel function which projects the data into a high dimensional feature space and thereby increases the computational power of the linear learning machine. A kernel may be defined as a function K, such that for all X i ; X j [ X: ð13Þ KðX i ; X j Þ ¼ wðX i Þ:wðX j Þ where f is a mapping from input space X to an inner product feature space F. The use of kernels makes it possible to map the data implicitly into a feature space and to train a linear machine in such a space, potentially side-stepping the computational problems inherent in evaluating the feature map. Therefore, we need to first create a complicated feature space, and then work out what the inner product in that space would be, and finally find a direct method of computing that value in terms of the original inputs. Different types of kernel function are exemplified in the Table I. Figure 2 shows an example of a feature mapping, where linear classification of data cannot be possible in the input space; however it can be possible in the feature space. The main problem with the maximal margin classifier is that it always produces perfectly consistent hypothesis, which is a hypothesis with no training error. In real data, where noise can always be present, this can result in brittle estimator. Type of function Linear Polynomial Gaussian radial basis
Exponential radial basis Table I. Different type of kernels functions
Multilayer perceptron
Expression KðX i ; X j Þ ¼ X i · X j d KðX i ; X j Þ ¼ X i · X j þ t i ! X 2 X j 2 KðX i ; X j Þ ¼ exp 2 2s 2 i ! X 2 X j KðX i ; X j Þ ¼ exp 2 2s 2 KðX i ; X j Þ ¼ tanh s X i · X j þ t 2
These problems can be overcome by using the soft-margin optimization, where we need to introduce slack variables (ji) to allow the margin constraints to be violated: subject to yi w · X i þ b $ 1 2 ji ; ji $ 0; i ¼ 1; 2; . . . ; l: Thus, the soft-margin optimization problem becomes: l X ji ðfor 1-norm soft marginÞ minimizej;w;b hw:wi þ C
Classification of fabric defects
147
i¼1
or: minimizej;w;b
hw:wi þ C
l X
j2i
ðfor 2-norm soft marginÞ
i¼1
subject to
yi w · X i þ b $ 1;
ð14Þ i ¼ 1; 2; . . .; l:
where C is a pre-specified value. To get M-class classifiers, a set of binary classifiers B l, B 2 . . . , B M is constructed, each trained to separate one class from the rest, and combine them by doing the multi-class classification. In the present work, a multi-class 1-norm soft margin classifier has been used for the classification of fabric defects with the help of MATLAB 7.5 coding. 3. Developing SVM based pattern classification system A pattern recognition system for classifying fabric defects can be partitioned into a numbers of components as shown in Figure 3. At first, a digital camera captures the images of fabric defects. Next the camera’s signals are processed to simplify subsequent operations without losing relevant information. In this process, the images of different fabric defects are isolated from one another and from the background. The information from each fabric defect is then sent to a feature extractor, whose purpose is to reduce the data by measuring certain features or attributes. A classifier uses these features to evaluate the evidence presented and makes a final decision as to the fabric defects. Tsai et al. (1995) experimental data has been used for the purpose of classifying different fabric defects using the classifier based on SVM. Tsai et al. employed a grey level co-occurrence matrix to obtain the feature parameters f1, f2, f3, f4, f5, f6 for various defect categories such as nep, broken ends, broken picks and oil strain. The categories f
0
f (x)
x
0
f (x)
f (0)
x x
f (x)
f (0) 0
f (0) 0 x X
f (x)
f (0) F
Figure 2. A feature map can simplify the classification tasks
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Fabric defects
Image capturing
148 Image processing
Feature extraction
Figure 3. Components of a pattern recognition system for classifying fabric defects
Classification
Decision
are identified by numbers, namely 1-normal, 2-nep, 3-broken threads, 4-broken picks and 5-oil strain. Among the feature vectors, f1, f2, f3, and f4 are the contrast measurement of texture images along 08, 458, 908 and 1358, when spatial displacement d ¼ 1, while f5 and f6 are the contrast values at d ¼ 12, u ¼ 08, and d ¼ 16, u ¼ 908, respectively, where u is the direction angle. The dataset comprises of a total of 50 experimental data encompassing 10 experiments per category. Table II refers to the datasets representing various fabric defects. 3.1 Cross validation Cross validation techniques are very popular for model selection and performance estimation and thereby determining the generalization error of any machine-learning method (Han and Kamber, 2006). In every cross validation method the dataset is split into two groups; training dataset, i.e. used to train the model and testing dataset, i.e. used to estimate the predictive accuracy of the model. Among the various cross-validation techniques the one-leave-out cross validation has been used in this work. The one-leave-out cross validation is a relatively new technique in which only one sample is left out at a time for the testing and the rest of the dataset are used for the training. And for the next cycle a new sample is taken for the testing and rest of the dataset are used as training dataset. The cycles repeat until each sample is used the same number of times for training and once for testing. Hence, the total number of cycles is equal to the size of the dataset. The one-leave-out cross validation method for N number of data sets is schematically shown in Figure 4. 3.2 Optimization of SVM parameters The parameters for SVM classifier were tuned by means of trial and error method. For this purpose both the Gaussian radial basis and polynomial kernels were considered and several combinations of the different parameters such as the width of the Gaussian radial basis kernel (s), the degree of the polynomial kernel (d ), and the penalty term C
f1 0.39 0.4026 0.3879 0.3931 0.3826 0.3978 0.392 0.3887 0.388 0.3851 0.3689 0.3789 0.3663 0.3881 0.3964 0.3529 0.3465 0.3467 0.3697 0.3537 0.3509 0.3661 0.3717 0.3589 0.3436 0.3159 0.3354 0.3231 0.3534 0.3761 0.3723 0.3836 0.3716 0.4115 0.4321 0.3765 0.3987 0.384 0.3854 0.3873 0.4 0.2626 0.2657 0.364 0.4051 0.3592 0.4049 0.3586 0.3049 0.4029
f2
f3
f4
f5
f6
Defects
0.6402 0.6362 0.6161 0.6381 0.6298 0.6433 0.6464 0.6363 0.6322 0.6228 0.6188 0.6173 0.6173 0.6345 0.6362 0.5768 0.5874 0.5767 0.5805 0.5642 0.5957 0.5915 0.5968 0.5903 0.5775 0.5158 0.5356 0.5202 0.5655 0.5795 0.5821 0.6022 0.5918 0.6037 0.6446 0.608 0.6132 0.5953 0.6023 0.597 0.4976 0.3115 0.3276 0.4823 0.5158 0.4453 0.4874 0.4805 0.3866 0.5257
0.3584 0.3601 0.3419 0.3569 0.3537 0.3704 0.3532 0.3601 0.3672 0.3567 0.3483 0.3447 0.3444 0.3569 0.3512 0.3219 0.3225 0.313 0.3232 0.3182 0.3507 0.3361 0.3237 0.323 0.3298 0.3214 0.3373 0.3197 0.3275 0.3399 0.2097 0.3054 0.3101 0.2797 0.309 0.3098 0.3145 0.3123 0.3101 0.3074 0.3254 0.2417 0.2263 0.3034 0.3361 0.3003 0.3207 0.3102 0.2726 0.3363
0.4205 0.432 0.4153 0.4284 0.4234 0.443 0.4221 0.4202 0.4302 0.4361 0.4026 0.4042 0.4045 0.4305 0.4236 0.3865 0.3819 0.3782 0.3978 0.3918 0.4079 0.4137 0.4003 0.3931 0.3907 0.3981 0.4095 0.3899 0.4129 0.4324 0.3695 0.3861 0.3761 0.4036 0.4157 0.3842 0.3954 0.392 0.389 0.3944 0.3969 0.2633 0.2723 0.3518 0.4082 0.3543 0.3977 0.3614 0.3215 0.4028
0.3726 0.3438 0.3228 0.3694 0.3489 0.3584 0.3352 0.322 0.3481 0.3496 0.4393 0.3954 0.4439 0.4214 0.4049 0.4417 0.474 0.3845 0.466 0.4358 0.5432 0.4808 0.4708 0.4377 0.4888 0.5433 0.5594 0.5466 0.521 0.529 0.3453 0.3383 0.3595 0.3987 0.4254 0.3198 0.3272 0.3165 0.3154 0.3554 0.5242 0.4584 0.3681 0.5274 0.6228 0.4673 0.5187 0.4967 0.4967 0.5465
0.3434 0.3442 0.3547 0.4308 0.3435 0.3811 0.3859 0.3257 0.3378 0.3371 0.4813 0.4213 0.4788 0.5121 0.421 0.4725 0.5255 0.4925 0.4953 0.5035 0.3107 0.2884 0.3376 0.3266 0.3454 0.3301 0.3677 0.351 0.3302 0.3305 0.3765 0.3429 0.3248 0.3294 0.3284 0.3587 0.3829 0.4022 0.3635 0.3735 0.4233 0.3841 0.4321 0.62 0.6095 0.41 0.424 0.8066 0.5492 0.4661
1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5
Source: Adapted from Tsai et al. (1995)
Classification of fabric defects
149
Table II. Dataset for various kinds of fabric defects
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Training data set 1st cycle:
1 Testing sample
150
Training data set i
ith cycle:
Testing sample
Figure 4. Schematic representation of one-leaveout-cross-validation
Testing sample nth cycle: n Training data set
were tried out. In case of Gaussian radial basis kernel, the optimum values for s and C were found to be two and 1,000, respectively. For polynomial kernel, the optimum values for d and C were estimated as two and 100, respectively. 3.3 Validation of the proposed system One-leave-out cross validation was applied to assess the performance of the multiclass 1-norm soft-margin SVM classifier for classifying the fabric faults under various categories. The SVM classifier was trained using 49 data and tested on the sample left out for each cycle. The training and testing were performed for 50 cycles. Table III shows the expected generalization accuracies correspond to training as well as testing, which were estimated over 50 cycles. The learning accuracy on the training set was expectedly higher than the predictive accuracy on the test data due to the fact that the latter was performed on the unseen dataset. The grand testing accuracies using both types of kernels were found to be 98 per cent. 4. Conclusions This paper outlines the theory and application of SVM classifier with reference to pattern classification problem in textiles. A multiclass 1-norm soft margin SVM classifier with one-leave-out cross validation technique has been used for the classification of various fabric defects. The results shows that the fabric defects inspected by means of image recognition in accordance with the SVM classifier agree reasonably well. The SVM classifier outperforms the other techniques of machine learning systems such as Artificial Neural Network (ANN) in terms of efficiency of calculation. Therefore, SVM classifier has great potentiality for automatic inspection of fabric defects in industry. Table III. Training and testing accuracies of SVM classifier
Grand accuracies Training accuracies Testing accuracies
With Gaussian radial basis kernel (%)
With polynomial kernel (%)
100 98
99.95 98
References Critanini, N. and Shawe-Taylor, J. (2000), An Introduction to Support Vector Machines and Other Kernel Based Learning Methods, Cambridge University Press, Cambridge. Han, J. and Kamber, M. (2006), Data Mining Concepts and Techniques, 2nd ed., Morgan Kaufmann Publishers, San Francisco, CA. Schlkopf, B. and Smola, A.J. (2001), Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond, MIT Press, Cambridge, MA. Tsai, S., Lin, C.H. and Lin, J.J. (1995), “Applying an artificial neural network to pattern recognition in fabric defects”, Textile Research Journal, Vol. 65 No. 3, pp. 123-30. Vapnik, V. (1995), The Nature of Statistical Learning Theory, Springer, New York, NY. Vapnik, V. (1998), Statistical Learning Theory, Springer, New York, NY. Corresponding author A. Ghosh can be contacted at:
[email protected]
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152 Received 27 April 2010 Revised 24 September 2010 Accepted 24 September 2010
Simultaneous influence of ageing and softener on mechanical properties of knitted textiles during life cycle of garment Gaurav Agarwal, Ludovic Koehl and Anne Perwvelz Ecole Nationale Supe`rieure des Arts et Industries Textiles, Roubaix, France Abstract Purpose – The purpose of this paper is to examine the influence of ageing and the use of fabric softener during the life cycle of knitted fabrics. Design/methodology/approach – The low-stress mechanical properties were evaluated by means of the Kawabata evaluation system for fabric (KES-F) and universal surface tester (UST) revealing that the tensile, shear, bending, compression and surface properties were altered by both ageing during the wash cycles and the use of fabric softener. Findings – Machine laundering leaves fabrics with an uncomfortable hand due to the removal of finishes and the harsh mechanical action of laundering, and results in the change in mechanical properties of the fabrics. Originality/value – The paper identifies the critical mechanical parameters which are influenced by ageing and the use of fabric softeners during life cycle of garments. Keywords Mechanical properties of materials, Knitwear, Cleaning, Fabric softeners, Ageing (materials) Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 152-169 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107342
Introduction During the knitting process, the yarns forming the fabrics are constantly under stress. As a result, the fabric is more distorted than in its natural relaxed state. After removal of the knitted fabric from the machine, it starts to overcome these stresses by means of dry and wet relaxation. During the laundering process also, fabrics relax toward their minimum energy configuration. Machine laundering alters the apparel performance during wear because of changes in fabric mechanical properties during laundering. That is why the need for a fabric softener was recognized. A fabric softener is a product designed to increase the consumer’s satisfaction regarding comfort and aesthetic aspects resulting from the wash. Low-stress mechanical properties or combinations of these are the deciding factors for comfort aspects of any apparel during wear. Fabric stiffness, harshness and other unwanted laundering effects can be overcome by regular use of a fabric softener in the washing process. Morton and Hearle (1962) pointed out that the fabrics that we deal with in everyday life are not in relax condition and come to their relaxation condition after several washings. Many researchers have reported that this relaxation process during ageing will depend on the laundry parameters. Each separate step of the laundering has an influence The authors thank Dr Kenneth Lee and his team from Unilever Research and Development Laboratory, Port Sunlight for providing their valuable suggestions and guidelines; it was not possible to do the present work without their technical and financial support.
on dimensional stability and distortion of knitted fabrics, that is why it is very important to select optimum laundry parameters to minimize the distortion of fabrics (Anand et al., 2002; Fijan et al., 2007; Morris, 1970). The level of changes that occur in the fabric dimensions are not consistent, most of the changes occur in the initial laundry cycles and these changes also depend on the fiber type and construction (Higgins et al., 2003a, b). Changes in mechanical properties resulting from laundry are related to physicochemical changes occurring at the fiber level in cotton, wool and acrylic (Mackay et al., 1999). The importance of the chemical action of water on hydrophilic-fiber fabrics as opposed to hydrophobic fabrics is manifested by the wet relaxation process (Quaynor et al., 2000). The behavior of knitted fabrics under bending and shear deformation was studied by Mehmet and he found that the progress of relaxation leads the fabric towards greater rigidity (UCAR Mehmet, 2003). The use of rinse cycle softener generally reduces the level of shrinkage and also causes a slower down or reversed the successive loss of mass observed when no softener was used (Higgins et al., 2003a, b). Virginija also observed that fabric finishing with chemical liquid softeners significantly influence the slower deterioration of the hand parameters during the use of the fabric (Daukantien et al., 2005). Significant research has been done on the influence of different kinds of fabric softeners on softness, wrinkle recovery, pilling, breaking strength, yarn pull out force and other mechanical properties (Baumert et al., 1996; Chiweshe and Crews, 2000; Sebastian et al., 1986). J. Peberdy also reported that cationic fabric softeners limit inter-fiber friction and tapering entanglements of fibers (Peberdy et al., 2008). Belinda et al. (2009) have studied influences of laundry on some of the mechanical properties of the textiles and found that laundry cycle does not have a significant effect on fabric drape, shear or bending properties. However, drape values increased overall, while shear and bending modulus and hysteresis decreased, resulting in a more drapable, pliable fabric after five laundry cycles. Impact of laundering on the seam tensile properties of suiting fabric was also investigated by Mukhopadhyay and Karmakar (2004). All these studies need to be further extended in order to understand the influence on mechanical properties during the life cycle of a garment under the practical laundry practices. This study is dealing with simultaneous influence of ageing and rinse cycle softener on mechanical properties from cradle to grave state of fabric. The life cycle of a garment was considered to have 40 washing cycles. We tried to identify the degree of influence of these two factors on different mechanical properties and to discuss physicochemical changes that occur during the laundry process. Experimental Details of the fiber, yarn and knitted fabric parameters used in this work are given in Table I. We used 13 knitted fabrics varying in fiber type (viscose and polyester (PET)), fiber fineness (micro and regular), knitting construction ( jersey, rib and interlock). All the knitted fabrics involved in this work were subjected up to 40 wash cycles. The washing was done under two conditions, i.e. with and without softener. A front loading washing machine from Miele (model: A W3268) was used for laundering. The whole study requires running the was cycles under the same conditions: same cycle, same softeners, same water hardness, same loading weight. These conditions should be close to consumer laundry practices in order to make this study market relevant. All the washing experiments were done under the following conditions:
Influence of ageing and softener 153
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Code VmJ
154
Table I. Yarn and knit parameters of the fabrics of the study
Fiber type
Fiber fineness & yarn construction
Knitting structure Porosity gsm Gauge
100% Viscose Micro fiber (1.30 dtex) Ring-modal 50 Nm Jersey 1£1 VmR 100% Viscose Micro fiber (1.30 dtex) Ring-modal 50 Nm Rib VmI 100% Viscose Micro fiber (1.30 dtex) Ring-modal 50 Nm Interlock VRJ 100% Viscose Regular (1.95 dtex) Ring 50 Nm Jersey 1£1 VRR 100% Viscose Regular (1.95 dtex) Ring 50 Nm Rib VRI 100% Viscose Regular (1.95 dtex) Ring 50 Nm Interlock VmOJ 100% Viscose Regular (1.30 dtex) Open end 50 Nm Jersey PmJ 100% PET Micro fiber (1.13 dtex) Multifilament Jersey 60 Nm PmR 100% PET Micro fiber (1.13 dtex) Multifilament 1£1 60 Nm Rib PmI 100% PET Micro fiber (1.13 dtex) Multifilament Interlock 60 Nm PRJ 100% PET Regular (1.83 dtex) Multifilament Jersey 60 Nm PRR 100% PET Regular (1.83 dtex) Multifilament 1£1 60 Nm Rib PRI 100% PET Regular (1.83 dtex) Multifilament 60 Interlock Nm
0.884
145
28
0.895 0.879 0.894
180 240 160
20 20 28
0.905 0.882 0.897 0.895
175 250 150 130
20 20 28 28
0.882
165
20
0.864
230
20
0.867
172
28
0.862
200
20
0.854
250
20
Notes: VRJ, viscose-regular-jersey; VRR, viscose-regular-rib; VRI, viscose-regular-interlock; PRJ, polyester-regular-jersey; PRR, polyester-regular-rib; PRI, polyester-regular-interlock . . . .
. . .
load: 1 kg; no prewashing; washing product: 45 ml non-bio liquid detergent, provided by Unilever in 2008; fabric conditioner: 35 ml (rinse cycle cationic conditioner: Comfort Pure (white), provided by Unilever in 2008; 408C cotton cycle; water hardness: 258F; and line dried.
We chose the minimum load possible on our washing machine to provide sufficient mobility to the fabric so that achieve maximum uniformity of deposition of softener could be achieved. The recommended temperature for washing of these fibers is up to 608C, so we decided to use the 408C cotton cycle for washing. Mechanical properties of all laundered fabrics were measured using appropriate instruments. The objective measurements, chosen to represent major changes that occur during the life cycle of apparel are given in Table II. All measurements were made on conditioned fabric samples at 20 ^ 28C and 65 ^ 2 per cent RH. The mechanical parameters were measured after initial (one and five) washing cycles, at middle of life cycle (20 washing cycles) and at end (40 washing cycles). All the measurements were made in wales and course directions, and mean values were used in further data analysis. The tensile measurements were made on “high sensitivity” configuration because
Properties
Characteristic value Unit
Tensile
EMT
%
RT G 2HG & 2HG5 B 2HB
% gf/cm · 8 gf/cm gf· cm2/cm gf· cm/cm
Shear Bending
Compression WC RC
gf· cm/cm2 %
Surface
Ra Rz
mm mm
D ED
mm mm
Definition Percentage of extended length after applying known tensile force Ability of fabric to recover after applying tensile stress Ability of the fabric to resist shear stress Fabric recovery ability after applying the shearing stress Measure of elastic resistance to the bending of yarn Measure of interfiber and inter yarn friction opposing fiber and yarn movement arising from bending Energy associated in applying a certain amount of load Determine the recoverability of the fabric after compression deformation Deviation of surface from mean position Mean of distance between the five highest peaks and the five deepest holes Deformation corresponding to surface of the textile Recoverable deformation corresponding to surface of the textile
of higher stretchability of the knitted fabrics. In order to obtain the surface deformation parameters of knitted fabric with papillary stylus, the surface properties of the knitted fabrics were measured using universal surface tester (UST) instead of KES. Tensile properties KES-FB-1-A system was used to measure the tensile properties of knitted samples, which have gone through one, five, 20 and 40 ageing cycles with and without fabric softener. All the tests were conducted under the high sensitivity condition, i.e. maximum tensile load 120 gf/cm, elongation speed: 0.1 mm/s, sample size: 20 £ 20 cm2. Compression properties KES-FB-3-A system was used to measure the compression properties of knitted samples, which had gone through one, five, 20 and 40 ageing cycles with and without fabric softener. All the tests were conducted under the standard condition, i.e. Compression speed: 0.02 mm/s, maximum pressing load: 50 gf/cm2 and with area of pressing plate 2 cm2 (circle). Shear properties KES-FB-1-A system was used to measure the compression properties of knitted samples, which had gone through one, five, 20 and 40 ageing cycles with and without fabric softener. All the tests were conducted under the standard condition, i.e. maximum shear angle ^ 88, sample size: 20 £ 20 cm2, Fabric tension 200 gf (10 gf/cm), speed of shearing deformation 0.4688/s. Bending properties KES-FB-2-A system was used to measure bending properties, all the tests were conducted under the standard condition, i.e. max curvature (K): ^ 2.5 cm2 1, bending rate: 2.5 cm2 1/s and sample size: 20 £ 20 cm2.
Influence of ageing and softener 155
Table II. List of main mechanical properties
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156
Surface properties UST was used to measure the surface properties of the knitted fabrics. UST is an instrument for the determination of micro mechanical properties of the material by determining the deformation behaviour of material near its surface. 3-D standard measurement. This measurement was carried out to study the viscoelastic behaviour of knitted textiles during life cycle. During this measurement the surface was scanned three times, the load during first and third measurement was almost negligible (1 mN) during the second measurement a value of 25 mN was chosen. The scanning was done at 100 mm/s with the increment of 2 mm. The area of 10 £ 4 mm of sample was scanned. Roughness measurement. Knitted samples were scanned for a 15 mm length at the speed of 0.10 mm/s without using a load. The roughness (Ra) was defined as the arithmetic mean of the deviation from the mean and roughness depth (Rz) is the mean of the distance between the five highest peaks and the five deepest holes. The selection of the stylus is very critical for the surface properties of fabrics. The papillary stylus which is very similar to polymeric human finger sensor developed by Ramkumar et al. (2003a, b) was selected for all surface parameters measurements in order to get results which represent human feeling. Data treatment The 13 knitted fabric samples were put through a varying number of ageing cycles (one, five, 20 and 40) under two different conditions (with and without softener). The third set of knitted fabrics was washed for 39 cycles without fabric softener and then during the 40th washing cycle fabric softener was used (these samples are referred to below as “40A”). This was in order to investigate the effect of fabric softener, if it is used only at the end of life cycle. In this way for each mechanical property, we have a space of 117 (13 £ 4 £ 2 þ 13) fabric samples. In order to reduce the complexity of the data we used a classification method of data mining called a decision tree (Masataka, 2010; Breiman et al., 1984). This method builds a tree which is used to mine the large amounts of data to reveal previously unknown relationships between inputs (wash ageing and use of softener) and output (mechanical parameters). The decision tree subdivides the data into different clusters based on the same input parameters. We chose the number of ageing cycles (one, five, 20 and 40) and treatment type (with softener, without softener, softener used for only 40th cycle) as inputs to generate the decision tree for each mechanical parameters. The leaves of the decision tree correspond to the centre of gravity of the cluster. Each branch in the tree is labelled with its decision rule, and each terminal node is labelled with the predicted value for that node. For each branch node, the left child node corresponds to the points that satisfy the condition, and the right child node corresponds to the points that do not satisfy the condition. Previous studies show that behaviour of viscose and PET differ during laundry, so we decided to make a decision tree for the two kinds of fabrics separately (63 viscose fabrics and 54 PET fabrics). We defined parameters mw and mS in order to quantified the influence of ageing and softener on the different mechanical properties. We calculated percentage change in mechanical properties due to ageing and use of fabric softener:
M 40 2 M 1 £ 100 mw ¼ M1
ð1Þ
where
Influence of ageing and softener
mw ¼ Percentage change in mechanical properties due to washing or ageing. M40 ¼ Value of mechanical parameter after 40 washing cycles.
157
M1 ¼ Value of mechanical parameter after one washing cycle. We cannot compare the influence of ageing between two successive stages of the life cycle (e.g. between one and five, five and 20, 20 and 40) because the total number of ageing cycles between the stages are not equal, being four, 15 and 20, respectively. So we considered only the total ageing influence at the end of life cycle of the fabric. For the effect of softener:
mS ¼
1X 4
M NS 2 M NW £ 100 M NW
ð2Þ
N ¼1;5;20;40
mS
¼ Percentage change in mechanical properties due to use of fabric softener.
MNS ¼ Value of mechanical parameter after N washing cycles with fabric softener. MNW ¼ Value of mechanical parameter after N washing cycles without fabric softener. mS identifies the influence of fabric softener at different stages of the ageing, i.e. after one, five, 20 and 40 wash ageing cycles. When we compare MNS and MNW (Value of mechanical parameter after N washing cycles with and without softener), N (Number of ageing cycles) is equal. Results and discussion In Figure 1, decision tree for the tensile extension (EMT) value of viscose and PET fabric is shown. An example of how to read a decision tree is shown by the darker lines in the decision tree of viscose fabric. The darker portion indicates that if viscose fabrics have been washed without softener than it will be in the left part of the decision tree. Among these fabrics, the fabrics which have gone through 40 washing cycles have EMT value of 16.65 per cent, for the remaining fabrics the decision tree has to be followed via the right side child node, which shows that if fabrics have gone though 20 washing cycles then the EMT value is 18.43 per cent. The first two nodes of the decision tree (Figure 1) show that fabric softener has a major influence on EMT, under the influence of fabric softener, fabrics show an increased EMT value for both viscose and PET samples. In the case of viscose knitted textiles at the end of their life cycle (40th wash cycle), the increment in EMT value was enhanced if softener had been used for every ageing cycles of the fabric instead of using it only for the 40th cycle (Figure 2). But in the case of PET knitted textiles at the end of their life cycle, there is no difference in the impact on EMT between the use of softener for every wash cycle or for the use of softener in only the 40th cycle. The increased EMT value seen with the use of softener is caused by the fabric softener changing the inter-fiber and inter-yarn friction and adhesion,
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Without softener Ageing 40
20
5
With softener 1
5
Without softener
40
20
Without softener 1
Ageing 20
5
40
40th S All
With softener 1
5
20
1
40
Without softener
Ageing = 5
Ageing (5,20)
16.65
Ageing (5,20)
Ageing (1,5)
Ageing = 5
Ageing = 20
Polyester
158
Viscose
Ageing = 40
Ageing = 20 Ageing = 20
18.37 Ageing = 40 19.27 Ageing =1
Ageing =20
19.52
Softner = 3
22.67
16.55
23.63
16.65
17.09
17.33
EMT (%)
20.01 EMT (%)
Figure 1. Decision tree for EMT of viscose and PET knitted textiles
19.75 18.43
18.63
20.79
19.78
21.66
25
EMT (%)
24
Figure 2. Change in EMT with successive ageing and use of fabric softener
23
Viscose-without softener
22
Viscose-with softener
21
PET-without softener
20 PET-with softener
19 18
Viscose-40A
17
PET-40A
16 15 1
5 20 40 Number of washing cycles
40A
making the fibers more mobile due to boundary lubrication. The values resulting from the decision tree have been presented in Figure 2 in order to demonstrate the behaviour of EMT of viscose and PET fabrics during their life cycle. Regenerated cellulosic fibers like viscose swell about 70-130 per cent by volume in water, because of this swelling viscose knitted fabric’s shape and orientation of loops change and relax toward their minimum energy configuration. Fiber swelling causes cellulosic textiles to become jammed in the wet state, they then resists fabric extension. So with successive ageing cycles the EMT value will be reduced. For viscose without softener, the reduction of EMT value was more prominent in the initial ageing cycles (one to five cycles), after that the rate of reduction is not so high because the loops have already achieved their minimum energy stage. The change in EMT, as a result of washing alone, between five and 20 washing cycles was observed to be a minimum. In this period of life cycle (five to 20) the influence of softener was found to be greater and hence there was increase in EMT value from five to 20 washing cycles in case of viscose washed with softener. After 20 washing cycles fibers may start to damage or serious fiber fibrillation may start because of vigorous and repeated mechanical
action, which will further effect mechanical properties. In some samples, it was observed that during initial ageing cycles (one to five) EMT increases, this may be because swelling leads to increase in yarn crimp which enhanced EMT. As PET fibers are highly crystalline, mechanically tough and hydrophobic, and do not swell significantly in water, significant change was not observed in the EMT value with successive ageing cycles. There were random changes in the middle of the ageing because of mechanical action, but at the end of the life cycle, the EMT value was observed to be the same as at the beginning. A reduced fabric tensile resilience (RT) value indicates that the fabric is having difficulty recovering from its original shape after removal of the applied tensile stress. Figure 3 shows that fabric softener increases the RT value for both viscose and PET fabrics. When the tensile force is removed, the lubricating effect of the fabric softener helps the fibers to regain their original position. This implies that fabrics washed with fabric softener have more tendency to retain garments shape than fabric washed without softener. The prolonged washing treatment reduces the RT value as, with successive washing, the fibers have got to their minimum energy state resulting in a loss of springiness of the structure. When the fabric softener was only used for the 40th cycle, it did not seem to improve RT. However, continuous use of fabric softener reduces the influence of the ageing process. In PET fabrics RT decreased during the first 20 ageing cycles, after this there was little further change. The compression energy (WC) value of fabrics implies a fluffy feeling of the fabric. When the value of WC increases, the fabric will appear fuller. The decision tree (Figure 4) of viscose knitted textiles shows that after going through prolonged washing cycles (20 and 40), the WC value will be greater compared to fabrics which have just gone through the initial washing cycles (one and five). The reason for the higher WC value may be the presence of loose fluffy fibers and pills on the surface of the fabrics, alternatively it may be a bulk effect due to greater relaxation of the textile.
Influence of ageing and softener 159
50 45 Viscose-without softener Viscose- with softener PET-without softener PET-with softener Viscose-40A PET-40A
RT (%)
40 35 30 25 20 1
5 20 40 Number of washing cycles
40A
Figure 3. Change in RT with successive ageing and use of fabric softener
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Ageing (1 5) Without With softener 5 softener 5
With softener40th cycle
Ageing (20 40)
Without With softener 1 softener 1
40th cycle Without Without With With softener softener 20 softener 40 softener-20 softener-4
Ageing 40
Ageing (1,5)
Without softener 40
20
With softner
5
1
Softener in only 40th ageing cycle
Ageing = 5
5
1
40
20
Without softener
Without Softener/ 40th cycle softner Ageing (5,20,40)
0.325
0.356
0.374
Without softener
Softener for only 40th cycle
0.36
0.377
Ageing = 20
Ageing = 20
0.48
0.5
0.50
0.367
Ageing (1,5)
PET
Without softener
2 WC (gm cm/cm )
Figure 4. Decision tree for WC of viscose and PET knitted textiles
WC (gm cm/cm2)
160
Viscose
0.24
Ageing = 40
0.276
Ageing = 40 Ageing = 5
Ageing = 20
0.256
0.269
0.262
0.273
0.278
0.283
0.263
It can be also observed from Figure 5 that in case of five, 20 and 40 ageing cycles, fabrics softener increases the WC value but in case of one ageing and 40A (Softener used for only 40th cycle), there was no significant change. PET fibers are highly crystalline, mechanically tough and hydrophobic. They do not swell significantly during washing, so both the surface and the thickness remain almost the same even after 40 ageing cycles. As a result the WC value does not change significantly. The influence of softener was also not so significant for the PET samples. The compression resilience (RC) value can help to quantify the recoverability of the fabric after compressional deformation. When the value is large, the recovery from deformation after compression will be good. Figure 6 shows that influence of wash-ageing and use of the fabric softener on RC was found to be random for viscose fabrics. While for PET fabrics, it was found that RC value decreases during initial five wash-cycles and increased by prolonged wash-ageing. The use of the fabric softener for prolonged wash ageing of PET fabrics also increases the RC value. 0.6
WC (gm cm/cm2)
0.5
Viscose-without softener
0.4
Viscose-with softener PET-without softener
0.3
PET-with softener Viscose-40A
0.2
PET-40A
0.1
Figure 5. Change in WC with successive ageing and use of fabric softener
0 1
5
20
40
Number of washing cycles
40A
Influence of ageing and softener
55 50 45 Viscose-without softener RC (%)
161
Viscose-with softener
40
PET-without softener PET-with softener
35
Viscose-40A PET-40A
30 25
Figure 6. Change in RC with successive ageing and use of fabric softener
20 1
5
20
40
40A
Number of washing cycles
The shear rigidity (G) of the fabrics primarily depends on yarn interaction, i.e. an increase in yarn interaction will increase G. Figures 7 and 8 show that for both viscose and PET, the use of fabrics softener during laundering decreases the G of the textiles. The reason is the boundary lubrication of the fibers and yarns, which enhances the mobility on applying a shear stress. The decision tree shows that even after prolonged ageing of knitted fabric, a single use of softener (in 40th cycle only) will enhance the shear property. There is no influence of ageing on G for PET fabrics but in viscose fabrics with successive washing cycles G increases. In the latter case, successive washing causes the fibers to swell and relax towards their minimum energy configuration. The loops become rounder in shape causing more interaction of the yarns and resulting in increased inter-yarn friction. Figure 9 shows that for viscose and PET knitted fabrics ageing has a negative impact (increase in hysteresis value) on the recovery ability of fabrics after removing With softener Ageing
1
20
40th
Without softener 40
5
1
5
20
40
With softener Ageing 40th 40
20
Without softener
1
5
1
5
20
40
With softener With softener Ageing (1,20,40)
Viscose
Ageing = 1
0.56
PET
Ageing = 1 Ageing = 20
0.65 0.66
Ageing = 40
Softener in only 40th cycle
0.59
Ageing = 20
0.66
Ageing = 40
0.60
Ageing = 5 0.64
0.62 0.64
0.62
0.63
0.70
0.74
G (gm/cm degree)
0.49 G (gm/cm degree)
Ageing (20,40)
Ageing (1,5) Ageing = 20
Ageing = 1
Softener only in 40th cycle 0.58
0.56
0.57
0.66
Figure 7. Decision tree for G of viscose and PET knitted textiles
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0.8 0.75 0.7 G (gm/cm degree)
0.65
162
Viscose-without softener Viscose-with softener
0.6
PET-without softener
0.55
PET-with softener
0.5
Viscose-40A PET-40A
0.45 0.4 0.35
Figure 8. Change in G with successive ageing and use of fabric softener
0.3 1
5 20 40 Number of washing cycles
40A
3.5
3
HG (gf/cm)
Viscose-without softener Viscose-with softener
2.5
PET-without softener PET-with softener 2
Viscoe-40A PET-40A
1.5
Figure 9. Change in HG with successive ageing and use of fabric softener
1 1
5
20
40
40A
Number of washing cycles
the shear forces. Use of fabric softener enhances the recovery ability from the shear deformation. In the case of viscose fabrics, the influence of prolonged ageing (40 ageing) is so significant that even the use of fabric softener is not able to enhance the recovery ability of these fabrics. However, for both viscose and PET fabrics in the case of one, five and 20 cycles shear hysteresis (HG) is lower for the fabrics washed with softener than those washed without softener. Figure 10 represents the decision tree for Bending rigidity (B) of knitted textile, where B is the average of forward bending rigidity (Bf) and backward bending rigidity (Bb).
Ageing (1,5,20) Softner With 1 Without Without With 5 1 5
Ageing 40 With 20 Without 20
40th
With
With softener Without
Ageing
40
20
Without softener
40th
1
5
20
1
40
5
With softener
Ageing (1,5,20)
Influence of ageing and softener
Ageing (1, 20, 40) Ageing = 1
Viscose
With softener
0.047
0.33
0.029
0.040 Ageing = 1
0.038 0.031
2
0.023
Ageing = 40
B (gm cm /cm)
With softener
Without softener
2
B (gm cm /cm)
With softener
163
Ageing = 20 0.038
Softener only in 40th cycle
Ageing = 5
Ageing (1, 20, 40)
Ageing (20,40)
PET
With softener
0.0053 0.0093 0.011
0.017
0.0128
0.026
0.029
0.030 0.039
0.039
Figure 10. Decision tree for B of viscose and PET knitted textiles
It can be noticed in Figure 11 that B of viscose knitted textiles increases with successive washings and the rate of increase in B is enhanced with increased number of ageing cycles (up to 40 ageing cycles). The reason for the increased B is the relaxation state of the knitted textile: loop relaxation causing the loops to have a rounder shape resulting in more interaction between loops. This in turn causes an increase in the tightness factor, since increasing tightness factor means decreasing space for stitch movements as well an increased friction between yarns. Another possible reason is the deposition of Ca þ and Mg þ ions. The use of fabrics softener during laundering decreases the B of the textiles. The reason for this is the boundary lubrication of the fibers and yarns. Even a single use of fabric softener after 39 washing cycles improves B. For PET knitted textiles, there was no significant change in B through out the ageing process. 0.05 0.045 0.04
B (gm cm2/cm)
0.035
Viscose-without softener Viscose-with softener PET-without softener PET-with softener Viscose-40A PET-40A
0.03 0.025 0.02 0.015 0.01 0.005 0 1
5
20
40
Number of washing cycles
40A
Figure 11. Change in B with successive ageing and use of fabric softener
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164
The bending moment hysteresis reflects the recovery ability of fabric after bending. The smaller the value of bending hysteresis (2HB), the better the fabric recovery ability will be. The behaviour of hysteresis is the same as for B for knitted textile (Figure 12), i.e. the value is reduced by the use of softener, and prolonged ageing increases the value for viscose but has no influences for PET. It was observed that surface deformation of viscose is much higher than the PET samples (Figures 13 and 14); this is because PET is a resilient and tough fiber. During the initial ageing cycles (up to five cycles) there is a decrease in total deformation (D). After the initial ageing cycles, there was as increase in deformation, this higher deformation may be due to deformation of loose fibers and pills present on the surface of the fabric. The influence of the fabric softener was found to be different on PET and viscose fabric. The surface deformation was enhanced by the use of softener in case of viscose while it was reduced on PET knitted textiles. At present, the origin of these differences is not clear. More work would be needed to resolve this. 0.14 0.12
2HB (gm cm/cm)
0.1 Viscose-without softener Viscose-with softener
0.08
PET-without softener PET- with softener
0.06
Viscose-40A PET-40A
0.04 0.02
Figure 12. Change in 2HB with successive ageing and use of fabric softener
0 1
5
20
40
40A
Number of washing cycles
Ageing
W1
S1
W20
W40
S40
S20
S5
W5
40th
Ageing
S5
W5
S1
S40
S20
40th
W20 W40
W1
Ageing = 5 Without and with softener
PET
With softener
Viscose
Ageing = 1
Ageing = (20,40) With softener
486
Ageing = 1
Ageing = (20,40)
Without softener
Softener only in 40th cycle
With softener
Without softener 327
426 Ageing = 20
Ageing = 40 395
382
404
404
420
452
Total deformation (µm)
Total deformation (µm)
357
Figure 13. Decision tree for total surface deformation of viscose and PET knitted textiles
Ageing = 40 197
247
237 Ageing = 20 295
274
266
296
319
Influence of ageing and softener
500
Total deformation (µm)
450 400
Viscose-without softener Viscose-with softener PET-without softener PET-with softener Viscose-40A PET-40A
350 300 250 200
Figure 14. Total surface deformation of viscose and PET knitted fabrics during their life cycle
150 100 1
5 20 40 Number of washing cycles
165
40A
The level of elastic deformation (ED) was 90-95 per cent in viscose fabrics, but was only 65-73 per cent for PET fabrics (Figure 15). It was observed that ED is mainly determined by fiber type and structure. Ageing and softener do not have significance influence on ED. It was clearly observed that the Ra value for viscose fabric gradually increases with successive ageing cycles (Figure 16). The cause of enhanced Ra is the fibrillation phenomenon, which occurs at the surface of the textiles due to the harsh mechanical action of washing. The fibrils form on the surface and result in strongly tangled form, i.e. lint and pills. The variation in lint and pill height is responsible for increased Ra and Rz of viscose fabrics. The use of fabric softener reduces the Ra and Rz of viscose fabrics (Figures 16 and 17). This can be explained by the fact that the use of softener limits the fibrillation 100
Elastic deformation (µm)
90
Viscose-without softener
80
Viscose-with softener PET-without softener
70
PET-with softener Viscose-40A
60
PET-40A
50
40 1
5
20
40
Number of washing cycles
40A
Figure 15. ED of viscose and PET knitted fabrics during their life cycle
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Viscose-without softener Viscose-with softener
5
PET-without softener PET-with softener
4
Viscose-40A 3
PET-40A
2 1
Figure 16. Ra of viscose and PET knitted textiles during their life cycle
0 1
5
20
40
40A
Number of washing cycles 45 40
Roughness depth (µm)
35 Viscose-without softener
30
Viscose-with softener 25
PET-without softener PET-with softener
20
Viscose-40A 15
PET-40A
10
Figure 17. Rz of viscose and PET knitted textiles during their life cycle
5 0 1
5
20
40
40A
Number of washing cycles
at the surface of fabric. J. Peberdy also reported that cationic fabric softeners limit inter-fibre friction and tapering entanglements of fibres (Peberdy et al., 2008). PET knitted textiles seem to be unaffected during the life cycle of fabrics. Use of softener in the 40th cycle only, reduces Ra for viscose fabrics (i.e. lesser value than the level for 40 cycles without softener) while for PET it results in a higher Rz. This result was unexpected and unexplainable for us.
In this paper, we found that for the softener treated fabrics, value of parameters WC and D is increased while value of Ra was decreased. This may be due to the fact that in the case of WC and D a certain amount of force is applied, which causes the change in thickness. This change in thickness will be greater for softener treated fabrics because of boundary lubrication of the fibres, which reduces the inter-fibre friction forces. While Ra is measured without any load on the surface and gives information about the surface of the fabric. The observed changed may be due to reduced fibrillation at the surface of the fabric, which provides a smoother surface and hence a reduced value of Ra.
Influence of ageing and softener 167
Conclusions On the basis of (1) and (2) influence values mw and ms were calculated and can be divided in four categories: (1) Drastic changes (^ ^ ^ ): jmw/msj $ 30 per cent. (2) Significant changes (^ ^ ): 10 per cent # jmw/msj # 30 per cent. (3) Slight changes (^): 5 per cent # jmw/msj # 10 per cent. (4) No change (0): 5 per cent # jmw/msj # 0 per cent. Note: Sign (^ ) has to be considered for the direction of the change. The summary of influence of ageing and use of fabric softener on mechanical properties of knitted textiles is given in Table III. It can be noticed from Table III that
EMT RT WC RC G HG B HB Drape D ED Ra Rz
Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET Viscose PET
Ageing
Softener
22 0 22 2 þþþ 2 22 2 þþ 0 þþ þ þþþ 0 þþþ þ þþþ 0 þþ 2 0 0 þþþ 22 þþþ 22
þþ þþ þ þþ þþ þ þ 0 22 22 0 22 22 22 22 22 22 2 þþ 22 0 0 22 0 22 0
Table III. Influence of ageing and use of fabric softener on mechanical properties
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in the case of viscose fabrics there are drastic changes in WC, B HB, Ra and Rz. All of these changes occur because of swelling and surface damage due to the severe mechanical action of the washing machine. It implies that ageing deteriorates apparel by making fabrics more stiff, rough and less full. Use of fabric softener diminished the influence of ageing and results in significant changes in EMT, RT, G and B for both PET and viscose fabrics. In this study, we tried to find the level of simultaneous influence of ageing and the use of fabrics softener on different mechanical parameters. These mechanical parameters or the combination of them is representative of the fabric handle or sensory perception (softness, smoothness, etc.) of the user. The authors are looking forward to carry on this work in order to investigate what aspects of the feel or hand of the fabrics change during the life cycle as a result of changes in mechanical parameters. References Anand, S.C., Brown, K.S.M., Higgins, L.G., Holmes, D.A., Hall, M.E. and Conrad, D. (2002), “Effect of laundering on the dimensional stability and distortion of knitted fabrics”, Autex Research Journal, Vol. 2 No. 2, pp. 85-100. Baumert, J.K., Penney, J.C., Carrollton, T. and Crews, C.P. (1996), “Influence of household fabric softeners on properties of selected woven fabrics”, Textile Chemist and Colourist, Vol. 28 No. 4, pp. 36-43. Belinda, T.O., Moore, M.A., Collier, B.J. and Chen, J.Y. (2009), “Effect of laundering on fabric drape, bending and shear”, International Journal of Clothing Science & Technology, Vol. 21 No. 1, pp. 44-55. Breiman, L., Friedman, J., Olshen, R. and Stone, C. (1984), CART: Classification and Regression Trees, Wadsworth International, Monterey, CA. Chiweshe, A. and Crews, C.P. (2000), “Influence of household fabric softners and laundery enzymes on pilling and breaking strength”, Textile Chemist and Colorist and American Dyestuff Reporter, Vol. 32 No. 9, pp. 41-7. Daukantien, V., Bernotiene, B. and Gutauskas, M. (2005), “Textile hand: the influence of multiplex washing and chemical liquid softener”, Fibers and Textiles in Eastern Europe, Vol. 13 No. 3, pp. 63-6. Fijan, S., Sonja, S.-T. and Branko, N. (2007), “The influence of industrial laundering of hospital textiles on the properties of cotton fabrics”, Textile Research Journal, Vol. 77, pp. 247-55. Higgins, L., Anand, S.C., Holmes, D.A., Hall, M.E. and Underly, K. (2003a), “Effects of various home laundering practices on the dimensional stability wrinkling, and other properties of plain woven cotton fabrics: part 1: experimental overview, reproducibility of results and effect of detergent”, Textile Research Journal, Vol. 73 No. 4, pp. 357-66. Higgins, L., Anand, S.C., Holmes, D.A., Hall, M.E. and Underly, K. (2003b), “Effects of various home laundering practices on the dimensional stability wrinkling, and other properties of plain woven cotton fabrics: part 2: effect of rinse cycle softener and drying method and of tumble sheet softener and tumble drying method”, Textile Research Journal, Vol. 73 No. 5, pp. 407-20. Mackay, C., Anand, S.C. and Bishop, D.P. (1999), “Effects of laundering on the sensory and mechanical properties of 1 £ 1 rib knitwear fabrics: part 2: changes in sensory and mechanical properties”, Textile Research Journal, Vol. 69 No. 4, pp. 252-60. Masataka, T. (2010), “Kansei impression analysis using fuzzy C4.5 decision tree”, paper presented at Kansei Engineering and Emotion Research International Conference, KEER-2010, Paris, March 2-4.
Morris, A.M. (1970), “Laundering cotton fabrics: part II: effect of detergent type and water temperature on appearance, hand, strength, and cost”, Textile Research Journal, Vol. 40, pp. 644-9. Morton, W.E. and Hearle, J.W.S. (1962), “Physical properties of textile fiber”, The Textile Institute, Butterworths, London, pp. 215-16. Mukhopadhyay, M.S. and Karmakar, A.K. (2004), “Impact of laundering on the seam tensile properties of suiting fabric”, International Journal of Clothing Science & Technology, Vol. 16 No. 4, pp. 394-403. Peberdy, J., Marty, J.-P., Pons-guiraud, A., Laverdet, C., Martin, L. and Berthod, D. (2008), “Les adoucissants textiles: pourquoi faut-il les utiliser, en particulier quand on a une peau sensible, voire atopique?”, Les Nouvelles Dermatologiques, Vol. 27, pp. 221-6. Quaynor, L., Takahashi, M. and Nakajima, M. (2000), “Effects of laundering on the surface properties and dimensional stability of plain knitted fabrics”, Textile Research Journal, Vol. 70 No. 1, pp. 28-35. Ramkumar, S.S., Wood, D.J., Fox, K. and Harlock, S.C. (2003a), “Developing a polymeric human finger sensor to study the frictional properties of textiles: part 1: artificial finger development”, Textile Research Journal, Vol. 73 No. 6, pp. 469-73. Ramkumar, S.S., Wood, D.J., Fox, K. and Harlock, S.C. (2003b), “Developing a polymeric human finger sensor to study the frictional properties of textiles: part 2: experimental results”, Textile Research Journal, Vol. 73 No. 7, pp. 606-10. Sebastian, S.A.R.D., Bailey, A.I., Briscoe, B.J. and Tabor, D. (1986), “Effect of softening agent on yarn pull-out force of a plain weave fabric”, Textile Research Journal, Vol. 56, pp. 604-11. UCAR Mehmet (2003), “Mechanical behvaiour of knitted fabrics under bending and shear deformation”, Turkish Journal of Engineering and Environmental Sciences, Vol. 27, pp. 177-81. Further reading Mackay, C., Anand, S.C. and Bishop, D.P. (1996), “Effects of laundering on the sensory and mechanical properties of 1 £ 1 rib knitwear fabrics: part 1: experimental procedures and fabric dimensional properties”, Textile Research Journal, Vol. 66 No. 3, pp. 151-7. Corresponding author Gaurav Agarwal can be contacted at:
[email protected]
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Influence of ageing and softener 169
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Mesh topology in scanned garment reconstruction Hongyan Liu, Yueqi Zhong and Shanyuan Wang
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College of Textiles, Donghua University, Shanghai, China
Received 2 June 2010 Revised 26 September 2010 Abstract Accepted 26 September 2010 Purpose – The purpose of this paper is to investigate the draping behavior of a scanned garment
model in irregular and regular mesh topology. 3D garment with high fidelity can be obtained via range data scanning. The original output of a body scanner is an unorganized points cloud. In this paper, the geometrical surface of 3D garment is reconstructed through a series of treatments. Design/methodology/approach – The primary target of this work is to investigate the dynamic behavior of the corresponding physical model transferred from different mesh topologies. A mass-spring model is constructed for both regular and irregular meshes. The performance under various integration methods is evaluated. Findings – Experimental results reveal the procedure of regularization is suitable for the integrators that are sensitive to the physically-based simulation of scanned garments. Originality/value – The geometrical surface of 3D garment is reconstructed through a series of treatments solving the problem of points cloud data for high definition 3D data. Keywords Topology, Meshes, Strain measurement, Clothing Paper type Research paper
Introduction For the implementation of virtual reality or virtual environment, there are two different methods in forming the 3D garment. The first one is to mimic the manufacturing of a real garment, i.e. to form the 3D garment via virtual sewing. The second one is to engage a full body scanning to acquire the points cloud followed by surface reconstruction. The major limitation of virtual sewing is that the patterns of the desired garment have to be known beforehand. The 3D configuration of this approach usually demonstrates a cloth-like appearance comparing to the real garment. Hence, this method is not the best candidate for the implementations where high fidelity is concerned. Recently, using whole body scanner to obtain the geometrical shape of the garment has attracted more and more attention. The major challenge is how to reuse the scanned subject, since they are the reflection of a specific origin. A possible solution is to assign physical behavior to the geometrical model. In this paper, we investigate such behavior under various mesh topologies to find out the optimal pipeline in preparing the corresponding physical model. Previous work The technology involved in virtual sewing and draping is generally regarded as physically-based method. Among which, continuum approach (Eischen et al., 1996; International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 170-183 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107351
This work was supported by Natural Science Foundation of China (Grant no. 60703098, Grant no. 60973072); Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP) (Grant no. 20070255003); and Foundation of Donghua University for Phd. Candidates (Grant no. BC200918).
Feynman, 1986; Terzopoulos and Fleischer, 1988a, b; Terzopoulos et al., 1987; Volino and Magnenat-Thalmann, 1995) and particle-based approach (Baraff and Witkin, 1998; Breen et al., 1994; Eberhardt and Weber, 1997; Eberhardt et al., 1996; Provot, 1995; Volino and Magnenat-Thalmann, 1997) are often referred. Feynman’s model (Feynman, 1986) for generating the appearance of cloth is one of the earliest works. By regarding the cloth object as elastic plate, the final drape was computed by finding the minimum value of the energy equation. In the work of Terzopoulos et al. (1987), the cloth object was also represented as an elastic object. However, this method suffers from instability problem that decreases overall performance. The first milestone of non-continuum approach was set by Breen et al. (1994) in their famous particle-based model to predict the draping behavior of woven cloth. The cloth object was represented as an interlaced particle system. The method was devised to achieve the final equilibrium state of specific materials. Energy minimization was also employed to find the equilibrium position. The drawback of this method is that it cannot produce transitions between the initial state and the final equilibrium. Years later, House et al. (1996) extended this model with force-based techniques, which was very similar with the most popular mass-spring model proposed by Provot (1995). Actually, the major contribution of Provot is his attempt to describe the rigid behavior of cloth with a position adjustment method to overcome the super-elasticity, which is a hot topic in many physically-based methods (Bergou et al., 2008; Bridson et al., 2002; English and Bridson, 2008; Goldenthal et al., 2007; Hong et al., 2005; Mu¨ller, 2008; Mu¨ller et al., 2006; Thomaszewski et al., 2009; Tsiknis, 2006; Vassilev, 2000; Vassilev et al., 2001). Eberhardt et al. (1996) expanded the particle-based model by incorporating hysteresis and creases to create a dynamic simulation method based on a Lagrangian formulation. Baraff and Witkin (1998) used a continuum approach on each triangle for in-plane deformation and the angle between adjacent triangles to measure out-of-plane deformation, their implicit integration scheme was the most advocated method in recent years. Geometrical methods are generally employed in constructing the surface model from a scanned points cloud. The raw data of points cloud usually contain holes and noises, which need to be repaired through various approaches. A thoroughly review on this topic can be found in Weyrich et al. (2004). When connect these techniques with physically-based modeling, meshing is of great importance in both continuum modeling and particle-based modeling, since they all need to be discretized for numerical computation. Technically, the improvement of mesh quality in terms of vertex sampling, regularity, and triangulation is called remeshing. According to Alliez and Gotsman (2003), remeshing techniques could be classified into five categories: structured remeshing, compatible remeshing, high quality remeshing, feature remeshing, and error-driven remeshing. The scanned 3D model usually demonstrates an unstructured or irregular configuration. Hence, the geometrical treatment on this type of problem is usually targeted in acquiring a smooth and refined mesh subdivision. Semi-regular or subdivision connectivity meshes offer many advantages over the irregular setting for downstream implementations. In the past decade, a variety of remeshing techniques were proposed for transforming input irregular meshes into semi-regular and/or regular meshes. According to the way of finding correspondences between the input and output meshes, remeshing can be categorized into two classes. The first class uses a parameterization to find bijective correspondence, which typically relies on establishing a parameterization of the input shape onto a base domain (Eck et al., 1995; Gu et al., 2002; Guskov et al., 2000; Lee et al., 1998; Praun and Hoppe, 2003).
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This method yields excellent results while being sensitive to the patch structure. Recently, some global parameterization methods have been introduced with the goal of building “nice” parameterization not only within each regular patch, but also across patch boundaries and corners. The “niceness” of parameterization is evaluated based on its smoothness or distortion metric (Khodakovsky et al., 2003; Sander et al., 2002; Schreiner et al., 2004). The main drawbacks of the global parameterization methods are the sensitivity to the specific parameterization used and the metric distortion that may arise. The second class of techniques uses ray shooting (Kobbelt et al., 1999) to find correspondences. Semi-regular meshes are obtained by recursive subdivision of an initial base mesh. The first and most popular subdivision surface schemes, introduced by Doo and Sabin (1978) and Catmull and Clark (1978), were based on quadrilateral meshes possessing C1 and C2 continuity, respectively. Loop (1987) introduced a simplest triangular scheme possessing tangent plane smooth surfaces. The mid-point subdivision scheme was proposed independently by Peters and Reif (1997) and Habib and Warren (1999). The former used the mid-point of each edge to build the new mesh. The latter used a four-directional box spline to build the scheme. This scheme generates C1 continuous limit surfaces on initial meshes with arbitrary topology. Midpoint subdivision (Attene and Falcidieno, 2006) split all the edges at their middle points. The geometry of the mesh does not change but the number of triangles is quadruplicated. Loop subdivision (Loop, 1987) splits one triangle into four triangles, adding new vertices in the middle of each edge. Attene et al. (2005) proposed a modified Butterfly scheme in which both boundaries and sharp edges were treated properly. It was implemented by finding mid-points for each edge of a triangle. The mid-points are calculated by finding the midpoint of the edge and adjusting it by its neighbour in the butterfly mask. The main target of this paper is to investigate the performance of a scanned garment model transferred to a physically-based model with various mesh topologies and numerical integrators (i.e. the ODE solvers) to find out the optimum when “manufacturing” the 3D garment via ranged scanned data. Algorithms Physical model of garment The present work employs a mass-spring system (Provot, 1995) for garments based on triangular mesh. Each vertex is considered as a mass and the triangle edges are considered as the springs. The stretching and shearing resistance is enforced by applying the spring force along each edge: f ¼ f i þ d i ¼ 2k
›CðxÞ ›CðxÞ _ CðxÞ 2 kd CðxÞ ›x i ›x i
ð1Þ
where fi and di are the elastic force and damping force applied onto ith mass. C is the conditional function. By defining C ¼ jx ij j 2 L, we have: 8 x < ks ðjx ij j 2 LÞ jx ijij j : jx ij j $ L fi ¼ : 0 : jx ij j , L where x ij ¼ x j 2 x i , L is the rest length between ith and jth masses.
The bending resistance (Figure 1) is enforced by resisting the rotation among two adjacent triangles who shares the same edge. As illuminated by the work of Bridson et al. (2003):
Mesh topology
2
f ¼ fei þ fdi ¼ ke u 1 ¼ j Ej u 2 ¼ j Ej
N1 2
jN 1 j N2
jEj ðsinðu=2ÞÞu i 2 kd jEjðu^uÞv; jN 1 j þ jN 2 j ;
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; 2 jN 2 j ðx 1 2 x 4 Þ · E N 1 ðx 2 2 x 4 Þ · E N 2 þ ; u3 ¼ 2 2 jEj jEj jN 1 j jN 2 j ðx 1 2 x 3 Þ · E N 1 ðx 2 2 x 3 Þ · E N 2 2 u4 ¼ 2 2 2 jEj jEj jN 1 j jN 2 j where i ¼ 1,2,3,4, u ¼ ðu 1 ; u 2 ; u 3 ; u 4 Þ represent motion mode that changes the dihedral angle but does not cause any in-plane deformation or rigid body motion. fei and fdi denotes elastic and damping bending forces, respectively. ke and kd is the elastic bending stiffness and material property separately: N 1 ¼ ðx 1 2 x 3 Þ £ ðx 1 2 x 4 Þ N 2 ¼ ðx 2 2 x 4 Þ £ ðx 2 2 x 3 Þ N 1 and N 2 is the area weighted normal, E ¼ x 4 2 x 3 is the common edge. Numerical integrator In our approach, the numerical methods of solving the ordinary differential equations (ODE) include Euler, Midpoint, RK4, Verlet, and Velocity Verlet (also called Leapfrog method). The criterion of selecting integrators is their popularity for real-time simulation. A straight-forward approach of Euler method is given by: ( v nþ1 ¼ v n þ ha n x nþ1 ¼ x n þ hv nþ1 ; where x nþ1 , v nþ1 denotes vector of position and velocity, respectively, at the end of the time step h. x n , v n are initial vectors of position and velocity of the time step.
e n1
P4
n1 n2
q
n2
P3
P1
P2
Figure 1. Model of bending resistance
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a n represents vector of acceleration at the beginning of the time step. Midpoint integration method is expressed as: 8 k 1 ¼ f ðtn ; x n Þ > > < k 2 ¼ f tn þ h2 ; x n þ h2 k 1 : > > : x nþ1 ¼ x n þ hk 2 RK4 integration method is comprised of: 8 k 1 ¼ f tn ; x n > > > > > > > k 2 ¼ f tn þ 12 h; x n þ 12 hk 1 > > < k 3 ¼ f tn þ 12 h; x n þ 12 hk 2 : > > > > k 4 ¼ f tn þ h; x n þ hk 3 > > > > > : x nþ1 ¼ x n þ 16 hðk 1 þ 2k 2 þ 2k 3 þ k 4 Þ The basic Verlet integration is in the style of: xnþ1 ¼ 2xn 2 xn21 þ h 2i x€ n ; i.e. the velocity is not shown and is expressed in an implicit way. And the Velocity Verlet approach is represented by: 8 > v nþ1=2 ¼ v n þ h2 a i > > < x nþ1 ¼ x n þ hv nþ1=2 > > > : v nþ1 ¼ v nþ1=2 þ h2 a iþ1 ; where the velocity is computed explicitly. In between the position calculation and velocity caculation, the forces are recomputed to get a iþ1 . Strain control scheme To prevent the garment model from over-elongation or over-compression, strain control is an inevitable procedure in the physically-based modeling. Position adjustment (Provot, 1995) and velocity adjustment (Bridson et al., 2002) are selected as the candidates to maintain the size stability of the garment model. Position adjustment rectifies the positions of the masses to set them at a specific distance (for instance, the rest length of a spring, or under a given threshold, depending on the property of the material). Velocity adjustment changes the initial velocity of each mass to ensure by the end of each time step, the updated position of each mass will maintain the size stability. A major concern on the selection of strain control scheme is its capacity to be combined with the collision detection/response procedure. In most physically-based garment simulations, the simulation can be expressed as: . solve the internal/external forces; . update the position and velocity (if it has) with a selected integrator; and . satisfy various constraints.
For a particle-based simulation, the constraint is usually the size stability (strain control) and colliding/penetration avoiding. To meet both, iterations are inevitable for convergence. This equals to consecutively satisfy various local constraints and then repeating. If the conditions are right, this will converge to a global configuration that satisfies all constraints at the same time:
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Algorithm 1 Position adjustment Input:
x 1 ,x 2 ,l 0
Step 1:
integrate system over time
Step 2:
while the strain of the current spring exceeds a given threshold tmax do if two ends are loose ¼ x mid 2 0:5Dl; xnew ¼ x mid þ 0:5Dl xnew 1 2 if one end is fixed xnew ¼ x 2 2 Dl 1
Step 3:
move the two ends to new position xnew and xnew 1 2 .
Algorithm 2 Velocity adjustment Input:
x1, x2, v1v2, l0
Step 1:
Pre-compute the xcandidate and xcandidate via a given integrator. 1 2
Step 2:
while strain of spring exceeds threshold tmax do if two ends are loose 2 0:5Dl 0:5 xcandidate 2 xcandidate 2 1 new v1 ¼ v 1 þ h 0:5 xcandidate 2 xcandidate þ 0:5Dl 1 2 ¼ v þ vnew 2 2 h if one end is fixed ¼ vnew 1
Mesh topology
x 2 2 Dl 2 xcandidate 1 þ v1 h
Step 3:
change v 1 and v 2 to the new velocities vnew and vnew 1 2 .
Step 4:
integrate system over time with new velocity.
In Algorithms 1 and 2, x 1 , x 2 , v 1 v 2 are the positions and velocities of the two ends of a spring at the beginning of the time step. l 0 is the rest length of this spring. x mid is the and xnew are the new position of the two ends of the spring being midpoint. xnew 1 1 adjusted. Dl is defined as:
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xcandidate 2 xcandidate 2 1 Dl ¼ l 0 ð1 ^ tmax Þ xcandidate 2 xcandidate : 2
1
xcandidate and xcandidate are the candidate position computed according to current 1 2 new and V are the new velocity adjusted according to the maximum velocity. Vnew 1 2 strain. Obviously, to meet the aforementioned constraints, the strain control in Verlet integration can only be enforced by position adjustment scheme. Surface reconstruction The raw data of range scanned garment model is usually stored as a points cloud. A major concern of this paper is to investigate the optimized way to recover the triangulated surface from a given points cloud. The pipeline is designed as shown in Figure 2. The initial surface reconstruction is usually the first step of geometrical modeling. The mesh density at this stage is commonly over one million triangles. The simplification procedure is to reduce the heavy trunk of data to reach a balance between efficiency and fidelity. In our approach, the mesh density after simplification at this stage is around 15,000 triangles. The following mesh regularization is mainly served as a pre-processing for a better physical behavior, once the geometrical model has been transferred into a mass-spring system. The remeshing after simplification is performed in the following manner: Step 1. Irregular mesh is treated with Loop subdivision to create a smoother surface. Step 2. The surface is simplified to 10,000 triangles where the shape error is controlled by using the quadric error matrices introduced by Garland and Heckbert (1998). Step 3. The simplified mesh is regulated via isotropic remeshing. Say for a vertex in a triangle mesh, if its valence (number of neighboring vertices) is six for interior vertices or four for boundary vertices, then it is called regular. We use the method proposed in (Botsch et al., 2008) to reach a uniform target edge length L while maintain the original shape. Once L has been specified, the iterations follow:
Figure 2. The pipeline of surface reconstruction
Raw data→Noise removing→Initial surface reconstruction→Simplification→Mesh regularization
.
Lmax ¼ .
Mesh topology
Split edges longer than edges (Figure 3): 4 L: 3
Collapse edges shorter than edges: Lmin ¼
4 L: 5
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As explained in (Botsch et al., 2008), by collapsing along chains of short edges, the algorithm may create new edges that are arbitrarily long and thus undo the work that was done in Step 3 first point. This can be resolved by testing before each collapse whether the collapse would produce an edge that is longer than high. If so, the collapse is not executed (Figure 4): . Flip edges to get closer to valence edges 6. This step tentatively flips each edge and checks whether the deviation to the target valences decreases. If not, the edge is flipped back (Figure 5): . Vertex shift by tangential relaxation (Figure 6). The tangential relaxation applies an iterative smoothing filter to the mesh. Here, the vertex movement has to be constrained to the vertex’ tangent plane in order to stabilize the following projection operator. Let p be an arbitrary vertex in the current mesh, let n be its normal, and let q be the position of the vertex as calculated by Laplacian smoothing. The new position p0 of p is then computed by projecting q onto p’s tangent plane: p0 ¼ q þ nn T p 2 q : .
Project vertices back to the surface.
Notice that the proper thresholds 4/5 and 4/3 are essential to converge to a uniform edge length (Botsch and Kobbelt, 2004).
Lmax
Figure 3. Edge split
Lmin
Figure 4. Edge collapse
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Figure 5. Edge flip
Figure 6. Vertex shift
Step 4. Now the meshes can be simplified to a target mesh density by repeating Steps 2 and 3. For instance, if we want a mesh density at n, we would simplify the 10,000 triangles to n triangles and then remeshing it uniformly. Experimental results and discussion In our implementation, a scanned skirt is employed as an example to validate our methods. All the experiments are conducted on a PC with a 1.61 GHz CPU and 2.00 GB physical memory. The first test is the comparison of visual effect between regular meshes and irregular meshes. As shown in Figure 7, although the overall appearance after shading is similar, the regular meshes are visually smoother than that of the irregular meshes. Obviously, if the mass-spring system is directly converted from these triangles, and the Hook constants are set to a unique value for each spring, the intrinsic physical unevenness in the irregular meshes will be greater than that of the regular ones. Although higher mesh density implies better fidelity of the 3D appearance, it is not uncommon that a physically-based approach may require a best mesh density to satisfy both the visual effects and the cost of computation. To find out the answer, virtual re-draping with strain control can be initiated under various mesh density. Using the scanned skirt as an example, the waist area is fixed to make sure the skirt can be draped under its own weight. Figure 8 depicts the visual effects and the computation cost when the mesh density is increased from 2,000 to 10,000. From our experience, it is necessary to perform this test before “manufacturing” the virtual garment. It is observed that 4,000 vertices in the garment model can meet the demand of visual realism. Since the stability and the speed of numerical integration is the key of a physically-based simulation, the performance related to these two behaviors under different integration methods are compared. To clarify the explanation, we define “strain” as:
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Figure 7. Mesh topology: irregular (red) and regular (blue)
FPS (frames per second)
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
2,000 vertices 3,000 vertices 4,000 vertices 5,000 vertices 6,000 vertices 7,000 vertices 8,000 vertices 9,000 vertices 10,000 vertices
65 60 55 50 45 40 35 30 25 20 15 10 5 0
Visual difference between 4,000 and 10,000 triangles (projection view) 0
500
1,000 Steps
1,500
2,000
tl ¼
l 2 l0 l0
where lis current length of the target, l 0 represents the original length of the target. In our approach, the term “target” can be referred to as a garment, a single spring or a single triangle, respectively. However, the strain of a garment is more noticeable. Therefore, it is adopted as an index to analyze the simulated results in the following discussions. The threshold of strain control in this experiment is set to 0.01. The performances of both irregular and regular mesh with velocity adjustment are shown in Figure 9. Observing that the strain in irregular mesh is 2 percent while in regular mesh, it is confined by 1 percent. This implies the regular mesh is better than
Figure 8. The visual difference and computational cost of the same skirt
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irregular mesh in maintaining the size stability. To further investigate the behavior of different integrators for an optimized combination, the speed test has been performed, as shown in Figure 10 (position adjustment) and Figure 11 (velocity adjustment). It is observed that in both strain control schemes, the basic Verlet method is the fastest, followed by Euler, Velocity Verlet, Midpoint, and RK4, respectively. This implies not only Verlet integration can be used to calculate trajectories of particles in molecular dynamics simulations, but also suitable for garment simulation. 0.020
0.010 Euler Midpoint RK4 Velocity verlet
Figure 9. Strain control under velocity adjustment in irregular(left) and regular(right) mesh
0.014 0.012
0.006 0.004 0.002
0.010
0.000 0
500
1,000 1,500 2,000 Steps
Figure 10. The speed of simulation with different integration methods (position adjustment)
0
Euler Midpoint RK4 Verlet
50 40 30 20 10 0
FPS (frames per second)
500
60
500
1,000 1,500 2,000 Steps
60
Figure 11. The speed of simulation with different integration methods (velocity adjustment)
Euler Midpoint RK4 Velocity verlet
0.008
Strain
0.016
FPS (frames per second)
Strain
0.018
Euler Midpoint RK4 Velocity verlet
50 40 30 20 10 0 0
500
1,000 Steps
1,500
2,000
1,000 1,500 2,000 Steps
Although the Velocity Verlet is in the third place of the speed, it is more stable than Euler and more accurate than the basic Verlet. If the implementation context demands accuracy over speed, Velocity Verlet might be the best candidate. Conclusions In this paper, the draping behavior of scanned garment model in irregular and regular mesh topology has been investigated. The best mesh density has been determined through experiments. After testing corresponding physical behavior of irregular and regular mesh, it is concluded that regular mesh is better than irregular mesh. Various integration methods have been tested under regular meshing. Considering from the performance and speed, Verlet integration with position adjustment is the fastest approach. Observed from the experimental results, the suitable candidate of “manufacturing” virtual garment from range scanned data is through regularization combined with Verlet integration or Velocity Verlet integration. References Alliez, P. and Gotsman, C. (2003), “Recent advances in compression of 3D meshes”, Proceedings of the Symposium on Multiresolution in Geometric Modeling. Attene, M. and Falcidieno, B. (2006), “Remesh: an interactive environment to edit and repair triangle meshes”, Proceedings of Shape Modelling International (SMI’ 06), IEEE Computer Society Press, Silver Spring, MD, pp. 271-6. Attene, M., Falcidieno, B., Rossignac, J. and Spagnuolo, M. (2005), “Sharpen&Bend: recovering curved sharp edges in triangle meshes produced by feature-insensitive sampling”, IEEE Transactions on Visualization and Computer Graphics, Vol. 11 No. 2, pp. 181-92. Baraff, D. and Witkin, A. (1998), “Large steps in cloth simulation”, Computer Graphics, Vol. 32, pp. 43-54 (Annual Conference Series). Bergou, M., Wardetzky, M., Robinson, S., Audoly, B. and Grinspun, E. (2008), “Discrete elastic rods”, SIGGRAPH (ACM Transactions on Graphics), Vol. 27 No. 3, pp. 1-12. Botsch, M. and Kobbelt, L. (2004), “A remeshing approach to multiresolution modeling”, Proceedings of Eurographics Symposium on Geometry Processing, New York, NY, ACM Press, New York, NY, pp. 185-92. Botsch, M., Pauly, M., Kobbelt, L., Alliez, P., Levy, B., Bischoff, S. and Ro¨ssl, C. (2008), “Geometric modeling based on polygonal meshes”, Eurographics 2008 Course Notes. Breen, D.E., House, D.H. and Wozny, M.J. (1994), “Predicting the drape of woven cloth using interacting particles”, Proceedings of ACM SIGGRAPH, ACM Press/ACM SIGGRAPH, New York, NY, pp. 365-72. Bridson, R., Fedkiw, R. and Anderson, J. (2002), “Robust treatment of collisions, contact and friction for cloth animation”, ACM Transactions on Graphics, Vol. 21 No. 3, pp. 594-603. Bridson, R., Marino, S. and Fedkiw, R. (2003), Simulation of Clothing with Folds and Wrinkles, Eurographics Association Aire-la-Ville, Switzerland, Switzerland, pp. 28-36. Catmull, E. and Clark, J. (1978), “Recursively generated B-spline surfaces on arbitrary topological meshes”, Computer-Aided Design, Vol. 10, pp. 350-5. Doo, D. and Sabin, M. (1978), “Behavior of recursive division surfaces near extraordinary points”, Computer-Aided Design, Vol. 10 No. 6, pp. 356-60. Eberhardt, B. and Weber, A. (1997), “Modeling the draping behavior of woven cloth”, Maple Tech, Vol. 4 No. 2, pp. 25-31.
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Eberhardt, B., Weber, A. and Strasser, W. (1996), “A fast, flexible, particle-system model for cloth draping”, IEEE Computer Graphics and Applications, Vol. 16 No. 5, pp. 52-9. Eck, M., DeRose, T., Duchamp, T., Hoppe, H., Lounsbery, M. and Stuetzle, W. (1995), “Multiresolution analysis of arbitrary meshes”, Proceedings of SIGGRAPH, pp. 173-82. Eischen, J.W., Deng, S.G. and Clapp, T.G. (1996), “Finite-element modeling and control of flexible fabric parts”, IEEE Computer Graphics and Applications, Vol. 16 No. 5, pp. 71-80. English, E. and Bridson, R. (2008), “Animating developable surfaces using nonconforming elements”, ACM Transactions on Graphics (TOG), Vol. 27 No. 3, pp. 1-5. Feynman, C. (1986), Modeling the Appearance of Cloth, Institute of Technology, Cambridge, MA. Garland, M. and Heckbert, P.S. (1998), Surface Simplification Using Quadric Error Metrics, Carnegie Mellon University, Pittsburgh, PA. Goldenthal, R., Harmon, D., Fattal, R., Bercovier, M. and Grinspun, E. (2007), “Efficient simulation of inextensible cloth”, ACM Transactions on Graphics, Vol. 26 No. 3, p. 7. Gu, X., Gortler, S.J. and Hoppe, H. (2002), “Geometry images”, SIGGRAPH Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques, pp. 355-61. Guskov, I., Vidimcˇe, K., Sweldens, W. and Schro¨der, P. (2000), “Normal meshes”, Proceedings of SIGGRAPH, pp. 95-102. Habib, A. and Warren, J. (1999), “Edge and vertex insertion for a class of C1 subdivision surfaces”, Computer Aided Geometric Design, Vol. 16 No. 4, pp. 223-47. Hong, M., Choi, M.-H., Jung, S., Welch, S. and Trapp, J. (2005), “Effective constrained dynamic simulation using implicit constraint enforcement”, Robotics and Automation, pp. 4520-5. House, D.H., DeVaul, R.W. and Breen, D.E. (1996), “Towards simulating cloth dynamics using interacting particles”, International Journal of Clothing Science & Technology, Vol. 8 No. 3, pp. 75-94. Khodakovsky, A., Litke, N. and Schro¨der, P. (2003), “Globally smooth parameterizations with low distortion”, Proceedings of SIGGRAPH, pp. 350-7. Kobbelt, L., Vorsatz, J., Labsik, U. and Seidel, H.P. (1999), “A shrink wrapping approach to remeshing polygonal surfaces”, Citeseer, pp. 119-30. Lee, A.W.F., Sweldens, W., Schro¨der, P., Cowsar, L. and Dobkin, D. (1998), “Maps: multiresolution adaptive parameterization of surfaces”, Proceedings of SIGGRAPH, pp. 95-104. Loop, C. (1987), “Smooth subdivision surfaces based on triangles”, Master’s thesis, University of Utah, Salt Lake City, UT. Mu¨ller, M. (2008), “Hierarchical position based dynamics”, Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS), pp. 1-10. Mu¨ller, M., Heidelberger, B., Hennix, M. and Ratcliff, J. (2006), “Position based dynamics”, Virtual Reality Interactions and Physical Simulation(VRIPHYS), Vol. 18 No. 2, pp. 71-80. Peters, J. and Reif, U. (1997), “The simplest subdivision scheme for smoothing polyhedra”, ACM Transactions on Graphics, Vol. 16 No. 4, pp. 420-31. Praun, E. and Hoppe, H. (2003), “Spherical parametrization and remeshing”, ACM Transactions on Graphics, pp. 340-9. Provot, X. (1995), “Deformation constraints in a mass-spring model to describe rigid cloth behavior”, Graphics Interface, pp. 147-54. Sander, P.V., Gortler, S.J., Snyder, J. and Hoppe, H. (2002), “Signal-specialized parametrization”, EGRW Proceedings of the 13th Eurographics Workshop on Rendering, pp. 87-98.
Schreiner, J., Asirvatham, A., Praun, E. and Hoppe, H. (2004), “Inter-surface mapping”, ACM Transactions on Graphics, pp. 870-7. Terzopoulos, D. and Fleischer, K. (1988a), “Deformable models”, The Visual Computer, Vol. 6 No. 4, pp. 306-31. Terzopoulos, D. and Fleischer, K. (1988b), “Modeling inelastic deformation: viscoelasticity, plasticity, fracture”, Computer Graphics, Vol. 22 No. 4, pp. 269-78. Terzopoulos, D., Platt, J., Barr, A. and Fleischer, K. (1987), “Elastically deformable models”, Computer Graphics Forum, Vol. 21 No. 4, pp. 205-14. Thomaszewski, B., Pabst, S. and Strasser, W. (2009), “Continuum-based strain limiting”, Computer Graphics Forum Proceedings of Eurographics, Vol. 28 No. 2, pp. 569-76. Tsiknis, K.D. (2006), “Better cloth through unbiased strain limiting and physics-aware subdivision”, Master’s thesis, The University of British Columbia, Vancouver. Vassilev, T.I. (2000), “Dressing virtual people”, SCI&apos, pp. 23-6. Vassilev, T.I., Spanlang, B. and Chrysanthou, Y. (2001), “Efficient cloth model and collision detection for dressing virtual people”, Proceeding of ACM/EG games technology Conference, GeTech, Hong Kong. Volino, P. and Magnenat-Thalmann, N. (1995), “Versatile and efficient techniques for simulating cloth and other deformable objects”, Computer Graphics Proceedings, Annual Conference Series, SIGGRAPH, pp. 137-44. Volino, P. and Magnenat-Thalmann, N. (1997), “Developing simulation techniques for an interactive clothing system”, Proceedings of the 1997 International Conferene on Virtual Systems and Multi Media, pp. 109-18. Weyrich, T., Pauly, M., Keiser, R., Heinzle, S., Scandella, S. and Gross, M. (2004), “Post-processing of scanned 3D surface data”, Citeseer, pp. 85-94. Corresponding author Yueqi Zhong can be contacted at:
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Validation of clothing insulation estimated by global and serial methods
184
Joo-Young Lee
Received 22 June 2010 Accepted 12 September 2010
Department of Ergonomics, Faculty of Design, Kyushu University, Fukuoka, Japan, and
Eun-Sook Ko, Hyo-Hyun Lee, Jae-Young Kim and Jeong-Wha Choi Department of Clothing & Textiles, College of Human Ecology, Seoul National University, Seoul, South Korea Abstract Purpose – The purpose of this paper is to examine differences between thermal insulation calculated by a global and a serial method using a thermal manikin, in comparison with human trials. Design/methodology/approach – A total of 150 single garments and 38 clothing ensembles were assessed using the manikin; 26 seasonal clothing ensembles were selected for human trials. Findings – The results showed that total insulation of single garments was 16 percent higher in the serial method than in the global method. The difference was higher in garments with smaller covering area per unit garment mass (e.g. winter garments). For seasonal clothing ensembles, the serial values were 39.2 percent (0.18 clo) for spring/fall wear, 62.6 percent (0.15 clo) for summer wear and for winter wear 64.8 percent (0.69 clo) greater than the global values. The clothing insulation by the global method was systemically lower in all 26 seasonal ensembles than values by human trials, which suggests that the values by the global calculation can be more accurately corrected with human testing data. Originality/value – The paper shows that values by the serial calculation were lower in spring/fall and summer ensembles but greater in winter garments than values collated by human trials. It suggests that the serial values had a lower validity when compared with thermal insulation values collated from human trials. Keywords Clothing, Thermal properties of materials, Thermal insulation Paper type Research paper
Introduction Since the unit of clothing insulation “clo” was coined by Gagge et al. (1941), thermal manikins have developed in sophistication. As thermal manikins have evolved from a one segment model to models with more than 30 individually heated segments (Holme´r, 2004), the spatial resolution measuring heat exchange has improved. However, these developments have also seen the emergence of distinct methods of calculating thermal insulation; global, parallel, and serial. The term, “parallel method”, has recently been renamed as “global method” to avoid any confusion with an actual parallel model (Havenith, 2005; ISO 9920, 2007; International Journal of Clothing Science and Technology Vol. 23 No. 2/3, 2011 pp. 184-198 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111107360
The authors express their thanks to Drs So-Young Kim, Myung-Ju Kim, and Su-Kyung Hwang for their cooperation, would like to convey special thanks to Professor Yutaka Tochihara for his advice, and Andrew J. Cookson and Shizuka Umezaki for their cordial assistance. This study was supported by the Korea Research Foundation (KRF-2004-041-C00472) and in part by the Japan Society for the Promotion of Science ( JSPS #P09128).
Oliveira et al., 2005, 2008a, b). In the present study, the conventional parallel method is referred to as the global method. In the global method, thermal insulation is obtained by calculating total mean surface temperature and heat flux using all body regional heat fluxes and surface temperatures weighted by area (ISO 9920, 2007). The serial method is based on the summation of local thermal insulation for each body segment assuming that each body segment has its own heat loss and production (ISO 9920, 2007). In the past decade, a number of studies have reported on the differences in global and serial methods used to calculate clothing insulation using manikins. Most studies are in agreement that the values obtained by the serial method are greater than those obtained by the global method (Anttonen, 2001; Holme´r, 2004; Kuklane et al., 2004; Meinander et al., 2004; Oliveira et al., 2008a; Xu et al., 2008). The serial values were 20 percent greater than values obtained by the parallel global method (Anttonen et al., 2004), approximately 14-38 percent greater than the global values (Xu et al., 2008), and 78.4 percent greater for cold protective clothing (Oliveira et al., 2008a). Moreover, it is reported that the difference between serial and global calculations was more significant than differences found in different body shapes (male vs female, adult vs baby manikins) (Kuklane et al., 2004). The difference has been mainly attributed to the uneven distribution of clothing over the body (Anttonen et al., 2004; Kuklane et al., 2007; Meinander, 2004; Nilsson, 1997; Oliveira et al., 2008a). If the manikin is covered with exactly the same level of insulation over all sections, results from the two methods would be the same (Nilsson, 1997). As the thermal regulatory system of the human body is controlled holistically not through individual body compartments, the global method rather than the serial method would be a more realistic representation of the human thermoregulatory system. Despite the serial method overestimating clothing insulation and the non-realistic representation of the human thermoregulatory system, the standards EN 342 (2004) and ISO 15831 (2004) still consider the serial method as a valid calculation method. This may be related to the lack of accumulated data. In the aforementioned studies comparing calculation methods, the total number of clothing ensembles that was employed for the comparison is insufficient, i.e. nine clothing ensembles (Oliveira, 2008a), four types of cold protective clothing ensembles (Anttonen et al., 2004), and eleven clothing ensembles (Xu et al., 2008), respectively. A thermal manikin has been used as an analogous tool of the human body with human-like functions such as sweating, walking, breathing, and multi-layered structures. There now seems to be a general consensus that the serial method generates a significantly greater value than the global values, but the final comparison between calculation methods should be validated in human testing values. Even though the variation in thermal insulation found when measured using identical clothing was greater in human subjects than in thermal manikins (Meinander et al., 2004), the validity of the calculated results should be examined with human testing. While most manikin-testing studies present clothing insulation values using a thermal manikin in the absence of human testing, some have compared clothing insulations through both thermal manikins and human participants (Ducharme et al., 1998; Konarska et al., 2007; Kuklane et al., 2007; Meinander et al., 2004; Nilsson et al., 1998; Sung, 1991). However, there are few reports on the validation of the global and serial methods in human trial-values. Therefore, the purpose of the present study was to investigate the validity of thermal insulations through the global and serial methods in comparison with
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human trials. Further, we aimed to extend the comparison between the global and serial methods to comprehensive daily and seasonal clothing, because most previous research has conducted comparative studies based on a limited number of clothing garments and ensembles. Methods Selection of single garments and clothing ensembles by season As mentioned earlier, the actual number of garments that was employed for the comparison between the global and serial methods is insufficient in previous studies. We surveyed the daily and work clothing through both questionnaires and interviews (825 Korean women) (Choi et al., 2006). Based on the questionnaire survey, a total of 150 single garments were selected evenly for winter, spring/fall, and summer wear (13 underwear, 16 T-shirts, seven blouses, six vests, seven cardigans, 18 Jackets/coats, 23 pants/overalls, two coveralls, 14 skirts/dresses, 15 headwear, four mufflers/scarves, ten gloves, 15 panty hoses/footwear). A total of 38 clothing ensembles were selected (eight ensembles for spring/fall, seven ensembles for summer, and 23 ensembles for winter) from combinations of the 150 single garments for the measurement using a thermal manikin. The 38 clothing ensembles consisted of 43 single garments (Figure 1, Table I). Surface area covered by clothing (covering area, CA, percent BSA) was estimated based on a photographic method, the data from the manikin manufacturing company (Newton, Measurement Technology, NorthWest), and regional body surface area (Lee, 2005; Lee and Choi, 2009). Every garment was weighed three times on an electronic balance (Sartorius Company, Germany, accuracy 1 g) in a dry state. Measurement of dry thermal insulation using a thermal manikin Thermal insulation values of 150 single garments and 38 clothing ensembles were determined using a standing thermal manikin with 20 independently heated thermal zones (Newton, 1.7 m2 of BSA). All zones were fitted with heaters to simulate heat output sk ) of 33.3 ^ 0.58C. Regional surface as to maintain a constant mean skin temperature (T temperatures were set based on the regional skin temperatures of the Korean adults females in thermal comfort (34.48C on the face, 34.58C head, 33.98C Right/Left upper arms, 32.08C R/L forearms, 32.58C R/L hands, 34.58C Chest, 34.78C Shoulders, 35.98C Stomach, 34.78C Back, 32.78C R/L hips, 33.88C R/L Thighs, 31.08C R/L claves, and 32.58C feet). The average values of the regional skin temperature in thermal comfort were obtained from Lee (2005). Air temperature and air humidity in the chamber was set at 21.5 ^ 0.58C and 50 ^ 5 percent RH, respectively. Air speed was limited to 0.1 m s2 1. All measurements were repeated twice or three times for each single garment and each clothing ensemble. The coefficients of variation of the thermal insulation values in the identical ensembles were all under 2 percent. The average was regarded as the thermal insulation of clothing (clo-value). The total clothing insulation (IT) including the insulation of air layer (Ia) around the clothed body was calculated as follows: air sk 2 T T IT ¼ 6:45 ð1Þ ðQAÞ IT
¼ total clothing insulation (clo).
6.45 ¼ constant for converting unit from “8C · m2 W2 1” to “clo”.
Clothing insulation Spring/ Fall No.1~10
187 1 Underwear 2 Underwear 3 Cotton Tee
4 Cotton
5 Underwear
6 Polyester
7 Cotton
Summer No.11~20
8 Translucent 9 Ankle socks
10 Leather
11 Underwear 12 Underwear 13 Cotton Tee 14 Cotton Tee
Winter No.21~36
15 Underwear
16 Cotton
22 Underwear
23 Sweater
17 Cotton
18 Cotton
24 Turtle Tee 25 Cardigan
19 Cotton (2)
20 Sandal
21 Underwear
26 Wool (2) 27 Underwear 28 Underwear 29 Wool (2)
WinterUpper wear No.37~39
30 Wool (2)
31 Opaque
32 Socks
33 Leather
34 Leather (2) 35 Wool (2)
36 Knit hat
Winter Lower wear No.40~43
37 Sweater
38 Sweater
39 Underwear
40 Jean
41 Corduroy 42 Underwear
Note: The number of parenthesis demonstrates the number of layering of garments
43 Leather
Figure 1. Seasonal single garments composing 38 clothing ensembles
Table I. Combinations of single garments composing 38 clothing ensembles by season
Note: aThe numbers of single garments on Figure 1
(11) þ (15 þ 19) þ (20) (11 þ 13) þ (15 þ 17) þ (20) (11 þ 14) þ (15 þ 18) þ (20) (11 þ 14) þ (15 þ 16) þ (20) (11 þ 14) þ (15 þ 17) þ (20) (11 þ 12 þ 14) þ (15 þ 18) þ (20) (11 þ 12 þ 14) þ (15 þ 16) þ (20) WL) (21 þ 38 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 38 þ 26) þ (27 þ 28 þ 29) þ (32 þ 33) (21 þ 22 þ 38 þ 26) þ (27 þ 29) þ (32 þ 33)
(1 þ 3) þ (5 þ 7) þ (9 þ 10) (1 þ 3) þ (5 þ 6) þ (10) (1 þ 2 þ 3) þ (5 þ 7) þ (9 þ 10) (1 þ 3) þ (5 þ 6) þ (8 þ 10) (1 þ 3 þ 4) þ (5 þ 7) þ (9 þ 10) (1 þ 3 þ 4) þ (5 þ 6) þ (10) (1 þ 3 þ 4) þ (5 þ 6) þ (8 þ 10) (1 þ 2 þ 3 þ 4) þ (5 þ 7) þ (8 þ 10)
a
Composition of clothing ensembles
Composition of clothing ensembles
(21 þ 22 þ 38 þ 26) þ (27 þ 28 þ 29) þ (32 þ 33) (21 þ 22 þ 38 þ 25 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 22 þ 38 þ 25 þ 26) þ (27 þ 28 þ 29) þ (32 þ 33) (21 þ 22 þ 24 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 24 þ 25 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 22 þ 38 þ 26) þ (27 þ 30) þ (31 þ 33) (21 þ 22 þ 38 þ 26) þ (27 þ 29) þ (32 þ 33 þ 34 þ 35) (21 þ 22 þ 38 þ 26) þ (27 þ 29) þ (32 þ 33 þ 34 þ 35 þ 36) (21 þ 23 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 38 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 37 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 22 þ 23 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 39 þ 23 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 38 þ 26) þ (27 þ 40) þ (32 þ 33) (21 þ 38 þ 26) þ (27 þ 29) þ (32 þ 33) (21 þ 38 þ 26) þ (27 þ 41) þ (32 þ 33) (21 þ 38 þ 26) þ (27 þ 30) þ (31 þ 43) (21 þ 38 þ 26) þ (27 þ 29) þ (31 þ 33) (21 þ 38 þ 26) þ (27 þ 42 þ 29) þ (32 þ 33) (21 þ 38 þ 26) þ (27 þ 28 þ 29) þ (32 þ 33)
Ensemble Winter (W; WU; WL) W4 W5 W6 W7 W8 W9 W10 W11 WU1 WU2 WU3 WU4 WU5 WL1 WL2 WL3 WL4 WL5 WL6 WL7
188
Spring/Fall (SF) SF1 SF2 SF3 SF4 SF5 SF6 SF7 SF8 Summer (S) S1 S2 S3 S4 S5 S6 S7 Winter (W; WU; W1 W2 W3
Ensemble
IJCST 23,2/3
sk ¼ 20 zones average temperature (8C). T air ¼ ambient average temperature (8C). T A
¼ body surface area (m2).
Q
¼ heat flux (W).
Clothing insulation
Ia fcl
ð2Þ
IT ¼ Icle þ Ia
ð3Þ
IT ¼ Icl þ
Originally, IT includes the effect of the increased surface area (fcl) as shown in equation (2). Icl is a property of the clothing itself and represents the resistance to heat transfer between the skin and the clothing surface (ISO 9920, 2007). Ia is the thermal insulation of air layer surrounding the body. fcl is the ratio of the clothed surface area of the body to the total surface area of the body. In the present study, effective thermal insulation (Icle) has been used because it is difficult to measure fcl directly for comprehensive combinations of single garments. Even though the fcl can be estimated with equations (McCullough et al., 1985), the equations may generate results with a high rate of error, especially in the case of winter ensembles (Havenith, 2005; Holme´r, 2001). As we selected a number of garments (150 kinds) including various winter ensembles, the present study did not consider fcl. The global and serial calculations are well defined in ISO 9920 (2007) and other literature (Havenith, 2005; Oliveira et al., 2005, 2008a, b). The global method (Oliveira et al., 2005, 2008a, b) performs an overall calculation and defines a whole body resistance value. That is, the area weighted of all heat losses and skin temperatures of each body part are summed up before the insulation is calculated (equation (4)). The serial method makes use of the skin temperature and the heat flux from each segment to calculate the local resistances which are then summed according to a serial model (equation (5)). Global and serial Ia were calculated as the same way in IT with equations (4) and (5): sk 2 Ta Pai · Ti 2 Ta T ¼ P ð4Þ Global method : IT ¼ a i · Hi Hsk Serial method : IT ¼
sk 2 Ta X Ti 2 Ta T ¼ ai Hsk Hsk
Where: sk ¼ area weighted mean skin temperature. T Ta ¼ air temperature. Hsk ¼ total heat loss. ai ¼ surface area of segment i/total surface area of manikin. Ti ¼ the surface temperature of segment i. Hi ¼ the heat loss of segment i.
ð5Þ
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Measurement of thermal insulation with human subjects Among the 38 clothing ensembles, 26 clothing ensembles were selected (eight ensembles for spring/fall, seven ensembles for summer, and 11 ensembles for winter) for the human measurement. Different clothing sizes were used for the manikin test and human trials. A total of five females participated as subjects (Age 22.4 ^ 1.3 years; Weight 51.4 ^ 1.7 kg; Height 162.3 ^ 1.9 cm; BSA 1.57 ^ 0.02 m2; BMI 19.5 ^ 0.7). Prior to participation, written and informed consent was obtained from all subjects. Experimental protocol of the present study was approved by the IRB of the College of Human Ecology in Seoul National University. The air temperature in the climatic chamber was maintained at a comfortable level inside the building with seasonal clothing ensembles. The seasonal environmental temperatures were maintained in a comfortable range, from 22 to 248C (mean 22.6 ^ 1.18C) for spring/fall, 24 to 278C (mean 24.7 ^ 0.98C) for summer, and 15 to 188C (mean 16.9 ^ 1.78C) for winter. The air humidity was maintained at 44 ^ 8 percent RH for spring/fall, 48 ^ 7 percent RH for summer, and 48 ^ 9 percent RH for winter. Air speed was maintained at 0.10 ^ 0.05 m s2 1 for spring/fall, 0.05 ^ 0.03 m s2 1 for summer, and 0.15 ^ 0.06 m s2 1 for winter. In these conditions, none of the subjects expressed feelings of discomfort, warmth or chills. Subjects maintained postural comfort in a sitting position on a wooden chair. The air temperature (Ta) and air humidity (Ha) were recorded every minute. Air speed (Va) was measured using a Kata thermometer (Kata coefficient 490). The energy metabolism (EE) was calculated with inhaled and exhaled gas continuously collected for one hour using a gas analyzer (Quark b2, COSMED Company, Italy). Rectal temperature (Tre) was measured at the rectum 12 cm in depth beyond the anal sphincter, using a portable thermistor (LT8 A, Gram Corporation, Japan). Skin temperatures (Tsk) were measured on 12 body regions (the forehead, chest, abdomen, forearm, hand, thigh, calf, foot, upper back, lower back, the back thigh, and the back calf) with the thermistor. Mean sk ) was calculated based on the regional body surface area of Korean skin temperature (T adult females (Lee, 2005). Rectal and skin temperatures were automatically recorded every minute. Body surface area was estimated using an equation derived from adult Korean subjects (Lee, 2005; Lee et al., 2008). Subjects donned experimental garments and mounted equipment on the body, and then rested for 60 minutes before entering the climatic chamber. Subjects were weighed before and after every trial using a body scale (Sartorius Company, sensitivity 1 g). Changes in body mass were considered as an insensible body mass loss. Using the above measurements, thermal insulation with human subjects was calculated by the use of a total heat balance for the body and indirect calorimetry, as shown in ISO 9920 (2007) and Winslow and Herrington (1949). The experimental clothing ensembles in each seasonal combination were randomly selected. All trials were repeated twice and a total of 260 experiments were conducted (two replications £ 26 clothing ensembles £ five subjects ¼ 260 experiments). Twice repeated values were averaged as a representative average. To minimize the effect of circadian rhythm, all experiments were conducted at the same time for each subject. To avoid the specific dynamic effect of diet, all experiments were conducted at least two hours after meals. To minimize the effect of seasonal differences in physiological responses, each seasonal clothing ensemble was selected during the actual season it represented. All experiments were conducted from March to December (April, May,
October, and November for spring/fall wear; May to September for summer wear; March, November, and December for winter wear). Statistical analysis Statistical analyses were conducted with SPSS V. 13.0. Paired T-test’s were conducted to examine the differences between thermal insulations that were calculated by the serial and global methods. To examine the relationship between clothing insulation and clothing factors, such as clothing weight and covering area and between thermal insulations obtained with a thermal manikin and human subjects, Pearson’s correlation was used. The ANOVA was conducted to test the differences between three groups ((1) spring/fall, (2) summer, and (3) winter clothing ensembles; (a) serial method with a manikin, (b) global method with a manikin, and (c) human subjects). A Post hoc test was used to analyze the group differences in items showing significant differences by the ANOVA. The level of significant difference was set at p , 0.05.
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Results Serial and global Ia calculated with a nude thermal manikin had a mean of 0.63 and 0.62 clo, respectively. For the single garments, IT by the serial method was 16 percent larger (0.1-115 percent) than that of the global method ( p , 0.001, Table II). In the case of converting IT to Icle of single garments, the percent difference between the two methods increased on average up to 66 percent. The clothing items that showed the least differences were small garments and accessories, such as a bra, a sun cap, a mask, gloves, and socks. In contrast, the items showing the greatest differences were mostly winter garments, such as jumpers, coats, hood pullovers, thermal hoods, and thermal pants. Among a total of 150 single garments, the upper 10 percent (15 garments) that displayed the biggest differences were all winter garments (Figures 2 and 3).
Item Underwear T-shirts Blouses Vest Cardigan Jacket Jumper/shawl/ coat Trousers/ overall Coverall Skirt/dress/ apron Headwear Scarf/Muffler Gloves Footwear Mean (SD)
Type (n)
Serial IT-Global IT (Serial IT-Global IT) 100/Global IT (clo) (0.01-0.08)b (0.04-0.27) (0.04-0.25) (0.02-0.49) (0.02-0.37) (0.11-0.25)
Coverin-g area (%)a
Clothing mass (g)
4 (1.6-11.1) 13 (6.0-30.9) 17 (6.2-30.0) 17 (3.2-60.8) 18 (3.3-41.3) 21(14.4-29.3)
4-46c 23-51 25-57 18-32 14-57 42-50
22-180c 60-417 61-457 104-446 92-834 301-700
13 16 7 6 7 4
0.03 0.10 0.13 0.13 0.15 0.17
14
0.58 (0.21-1.27)
54 (23.2-114.7)
47-80
213-2,083
23 2
0.13 (0.05-0.26) 0.40 (0.16-0.64)
15 (6.4-30.1) 27 (14.8-38.4)
43-72 86
162-2,552 240-1,076
14 15 4 10 15
0.14 0.04 0.03 0.03 0.02 0.14
18 (7.1-32.3) 6 (1.7-10.6) 4 (3.2-7.5) 4 (1.7-8.0) 3 (0.1-7.7) 16 (17.6)
21-55 1-15 3-6 5-11 3-53
146-510 6-583 15-121 4-265 4-652
(0.05-0.27) (0.01-0.07) (0.02-0.05) (0.01-0.05) (, 0.01-0.05) (0.20)
Notes: n ¼ 150; aLee and Choi (2009); bmean (range); crange
Table II. Differences in clothing insulation calculated by global and serial method
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As a result of the examination on the relevance of clothing factors with IT-differences between the serial and global methods, the IT-differences had significant relevance to both the covering area and total garment mass (Figure 2). A correlation between the covering area and the percent IT-difference was significant both in curve estimation expressed as a quadratic function (r ¼ 0.636, p , 0.01) and in a linear estimation (r ¼ 0.622, p , 0.01). The graph in Figure 2 (right) demonstrates that the smaller covering area (percent) per unit garment mass, the larger the difference between serial and global thermal insulation. For clothing ensembles, thermal insulation in both a thermal manikin and human subjects was estimated. The serial values were higher than the global values. For seasonal clothing ensembles, values by the serial calculation were 39.2 percent (0.18 ^ 0.03 clo) for spring/fall wear, 62.6 percent (0.15 ^ 0.03 clo) for summer wear and for winter wear 64.8 percent (0.69 ^ 0.13 clo) greater than values obtained by the global calculation (Figure 3). The thermal insulation with human subjects showed significant differences to values obtained using a thermal manikin ( p , 0.01, Figure 4). In particular, the Icle by the global method was systemically lower than Icle obtained from the human subjects for all seasonal ensembles ( p , 0.001, Figure 4). Icle by the serial method was larger than Icle obtained from the human subjects for only winter wear, while spring and summer ensembles showed smaller values in the serial values than in human trials.
Serial - Global IT (%)
120
Figure 2. Scatter plots between the IT-difference and clothing factors
120
120
r = +0.622 p < 0.01
100
100 Winter garments
r = +0.567 p < 0.01
80
80
60
60
60
40
40
40
20
20
20
0
0
0
80
0
20
40
60
80
100
0
Covering area, CA (%)
500 1,000 1,500 2,000 2,500
r = –0.199 p < 0.05
100
80% of the garments measured
0
0.4 0.8 1.2 1.6
Garment mass, GM (g)
2
2.4
CA/GM
Note: Covering area and garment mass
Single garments (N = 150, r = 0.937, p < 0.01)
Clothing ensembles (N = 38, r = 0.981, p < 0.01)
r=1
2.1
2.1
1.8
1.2 0.9 0.6 0.3 0.0
r=1
1.8 Insulative coverall Jumpers, winter coats Underwear, Shirts, Skirts, Pants, etc 0.0 0.3 0.6 0.9 1.2 1.5 1.8 2.1 Global Icle
1.5 Serial Icle
Figure 3. Relationship between thermal insulation of clothing ensembles estimated by the serial and global method with a thermal manikin
Serial Icle
1.5
Winter
1.2 0.9
Spring/ fall
0.6
***
(Serial-global)100/global Icle
0.3 0.0
Serial-global Icle = Spring/fall 0.18 (±0.03)clo = Summer 0.15 (±0.03)clo = Winter 0.69 (±0.13)clo ***
Summer
= Spring/fall 39.2 (±3.8)% = Summer 62.6 (±21.7)% = Winter 64.8 (±13.1)%
0.0 0.3 0.6 0.9 1.2 1.5 1.8 2.1 Global Icle
**
***
2.1
Serial method Global method
r=1
1.2
1.8
0.9 0.6 0.3
*** ***
Clothing insulation
***
1.5
N = 26 r = 0.970** Icle
Icle _ thermal manikin
1.8 1.5
Manikin serial Manikin global Human subjects
2.1
* ***
1.2 *
0.9 N = 26 r = 0.950**
0.0
0.6
193
*** *** ***
0.3 0.0
0.0 0.3 0.6 0.9 1.2 1.5 1.8 2.1 Icle _ Human subjects
Spring/fall (N = 8)
(a) Note: Significance at: *p < 0.05, **p < 0.01 and ***p < 0.001
Summer (N = 7)
Winter (N = 11)
(b)
Discussions One aim of the present study was to extend the current knowledge about differences in thermal insulation between the global and serial methods toward comprehensive daily and seasonal clothing (150 garments and 38 ensembles). In the present study, thermal insulation by the serial method was greater than those values obtained by the global method. The result is in agreement with previous studies (Anttonen, 1999, 2001; Holme´r, 2001; Kuklane et al., 2004, 2007; Meinander, 2004; Nilsson, 1997). The differences were greater in clothing ensembles (61 percent greater compared to the global values) than in the single garments (16 percent greater compared to the global values). Among a total of 150 single garments, the upper 10 percent (15 garments) that showed the greatest differences were all winter garments. For seasonal clothing ensembles, the differences were more striking in winter ensembles (0.69 clo) than in spring/fall and summer ensembles (0.18 and 0.15 clo). The overestimation in the serial values of the cold protective clothing can increase the risk of adverse health effects. These results indicate that the difference between the global and serial methods will be increased when the distribution of clothing layers on the body surface is not homogeneous or garments are bulky. Any uneven clothing insulation is expected to be the main source of the difference. Homogeneousness and bulkiness can be evaluated in terms of surface area covered by clothing (percent) and garment mass. For clothing ensembles, Figure 2 in the present study demonstrates that the differences had significant relevance to both the covering area and total garment mass. As shown in Figure 2, items that showed notable differences were the garments that had a greater garment mass per unit covering area. It was not only the characteristics of clothing, but also the number of independently controlled areas of the thermal manikin that affected the difference between global and serial values. Redortier (1997) reported that serial values on 35 segments are higher than on 15 segments. The serial model increases total insulation by 14 and 20 percent when calculated with a recombination into 15 areas and the 35 original areas, respectively. The increase of the body segments that are independently heated has an advantage of increasing the spatial resolution of thermal manikins, but it is important to note that the difference between the global and serial values also increases as well.
Figure 4. Relationship between thermal insulation of clothing ensembles estimated with a thermal manikin and human subjects
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For practical purposes, it is required that thermal insulation values with a thermal manikin are validated in human trials. There are some reports on the comparisons between manikins and human participants, but the results are conflicting. Some reported human testing values were smaller in human testing than manikin tests (Kuklane et al., 2007; Nilsson et al., 1998), greater in wear trial values than in manikin values (Ducharme et al., 1996; Konarska et al., 2007) or insignificant (Meinander et al., 2004; Sung, 1991). The differences between manikin and wear trial values have been attributed to the difference in the amount of trapped air and body surface area exposed to the air (Ducharme et al., 1996) or moisture accumulation in the cold protective clothing (Kuklane et al., 2007). However, the present study demonstrates that the calculation method can be one of the reasons for the difference between human and manikin values. We found that the global values obtained from the manikin were lower than the wear trial values for all seasonal ensembles, while the differences between the serial values and human testing values were dependent on the seasonal ensembles. That is, for the serial values, the differences between human trials and manikin depend more on the seasonal characteristics of clothing ensembles. When it is considered that most previous studies employed only several kinds of ensembles for the comparisons between human and manikin tests, the present results that employed 26 seasonal clothing ensembles represent a greater degree of verification. Further, if the difference between the global values and wear trial-values can be interpreted as a systematic error, it can be corrected. More data from wear trials will contribute to this correction. Besides differences in the amount of trapped air or moisture accumulation between human and manikin values, there are further factors to be considered as the reasons of the differences: fundamental physiological differences (e.g. insensible perspiration from the skin and lungs, vasodilation/vasoconstriction, non-uniform skin temperature) and differences in the experimental protocols (body size, posture, clothing fit, and air temperature between thermal manikin tests and human wear trials). Regarding the present experimental protocol, the following factors should be noted: . postures; . clothing fit; . air temperature; and . non-uniform skin temperature. First, the postures of the thermal manikin and human subjects were different in the present study. We used a standing thermal manikin, but human subjects were seated on a wooden chair to maintain comfort. For humans, the sitting posture represents a greater comfort state than the standing posture, which results in an increase in EE. There, apparently, is a difference in convective and radiant heat exchange between standing and sitting, but the difference was not large (Sung, 1991); 0.88 and 0.86 clo in standing and sitting positions, respectively. The difference seen in variation of posture seems to depend on the characteristics of the clothing, especially the thickness of the air layer inside the garments. Second, clothing fit is a crucial factor because it directly affects testing results. In the present study, the size of a thermal manikin (BSA 1.7 m2) was larger than the female subjects (BSA 1.57 m2). The height and weight of five female participants were similar
in range. To make the clothing fit correctly, we used two sizes of single garments with an identical design for a thermal manikin and human subjects. Third, in the present study, Ta in the chamber was different during the thermal manikin test and human wear trials. As described in the method section, Ta was constant at 21.58C during all thermal manikin tests, while for human wear trials Ta was flexible in the comfort range according to subjects’ preference. If air temperature goes up, both the numerator (Tsk 2 Ta) and the denominator (Q) will be smaller in equation (1). Unpublished data in our laboratory shows that the global values measured at Tair of 308C was the same as the value at 21.58C, but serial values at 308C were smaller at 21.58C. Finally, discussions on the control mode of thermal manikins are ongoing and open to question from a standpoint of the analogous tool to the human thermoregulatory system. According to Havenith (2005), Melikov (2004), and Oliveira et al. (2008a), four modes are in use to control a thermal manikin: (1) comfort mode, based on the comfort equation; (2) constant surface temperature for the whole body of the manikin; (3) constant surface temperature but different for the body segment; and (4) constant heat flux from the manikin’s body. Most commonly, constant uniform surface temperature mode (2) is applied (ISO 9920, 2007) at 338C (McCullough and Kenney, 2003; Oliveira et al., 2008b), 348C (Konarska et al., 2007), or 358C (Ducharme et al., 2004). However, the present study controlled the thermal manikin at the constant non-uniform surface temperature mode to take into account the thermal heterogeneity of the human body in thermal comfort, as shown in some previous research (Buisson et al., 2004; Elabbassi et al., 2002; McCullough et al., 1985). Even though the difference between the two control modes (i.e. a constant surface temperature and a comfort mode modeling a varying surface temperature) was small (Anttonen et al., 2004), and the thermal insulation values of both Ia and IT were not significantly different between the constant uniform and non-uniform skin temperature mode maintained at a mean Tsk of 32.78C (Takahashi-Nishimura et al., 1997), it is clear that uniform and non-uniform skin temperatures over a thermal manikin would generate different free convection flow around the manikin. In particular, the uniform temperature distribution leads to an overestimation of heat loss from the extremities and the overestimation particularly increases during exposure to cold (Tamura, 2006). The heat loss from the extremities of the manikin maintained at a uniform surface temperature was more affected by the wave motions when compared to the rest of the manikin body (Ducharme et al., 1996), but the effect was not present in humans since the extremities were vasoconstricted in cold environments. It important to address the discussion that control modes are bound alongside the calculation methods. For instance, the global values with a constant skin temperature mode were nearly equal to the serial values with a constant heat flux mode (Oliveira et al., 2008b; Xu et al., 2008). The serial values with the constant skin temperature mode and the constant heat flux mode saw large differences, while the global values were similar between the two modes (Xu et al., 2008). The issues concerning relationships between control modes and calculation methods should be further investigated for the standardization of thermal manikin testing.
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Conclusions In the present study, the comparisons between the global and serial calculations have been extended to 150 daily garments and 38 seasonal clothing ensembles. For both single garments and clothing ensembles, thermal insulation was greater in the serial calculation than in the global calculation. The difference was more notable in winter clothing, suggesting that the overestimation in the serial insulation values of the cold protective clothing can increase the risk of adverse health effects on the protection of workers in cold environments. For the validation of the global and serial values in human testing using 26 seasonal clothing ensembles, the global values were systemically smaller than the human testing values, while the serial values showed no consistent tendency in the difference from the values obtained from human trials. It indicates that the global values can be validated to the wear trial values through corrections, but the serial values are unlikely to be validated in human testing. Also, discussions about the thermal manikin testing for the validation in human trials should be accompanied by the control modes of the thermal manikin as well as the calculation methods. The constant skin temperature mode has been mostly used with the global calculation, but further examinations on a non-uniform skin temperature mode of thermal manikins are needed as an analog tool of the human thermoregulatory system. References Anttonen, A., Niskanen, J., Meinander, H., Bartels, V., Kuklane, K., Reinertsen, R.E., Varieras, S. and Sołtyn´ski, K. (2004), “Thermal manikin measurements-exact or not?”, Int J Occup Saf Ergon, Vol. 10 No. 3, pp. 291-300. Anttonen, H. (1999), “Inter laboratory trial of thermal manikin based on thermal insulation of cold protective clothing in accordance with ENV 342”, Proceedings of the 3rd International Meeting on Thermal Manikin Testing 3IMM in Stockholm, Sweden, pp. 8-11. Anttonen, H. (2001), “Subzero project: preliminary results of the manikin measurements”, Proceedings of the 4th International Meeting on Thermal Manikins in EMPA, pp. 5-7. Buisson, P., Bach, V., Elabbassi, E.B., Chardon, K., Delanaud, S., Canarelli, J.P. and Libert, J.P. (2004), “Assessment of the efficiency of warming devices during neonatal surgery”, Eur J Appl Physiol, Vol. 92, pp. 694-7. Choi, J.W., Lee, J.Y., Ko, E.S., Lee, H.H. and Kim, J.Y. (2006), “Daily clothing worn by Korean women both outdoors and at home by season”, Korean Soc Living Environ Sys, Vol. 13 No. 1, pp. 8-17. Ducharme, M.B., Brooks, C.J. and Potter, P. (1996), “Measurement of immersion suit insulation: a comparison between human subjects and a thermal manikin”, The 7th International Conference on Environmental Ergonomics, in Jerusalem, Israel, pp. 317-20. Ducharme, M.B., Potter, P. and Brooks, C.J. (1998), “Determination of immersion suit thermal resistance: a comparison between human and manikin”, The 8th International Conference on Environmental Ergonomics in San Diego, CA, pp. 207-10. Ducharme, M.B., Tikuisis, P. and Potter, P. (2004), “Selection of military survival gears using thermal manikin and computer survival model data”, Eur J Appl Physiol, Vol. 92, pp. 658-62. Elabbassi, E.B., Chardon, K., Telliez, F., Bach, V. and Libert, J.P. (2002), “Influence of head position on thermal stress in newborns: simulation using a thermal mannequin”, J Appl Physiol, Vol. 93, pp. 1275-9.
EN 342 (2004), “Protective clothing – ensembles and garments for protection against cold”, British-Adopted European Standard. Gagge, A.P., Burton, A.C. and Bazett, H.C. (1941), “A practical system of units for the description of the heat exchange of man with his environment”, Science, Vol. 94, pp. 428-30. Havenith, G. (2005), “Clothing heat exchange models for research and application”, The 11th International Conference on Environmental Ergonomics in Lund, Sweden, pp. 66-73. Holme´r, I. (2001), “Validation of manikin insulation values in wear trials”, Proceedings of the 4th International Meeting on Thermal Manikins in EMPA, Switzerland, pp. 8-12. Holme´r, I. (2004), “Thermal manikin history and applications”, Eur J Appl Physiol, Vol. 92, pp. 614-18. ISO 15831 (2004), Clothing – Physiological Effects – Measurement of Thermal Insulation by Means of a Thermal Manikin, International Organization for Standardization, Geneva. ISO 9920 (2007), Ergonomics of the Thermal Environment – Estimation of the Thermal Insulation and Evaporative Resistance of a Clothing Ensemble, International Organization for Standardization, Geneva. Konarska, M., Soltynski, K., Sudol-Szopinska, I. and Chojnacka, A. (2007), “Comparative evaluation of clothing thermal insulation measured on a thermal manikin and on volunteers”, Fibres & Textiles in Eastern Europe, Vol. 15 No. 2, pp. 73-9. Kuklane, K., Sandsund, M., Reinertsen, R.E., Tochihara, Y., Fukazawa, T. and Holme´r, I. (2004), “Comparison of thermal manikins of different body shapes and size”, Eur J Appl Physiol, Vol. 92, pp. 683-8. Kuklane, K., Gao, C., Holme´r, I., Giedraityte, L., Bro¨de, P., Candas, V., den Hartog, E., Meinander, H., Richards, M. and Havenith, G. (2007), “Calculation of clothing insulation by serial and parallel methods: effects on clothing choice by IREQ and thermal responses in the cold”, Int J Occu Safety Ergon, Vol. 13 No. 2, pp. 103-16. Lee, J.Y. (2005), A Study on the body surface area of Korean adults, PhD dissertation, Seoul National University, Seoul. Lee, J.Y. and Choi, J.W. (2009), “Estimation of regional body surface area covered by clothing”, J of Human-Environ System, Vol. 12 No. 1, pp. 35-45. Lee, J.Y., Choi, J.W. and Kim, H. (2008), “Determination of body surface area and formulas to estimate body surface area using the Alginate method”, J Physiol Anthropol, Vol. 27 No. 2, pp. 71-82. McCullough, E.A. and Kenney, W.L. (2003), “Thermal insulation and evaporative resistance of football uniforms”, Med Sci Sports Exerc, Vol. 35 No. 5, pp. 832-7. McCullough, E.A., Jones, B.W. and Huck, J. (1985), “A comprehensive data base for estimating clothing insulation”, ASHRAE Transactions, Vol. 91, pp. 29-47. Meinander, H. (2004), “Use of thermal manikins for the standardised assessment of SUBZERO clothing”, Proceedings of the 4th International Meeting on Thermal Manikins in EMPA, Switzerland. Meinander, H., Anttonen, H., Bartels, V., Holme´r, I., Reinertsen, R.E., Soltynski, K. and Varieras, S. (2004), “Manikin measurement versus wear trials of cold protective clothing (Subzero project)”, Eur J Appl Physiol, Vol. 92, pp. 619-21. Melikov, A. (2004), “Breathing thermal manikins for indoor environment assessment: important characteristics and requirements”, Eur J Appl Physiol, Vol. 92, pp. 710-13. Nilsson, H. (1997), “Analysis of two methods of calculating the total insulation”, Proceedings of a European Seminar on Thermal Manikin Testing in Arbetslivsrapport, pp. 17-22.
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Nilsson, H., Holmer, I. and Ohlsson, G. (1998), “Effects of wind and walking on local clothing insulation”, The 8th International Conference on Environmental Ergonomics in San Diego, CA, pp. 161-4. Oliveira, A.V.M., Gaspar, A.R. and Quintela, D.A. (2005), “Thermal insulation of cold protective clothing: static and dynamic measurements with a movable thermal manikin”, The 11th International Conference on Environmental Ergonomics in Lund, Sweden, pp. 99-102. Oliveira, A.V.M., Gaspar, A.R. and Quintela, D.A. (2008a), “Measurements of clothing insulation with a thermal manikin operating under the thermal comfort regulation mode”, Eur J Appl Physiol, Vol. 104, pp. 679-88, Comparative analysis of the calculation methods. Oliveira, A.V.M., Branco, V.J., Gaspar, A.R. and Quintela, D.A. (2008b), “Measuring thermal insulation of clothing with different manikin control methods. Comparative analysis of the calculation”, paper presented at the 7th International Thermal Manikin and Modelling Meeting in University of Coimbra, Portugal. Redortier, B. (1997), “Experiences with manikin measurements at ITF Lyon”, Proceedings of a European Seminar on Thermal Manikin Testing in Arbetslivsrapport, pp. 30-7. Sung, S.K. (1991), “Studies on the thermal insulation effect of the Korean women’s folk clothes-experiment by thermal manikin”, Journal of Korean Fiber Society, Vol. 28 No. 10, pp. 42-8. Takahashi-Nishimura, M., Tanabe, S. and Hasebe, Y. (1997), “Effects of skin surface temperature distribution of thermal manikin on clothing thermal insulation”, J Physiol Anthropol, Vol. 16 No. 5, pp. 181-9. Tamura, T. (2006), “Development of a two-layer movable sweating thermal manikin”, Ind Health, Vol. 44, pp. 441-4. Winslow, C.E.A. and Herrington, L.P. (1949), Temperature and Human Life, Princeton University Press, Princeton, NJ, pp. 132-45. Xu, X., Endrusick, T., Gonzalez, J., Santee, W. and Hoyt, R. (2008), “Comparison of parallel and serial methods for determining clothing insulation”, Journal of ASTM International, Vol. 5 No. 9, pp. 1-6. Corresponding author Joo-Young Lee can be contacted at:
[email protected]
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Effects of process parameters on mechanical properties of coated fabrics Yasemin Bulut and Vildan Su¨lar
Properties of coated fabrics
205
Department of Textile Engineering, Faculty of Engineering, Dokuz Eylu¨l University, ˙Izmir, Turkey Abstract Purpose – The purpose of this paper is to examine the effects of coating process parameters (base fabric, coating material, coating technique and production parameters) on mechanical properties of coated fabrics. Design/methodology/approach – In this research, 24 coated fabrics were produced under controlled production conditions by using two cotton base fabrics and two coating materials as polyurethane (PU), PU/silicone in order to study how coating affects some of the base fabric’s mechanical properties such as breaking strength, breaking elongation, tear strength, bursting strength, bending rigidity and abrasion resistance. The measured data were evaluated with variance analysis to determine the effects of the coating parameters at 95 per cent confidence level. Findings – Breaking strength shows increments for almost all fabrics, whereas breaking elongation values decreased by coating application. Coating has a very clear influence on tear strength of coated fabrics due to the penetration of coating material into the fabric structure. Changes in bursting strength are not similar for two base fabrics with systematically changed production parameters. Coating improves all measured parameters of bending rigidity. Coating application enhances abrasion resistance though some broken fibers are observed on the fabric surface in scanning electron microscopy investigation. Originality/value – In the past few years, the researches on this area focused on investigating the effects of coating materials and layers on tensile properties. This study comprehensively examines the effects of several coating parameters on mechanical properties such as breaking strength, breaking elongation, tear strength, bursting strength, bending rigidity and abrasion resistance. Keywords Coatings, Mechanical properties of materials, Polyurethane, Fabric production processes Paper type Research paper
1. Introduction Coating is a production process which leads to the enhancement of functional properties and technical performances rather than aesthetic properties or appearance of fabrics. Coated fabrics are produced by coating one or both surfaces of base woven, knitted or non-woven fabrics with coating materials. Coated fabrics have wide applications in fields such as medical substrates, protective clothing, sportive textiles, flexible membranes for civil structures, industrial fabrics and geotextiles. Nowadays, coated fabrics are widely used in protective and outerwear garments. Some functional features of coated fabrics stand out with their related end-uses but nevertheless fundamental mechanical and physical properties of fabrics are always critically important for their performances. The authors would like to thank Denizli Printing and Dyeing Ind. Inc. for providing materials and their technical support.
International Journal of Clothing Science and Technology Vol. 23 No. 4, 2011 pp. 205-221 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111136476
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206
Coating a layer of polymeric material on fabric imparts new characteristics to the base fabric. The resultant-coated fabric may have functional properties, such as resistance to soiling, penetration of fluids, etc. or have an entirely different aesthetic appeal, such as finished leather (Sen and Damewood, 2001). A coated fabric can be considered as a composite material in that its mechanical response is truly different from the simple sum of the behaviour of its two components, the fabric substrate and the coating material (Farboodmanesh et al., 2005). The resulting coated fabric will have many properties which cannot be offered by either component individually and careful consideration is necessary to select both base fabric and coating polymer (Fung, 2002). Coated fabrics behave much different from uncoated fabrics during deformation. To achieve reasonably good quality and to predict durability of such textile goods, it is essential to have enough understanding of their behaviour during wear. As a result, interest in this area of research has recently increased (O¨ner, 2007). It is well known that the fabrics become stiffer after coating, because coating material fills the spaces between the yarns and cements the warp and weft threads together. It increases tensile modulus and bending rigidity, especially in the warp direction (Masteikaite and Saceviciene, 2005). Armag˘an and Karakas¸ (2007) studied about physical performance of knit fabric laminate structure, concentrating on the different contents of fabrics laminated with the polyester-polyurethane (PU) and polyether-PU membranes. Results from that work suggested that bursting strength and abrasion resistance improved while thickness decreased by lamination. The investigation from Kut and Gu¨nes¸og˘lu (2005) demonstrated that breaking force increased with coating application and was influenced by the change of coating material. Abbott et al. (1971) proposed to accomplish to study the effect of coating on mechanical properties of fabrics using more than 30 cotton samples with different structures coated by PVC plastisol. Cho et al. (2003) tried to coat fabrics with shape-memory PU and reported that the breaking strength and elongation were primarily depended on the PU hard-segment content in coating formula. Even though, more content of PU (per cent), more breaking strength and less breaking elongation were obtained, relatively flexible or rigid-coated fabric can be produced by the optimum hard segment PU content in coating formula. Some researches focused on the anisotropic behaviour of coated fabrics. Masteikaite and Saceviciene (2005) made an attempt to examine the influence of structural characteristics of coated fabrics and laminates on the tensile property and analyze anisotropy of materials, the results showed that tensile behaviour varied with the test directions, delamination occurred between layers of the fabrics. Chen et al. (2007) examined tensile performance of PVC-coated woven fabrics under multi-axial loads and found out that tensile performance under bi- and multi-axial loads were much better than those under unaxial loads. Luo et al. (2008) further examined tensile properties in seven in-plane directions (0o, 15o, 30o, 45o, 60o, 75o and 90o with the weft direction) and the influence of initial crack length and propagation on tearing properties of PVC-coated biaxial warp-knitted polyester fabrics. The highest breaking strength was obtained at warp direction whereas the lowest at 45o (bias) along with the weft direction was observed. Tearing strength correlated positively with crack orientation but negatively with the initial crack length. Hu and Xu (2008) studied effect of test method and tearing direction on tearing properties of PVC-coated multi-axial warp knitted glass fabric. According to the measurement of trapezoidal and tongue tearing test results, they reported that tearing properties depended on test method and test direction for coated
multi-axial warp knitted fabric and highest tearing strength was obtained in diagonal direction of the coated fabrics. The aim of this study is to examine the effects of coating process parameters on mechanical properties of coated fabrics. We first studied how coating affects some of the base fabric’s mechanical properties and then measured data were evaluated with variance analysis to determine the effects of coating parameters at 95 per cent confidence level.
Properties of coated fabrics
207
2. Experimental details 2.1 Materials In this study, coated fabrics were produced under controlled production conditions by using two cotton base fabrics (Table I) and two coating materials as PU, PU/silicone. These base fabrics were coated with these coating materials as single-coat by two different coating techniques such as rotary screen coating and direct (blade) coating (Figure 1). All coated fabrics were manufactured by Stork CT4 coating machine in controlled conditions with systematically changing production parameters giving 24 test samples. The coated fabrics were dried at 140oC and cured at the speed of 24 m/min for at 170oC. The production plan and test sample codes are given in Table II. 2.2 Measurements All test fabrics were conditioned in a standard atmosphere of 65 ^ 2 per cent relative humidity and 20 ^ 2oC. After this step breaking strength, breaking elongation, tear strength, bursting strength, bending rigidity and abrasion tests were carried out. All properties were measured in this study and related standards are given in Table III: . The specimens of each sample were cut in square shape (7 £ 7 cm2) and the thickness of each sample was measured using James Heal R £ B Cloth Thickness Tester under the 5 g/cm2 pressure. To evaluate the homogeneity, the fabric thickness and the fabric air permeability were measured on ten different parts of each sample by using Textest 3300 Air Permeability Tester (test area ¼ 20 cm2, test pressure ¼ 100 Pa). . The breaking strength and elongation, tear strength and bursting strength were measured using Instron 4411 model tensile testing machine, the cross-head speed was kept constant at 300 mm/min during all strength tests. . For tear strength, the initial length between jaws was kept at 25 mm and the tearing of the test specimen was calculated from the average of the five highest
Fabric code S0 K0
Content 100 % cotton 100 % cotton
Weave
Yarn setting (threads/cm) Warp
Weft
Plain
51
29
Plain
39
21
Yarn linear density (tex) Warp
Weft
Mass per unit area (g/m2)
14.8
14.8
122.0
2 £ 29.5
29.5
185.5
Table I. The physical properties of base fabrics
IJCST 23,4
Blade Coating resin Coated fabric
Base fabric
208
(a)
Coated fabric Coating resin
Base fabric
Figure 1. Schematic diagrams of coating techniques used in experimental study
Table II. The production plan of test samples
(b) Notes: (a) Direct coating (Rosato et al., 2004); (b) Rotary screen coating (Rotary Screen System, 2011)
Codes of test fabrics
Coating material
Coating technique
Production parameters
SPR1, SPR2, SPR3 SPB1, SPB2, SPB3 SSR1, SSR2, SSR3 SSB1, SSB2, SSB3 KPR1, KPR2, KPR3 KPB1, KPB2, KPB3 KSR1, KSR2, KSR3 KSB1, KSB2, KSB3
PU PU PU/silicone PU/silicone PU PU PU/silicone PU/silicone
Rotary Blade Rotary Blade Rotary Blade Rotary Blade
Press: 2, 4, 6 Contact angle: Press: 2, 4, 6 Contact angle: Press: 2, 4, 6 Contact angle: Press: 2, 4, 6 Contact angle:
screen screen screen screen
20, 25, 30 20, 25, 30 20, 25, 30 20, 25, 30
Measured property
Related standard
Mass per unit area (g/m2) Thickness (mm) Air permeability (l/m2/s) Breaking strength and elongation (N, %) (warp, weft, bias direction) Tear strength (N) (warp, weft direction) Bursting strength (N) Bending rigidity (mg/cm) (bending length and bending rigidity in warp, weft, bias direction and fabric rigidity)
ASTM D 751-06 ISO 5084 (1996) ISO 9237 (1995) ASTM D 751-06 (cut strip method) (2006a)
.
.
.
ASTM D 751-06 (trapezoidal test) (2006c) ASTM D 751-06 (ring clamp method) (2006b) ASTM D 1388-96 (cantilever method) (2008)
peak loads of resistance (not including the initial peak) registered during the separation of the tear according to ASTM D 751-06. For bursting strength, force required for bursting that was perpendicular to the fabric surface was measured. Bending length was measured according to the Cantilever method in three main directions, namely, warp, weft and bias and fabric rigidity was calculated from warp and weft bending rigidity. Scanning electron microscopy (SEM) observation. SEM was used to examine the coated fabric surface before and after 20,000 abrading cycles. Scanning electron micrographs were taken by using JEOL JSM-6060, operated at 10 kV. Prior to SEM observations, the specimens were coated with gold using the plasma sputtering apparatus.
Measured data on mechanical properties of coated fabrics were analyzed with variance test in SPSS to determine the effects of coating parameters at 95 per cent confidence level. 3. Results and discussion Variance analysis was applied for statistical evaluation to identify the differences between coating parameters for the mechanical properties examined in this study. Before statistical evaluation of mechanical properties, fabric weight, fabric thickness and fabric air permeability were tested to evaluate the homogeneity of coating. With reference to results of variance analysis of these features, there is no statistically significant difference amongst repeats for 95 per cent confidence level. After this procedure, breaking strength and elongation, tear strength, bursting strength, bending rigidity and abrasion tests were carried out and the results were evaluated to determine the effects of coating components. 3.1 Effect of coating parameters on fabric breaking strength and breaking elongation When comparisons between base and coated fabrics are examined, it is determined that noticeable changes in breaking strength can be shown by coating in Figure 2. By restricting warp and weft yarn movement in fabric structure, coating causes fabric break as a whole and the yarns break at one time. The breaking strength increases
Properties of coated fabrics
209 Table III. The measured properties and related standards
210
1,600 Warp
1,400 Breaking strength (N)
IJCST 23,4
Weft
Bias
1,200 1,000 800 600 400 200 0 K K 0 PR K 1 P K R2 P K R3 P K B1 P K B2 P K B3 S K R1 S K R2 S K R3 S K B1 S K B2 SB 3 S SP 0 R SP 1 R SP 2 R SP 3 B SP 1 B SP 2 B SS 3 R SS 1 R SS 2 R SS 3 B SS 1 B SS 2 B3
Figure 2. The breaking strength of base and coated fabrics
Test sample
by increasing the rotary screen press for the first three samples coated with PU, but decreases for the samples coated with PU/silicone. But for the samples coated by direct coating, there is no systematically change according to the production parameters (contact angle). For S-coded samples breaking strength rises up with increasing rotary press magnitude (Figure 2). For both two base fabrics, decreases in breaking elongation especially in warp direction were obtained and changes in breaking elongation in weft and bias (45o) directions were similar after coating by changing coating parameters (Figure 3). According to the variance analysis, results as indicated in Table IV, the effects of base fabric and coating material on breaking strength and almost on breaking elongation are statistically significant at 95 per cent confidence level ( p , 0.05). The influence of other coating parameters and their interactions vary with the test directions of coated fabric. However, the interaction of both coating parameters has statistically significant influence at 95 per cent confidence level on breaking strength. When the effect of coating technique separately analyzed, the change in blade contact angle significantly affects breaking strength at 95 per cent confidence level ( p , 0.05) although the change in press magnitude does not have statistically
Figure 3. The breaking elongation of base and coated fabrics
35 30 Warp
25
Weft
Bias
20 15 10 5 0 K K 0 PR K 1 P K R2 P K R3 P K B1 P K B2 P K B3 S K R1 S K R2 S K R3 S K B1 S K B2 SB 3 S SP 0 R SP 1 R SP 2 R SP 3 B SP 1 B SP 2 B SS 3 R SS 1 R SS 2 R SS 3 B SS 1 B SS 2 B3
Breaking elongation (%)
40
Test sample
Source of variation Base fabric Coating material Coating technique Production parameters Base fabric £ coating material Base fabric £ coating technique Coating material £ coating technique Base fabric £ coating material £ coating technique Base fabric £ production parameters Coating material £ production parameters Base fabric £ coating material £ production parameters Coating technique £ production parameters Base fabric £ coating technique £ production parameters Coating material £ coating technique £ production parameters Base fabric £ coating material £ coating technique £ production parameters
Breaking Breaking strength elongation Warp Weft Bias Warp Weft Bias 0.000 0.000 0.247 0.028 0.002 0.003 0.000 0.000 0.000 0.079 0.000 0.000 0.000
0.000 0.000 0.017 0.081 0.917 0.286 0.635 0.000 0.918 0.244 0.280 0.005 0.396
0.000 0.000 0.284 0.060 0.237 0.901 0.000 0.000 0.577 0.009 0.206 0.003 0.970
0.000 0.000 0.031 0.011 0.013 0.183 0.000 0.001 0.391 0.985 0.120 0.006 0.332
0.000 0.001 0.967 0.031 0.354 0.155 0.090 0.000 0.696 0.091 0.331 0.000 0.050
0.000 0.926 0.863 0.886 0.248 0.306 0.336 0.001 0.626 0.329 0.060 0.223 0.065
0.000 0.497 0.096 0.049 0.155 0.682 0.000 0.001 0.000 0.000 0.007 0.053
Notes: The p-values of Duncan’ test are shown in this table; the effect of corresponding variable on the corresponding property is significant at 95 per cent confidence level ( p , 0.05)
significant influence on breaking strength for coated fabrics produced by rotary screen coating ( p . 0.05). 3.2 Effect of coating parameters on tear strength As shown in Figure 4, coating has a very clear influence on tear strength of coated fabrics. Coating material penetrates into fabric and intercepts the yarn’s mobility in fabric structure and as a result, coating process makes fabric more rigid and inflexible. Generally, this case causes decreases in tear strength of coated fabrics. In this study, the base fabrics have plain weaves so the tear strength of fabrics were low at the beginning and also after coating decreases in tear strength were observed as shown in Figure 4. As shown, the effects of production parameters of coating techniques depend on coating material, in this case, the rotary screen press makes dramatic changes in tear strength for PU/silicone-coated fabrics but slight changes for PU-coated fabrics. This case is just opposite for the direct coating; the contact angle changes drastically the tear strength of PU-coated fabrics but not leads to great differences for PU/silicone-coated fabrics. According to the variance analysis results seen in Table V, the effects of all coating parameters and almost their interactions are statistically significant on tear strength of coated fabrics at 95 per cent confidence level ( p , 0.05). 3.3 Effect of coating parameters on bursting strength The bursting strength of base and coated fabrics and also the change as a function of coating parameters are shown in Figure 5. Changes in bursting strength are not similar for two base fabrics with systematically changed production parameters. Generally, it can be emphasized that coating improves the bursting strength of fabrics; it reduces
Properties of coated fabrics
211
Table IV. Duncan’s test on the effects of coating parameters on breaking strength and breaking elongation
IJCST 23,4
45 Warp
Weft
40
212
Tear strength (N)
35 30 25 20 15 10 5 0 K K 0 PR K 1 P K R2 P K R3 P K B1 P K B2 P K B3 S K R1 S K R2 S K R3 S K B1 S K B2 SB SP 3 R1 S0 SP R SP 2 R SP 3 B SP 1 B SP 2 B SS 3 R SS 1 R SS 2 R SS 3 B SS 1 B SS 2 B3
Figure 4. The tear strength of base and coated fabrics
Test sample
Table V. Duncan’s test on the effects of coating parameters on tear strength
Source of variation
Tear strength Warp Weft
Base fabric Coating material Coating technique Production parameters Base fabric £ coating material Base fabric £ coating technique Coating material £ coating technique Base fabric £ coating material £ coating technique Base fabric £ production parameters Coating material £ production parameters Base fabric £ coating material £ production parameters Coating technique £ production parameters Base fabric £ coating technique £ production parameters Coating material £ coating technique £ production parameters Base fabric £ coating material £ coating technique £ production parameters
0.000 0.000 0.000 0.002 0.490 0.081 0.000 0.000 0.000 0.612 0.000 0.000 0.012 0.053 0.000
0.000 0.094 0.000 0.000 0.002 0.873 0.000 0.000 0.000 0.070 0.010 0.000 0.000 0.000 0.000
Notes: The p-values of Duncan’ test are shown in this table; the effect of corresponding variable on the corresponding property is significant at 95 per cent confidence level ( p , 0.05)
the flexibility of fabric and yarn’s mobility, so under the applied force, the yarns in fabric structure suddenly break and bursting strength increase with the penetration of coating material into base fabric. The results of variance analysis show that the effects of all coating parameters (base fabric, coating material, coating technique and production parameters) on bursting strength of coated fabrics are statistically significant at 95 per cent confidence level individually but the effect of the interaction of all coating parameters is not ( p . 0.05) (Table VI).
Properties of coated fabrics
1,000 900 Bursting strength (N)
800 700 600
213
500 400 300 200 100 K K 0 PR K 1 P K R2 P K R3 P K B1 P K B2 P K B3 S K R1 S K R2 S K R3 S K B1 S K B2 SB 3 SP S0 R SP 1 R SP 2 R SP 3 B SP 1 B SP 2 B SS 3 R SS 1 R SS 2 R SS 3 B SS 1 B SS 2 B3
0
Figure 5. The bursting strength of base and coated fabrics
Test sample
Source of variation Base fabric Coating material Coating technique Production parameters Base fabric £ coating material Base fabric £ coating technique Coating material £ coating technique Base fabric £ coating material £ coating technique Base fabric £ production parameters Coating material £ production parameters Base fabric £ coating material £ production parameters Coating technique £ production parameters Base fabric £ coating technique £ production parameters Coating material £ coating technique £ production parameters Base fabric £ coating material £ coating technique £ production parameters
Bursting strength 0.000 0.000 0.002 0.013 0.054 0.546 0.299 0.003 0.000 0.015 0.059 0.113 0.043 0.000 0.088
Notes: The p-values of Duncan’ test are shown in this table; the effect of corresponding variable on the corresponding property is significant at 95 per cent confidence level ( p , 0.05)
3.4 Effect of coating parameters on bending rigidity The effects of coating parameters on bending rigidity in three main directions (warp, weft and bias) and also fabric bending rigidity of base and coated fabrics are shown in Figure 6. Regarding to the values given in Table VII, it is obvious that bending length of base fabrics increased with coating and bending length of coated fabrics changed with systematically changed coating parameters. The base fabrics were taken as control group for comparison. As shown in Figure 6, that coating causes stiffness by penetration of coating material into base fabric and increases were obtained
Table VI. Duncan’s test on the effects of coating parameters on bursting strength
IJCST 23,4 Bending rigidity (mg.cm)
214
25,000 Weft Fabric
15,000 10,000 5,000 0
Figure 6. The bending rigidity of base and coated fabrics
K0 PR1 PR2 PR3 PB1 PB2 PB3 SR1 SR2 SR3 SB1 SB2 SB3 S0 PR1 PR2 PR3 PB1 PB2 PB3 SR1 SR2 SR3 SB1 SB2 SB3 S S S S S S S S S S S S K K K K K K K K K K K K Test sample
Fabric code
Table VII. The bending length of base and coated fabrics/change in bending length after coating
Warp Bias
20,000
K0 KPR1 KPR2 KPR3 KPB1 KPB2 KPB3 KSR1 KSR2 KSR3 KSB1 KSB2 KSB3 S0 SPR1 SPR2 SPR3 SPB1 SPB2 SPB3 SSR1 SSR2 SSR3 SSB1 SSB2 SSB3
Warp
Bending length (cm) Weft
Bias
5.5 8.8 9.2 10.2 8.3 8.3 6.9 8.1 8.6 8.8 7.3 7.4 7.4 4.4 6.6 7.0 7.3 6.6 6.4 6.4 6.6 6.6 7.0 5.8 5.7 5.5
3.8 5.8 5.8 6.4 5.5 5.3 4.6 5.3 5.5 5.8 4.8 4.8 4.7 2.8 4.1 4.3 4.5 3.7 4.0 3.7 4.0 4.1 4.2 3.8 3.4 3.4
4.2 6.4 6.4 6.9 5.9 5.9 5.1 5.8 5.8 6.3 5.3 5.3 5.3 3.3 4.8 5.3 5.3 4.6 4.6 4.5 4.8 5.0 5.2 4.5 4.0 4.1
Change in bending length (%) Warp Weft Bias – 60.3 68.1 85.0 50.9 50.6 24.8 46.8 55.5 60.3 31.9 35.0 34.2 – 49.4 58.4 66.2 49.6 45.9 44.6 49.6 49.4 60.0 31.7 28.7 24.9
– 53.3 51.8 68.9 44.9 40.6 20.9 39.8 44.7 52.8 26.8 25.8 23.4 – 47.3 52.9 59.8 31.5 42.0 33.0 41.8 45.8 51.4 34.6 21.2 20.8
– 52.1 52.4 63.4 40.0 39.7 21.7 39.1 38.4 49.3 27.2 25.5 25.1 – 46.7 59.7 60.6 40.2 38.8 36.4 45.1 50.2 56.2 35.2 22.5 22.9
for the bending rigidity of coated fabrics. In that case, it can be pointed out that resin penetration is essential for stiffness and can be taken under control by making changes in coating technique and its production parameters. When the press magnitude of rotary screen coating rises up, increments in bending rigidity for KPR3 and SPR3
samples were determined in the study. For KPB3 and SPB3 samples, increase in blade contact angle causes decrease in bending rigidity according to resin penetration. In order to examine the effect of coating material, PU-coated fabrics shows higher bending rigidity than PU/silicone-coated fabrics. To compare the coating techniques, rotary screen coating provides higher bending rigidity due to being more efficient for much more penetration of coating material into fabric structure. We can see from Table VIII, the effects of all coating parameters (base fabric, coating material, coating technique and its production parameters) are statistically significant on bending rigidity of coated fabrics at 95 per cent confidence level. Although the effects of these coating parameters are statistically significant individually, the influence of interaction of coating material and production parameters is not ( p . 0.05).
Properties of coated fabrics
215
3.5 Effect of coating parameters on fabric abrasion resistance One can expect that both base fabrics showed great increments in abrasion resistance after coating, this is because coating prevents losses in fabric weight, regarded as abrasion resistance, as shown in Figures 7 and 8. When different abrasion cycles are taken into comparison, it is possible to say that 10,000 cycles did not make a noticeable change in fabric weight and in fabric appearance; but after 20,000 cycles, brightness and smoothness were observed on the surface of coated fabrics. Abrasion resistance of coated fabrics changed with the coating parameters. Based on Table IX, the results of variance analyses show that base fabric, coating material and coating technique have statistically significant effects on abrasion resistance of coated fabrics for 20,000 abrasion cycles. For 10,000 cycles abraded coated fabrics, the effects of coating parameters except for base fabric are not statistically significant on abrasion resistance at 95 per cent confidence level ( p . 0.05).
Source of variation Base fabric Coating material Coating technique Production parameters Base fabric £ coating material Base fabric £ coating technique Coating material £ coating technique Base fabric £ coating material £ coating technique Base fabric £ production parameters Coating material £ production parameters Base fabric £ coating material £ production parameters Coating technique £ production parameters Base fabric £ coating technique £ production parameters Coating material £ coating technique £ production parameters Base fabric £ coating material £ coating technique £ production parameters
Bending rigidity Warp Weft Bias Fabric 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.947 0.488 0.000 0.000 0.000
0.000 0.000 0.000 0.042 0.000 0.000 0.018 0.122 0.263 0.830 0.060 0.000 0.000 0.000
0.000 0.000 0.000 0.083 0.000 0.000 0.002 0.001 0.480 0.123 0.255 0.000 0.000 0.011
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.828 0.039 0.000 0.000 0.000
0.000 0.000 0.003
0.000
Notes: The p-values of Duncan’ test are shown in this table; the effect of corresponding variable on the corresponding property is significant at 95 per cent confidence level ( p , 0.05)
Table VIII. Duncan’s test on the effects of coating parameters on bending rigidity
IJCST 23,4
5 Weight loss (%)
216
6
10,000
4
20,000
3 2 1
Figure 7. The abrasion resistance of K-coded base and coated fabrics
0
K0
R1
KP
R2
KP
R3
KP
B1
KP
B2
KP
R1 SR2 B3 K KS KP Test sample
R3
KS
B1
KS
B2
KS
B3
KS
12
Weight loss (%)
10 10,000
8
20,000
6 4 2
SS B3
SS B1 SS B2
SS R3
SS R1 SS R2
SP B3
SP B1 SP B2
SP R2 SP R3
SP R1
0 S0
Figure 8. The abrasion resistance of S-coded base and coated fabrics
Test sample
3.6 SEM analysis Surface morphologies of 20,000 cycles-abraded base and some coated fabrics (KPR3, KSR3, KPB3, KSB3; SPR3, SSR3, SPB3, SSB3) were studied under SEM at the magnification of 100 times. Such observations show that there is a separation of broken fibers from the coating resin as a result of abrading effect even though weight losses after 20,000 cycles were obtained very low besides brightness and smoothness were shown on the surface (Figures 9 and 10). To examine in details, there is a poorer adhesion between resin and substrate for coated fabrics, which are produced by direct coating rather than rotary screen coating. Fibers are stuck together firmly by PU/silicone material that provides better adhesion between substrate and coating resin. 4. Conclusion In this study, the effects of coating parameters on mechanical properties of coated fabrics have been investigated. It is necessary to emphasize that mechanical properties of coated fabrics are not similarly influenced by coating components. Increases in breaking strength of almost all fabrics are obtained by coating material application and changes in tensile properties are affected by all coating parameters.
Source of variation Base fabric Coating material Coating technique Production parameters Base fabric £ coating material Base fabric £ coating technique Coating material £ coating technique Base fabric £ coating material £ coating technique Base fabric £ production parameters Coating material £ production parameters Base fabric £ coating material £ production parameters Coating technique £ production parameters Base fabric £ coating technique £ production parameters Coating material £ coating technique £ production parameters Base fabric £ coating material £ coating technique £ production parameters
Abrasion resistance 10,000 abrasion 20,000 abrasion cycles cycles 0.017 0.183 0.128 0.434 0.163 0.145 0.624 0.535 0.315 0.983 0.921 0.033 0.017
0.012 0.000 0.038 0.415 0.000 0.493 0.230 0.624 0.001 0.071 0.067 0.024 0.022
0.029
0.000
0.214
0.015
Notes: The p-values of Duncan’ test are shown in this table; the effect of corresponding variable on the corresponding property is significant at 95 per cent confidence level ( p , 0.05)
Breaking elongation decreases due to stiffness of coated fabrics as a result of coating process. Tear strength is affected by all coating parameters and dramatically decreases due to restriction of yarn mobility in fabric structure. Changes in bursting strength are not similar for the base fabrics and bursting strength is affected positively or negatively by production parameters. It can be pointed out that coating causes fabric stiffness and more rigid structure, results in great increases in bending rigidity of fabrics. With the change of coating technique and adjustments of process parameters, the penetration of coating resin can be taken under control. Coating improves abrasion resistance of fabrics by reducing the losses of fabric weights, which comes into being due to abrading effect. However, the slight changes such as brightness and smoothness are observed in physical appearance. SEM investigations showed that coating enhanced surface resistance of base fabrics, but its efficiency depends on the coating parameters. It can be concluded that base fabric and coating materials have statistically significant influence on mechanical properties, but the effects of coating technique vary with test direction and the effects production parameters are statistically significant except for abrasion resistance at 95 per cent confidence level. All results of variance analysis based on base fabrics are shown (Table X) to figure out which corresponding coating parameter has significant effect on corresponding property. To examine in details, the results of variance analysis are divided into two main groups based on base fabrics because base fabric has found to be significant for all measured properties. Consequently, coating material affects almost all properties of two base fabrics, except for especially all parameters of breaking elongation of S0-coded base fabric. The effect of coating technique changes with the test direction
Properties of coated fabrics
217
Table IX. Duncan’s test on the effects of coating parameters on abrasion resistance
IJCST 23,4
218
(a)
Figure 9. SEM micrographs of K-coded coated fabrics after 20,000 abrasion cycles
(b)
(c)
(d)
(e)
Notes: (a) K0; (b) KPR3; (c) KSR3; (d) KPB3; (e) KSB3
on tensile properties for both base fabrics and is not significant on abrasion resistance for both 10,000 and 20,000 abrasion cycles of S0-coded base fabric. The influence of both coating material and coating technique are significant on tear strength, bursting strength and all parameters of bending rigidity. Finally, the effects of production
Properties of coated fabrics
219
(a)
(b)
(c)
(d)
(e)
Notes: (a) S0; (b) SPR3; (c) SSR3; (d) SPB3; (e) SSB3
Figure 10. SEM micrographs of S-coded coated fabrics after 20,000 abrasion cycles
IJCST 23,4 Property Breaking strength
220
Table X. The summary of variance analysis results based on base fabrics
K0 S0 Coating Coating Production Coating Coating Production Parameters material technique parameters material technique parameters
Warp Weft Bias Breaking elongation Warp Weft Bias Tear strength Warp Weft Bursting strength Bending rigidity Warp Weft Bias Abrasion resistance 10,000 cycle 20,000 cycle
* * * * * ** * ** * * * * * *
* ** * * ** ** * * * * * * * *
* ** ** * * ** * * * * ** ** ** *
* * * ** ** ** * * * * * * ** *
* ** ** ** ** ** * * * * * * ** **
* ** ** ** ** ** ** ** ** * ** ** ** *
Notes: *Statistically significant at 95 percent confidence level; * *not statistically significant at 95 percent confidence level
parameters vary with the base fabric and when compared with the other coating parameters, it is less significant on mechanical properties of coated fabrics. References Abbott, N.J., Lannefeld, T.E., Barish, L. and Bpysson, R.J. (1971), “A study of tearing in coated cotton fabrics”, Journal of Industrial Textiles, Vol. 1 No. 1, pp. 4-17. Armag˘an, O.G. and Karakas¸, H. (2007), “A study about physical performance of knit fabric laminated structure”, Proceedings of the 3rd International Technical Textiles Congress, Turkey, 1-2 December, pp. 178-85. ASTM D 751-06 (2006a), Standard Test Methods for Coated Fabrics – Breaking Strength (Cut Strip Method), ASTM International, West Conshohocken, PA. ASTM D 751-06 (2006b), Standard Test Methods for Coated Fabrics – Bursting Strength (Ring Clamp Method), ASTM International, West Conshohocken, PA. ASTM D 751-06 (2006c), Standard Test Methods for Coated Fabrics – Tear Strength (Trapezoidal Test), ASTM International, West Conshohocken, PA. ASTM D 1388-08 (2008), Standard Test Method for Stiffness of Fabrics (Cantilever Method), ASTM International, West Conshohocken, PA. Chen, S., Ding, X. and Yi, H. (2007), “On the anisotropic tensile behaviors of flexible polyvinyl chloride-coated fabrics”, Textile Research Journal, Vol. 77 No. 6, pp. 369-74. Cho, J.W., Jung, Y.C., Chun, B.C. and Chung, Y.C. (2003), “Water vapour permeability and mechanical properties of fabrics coated with shape memory polyurethane”, Journal of Applied Polymer Science, Vol. 92, pp. 2812-16. Farboodmanesh, S., Chen, J., Mead, J.L. and White, K.D. (2005), “Effect of coating thickness and penetration on shear behavior of coated fabrics”, Journal of Elastomers and Plastics, Vol. 3, pp. 197-227.
Fung, W. (2002), Coated and Laminated Textiles, Woodhead Publishing, Cambridge. Hu, H. and Xu, Y. (2008), “Tearing properties of coated multi-axial warp knitted fabric”, AUTEX Research Journal, Vol. 8 No. 1, pp. 13-16. ISO 5084 (1996), Textiles – Determination of Thickness of Textiles and Textile Products, ISO, Geneva. ISO 9237 (1995), Textiles – Determination of the Permeability of Fabrics to Air, ISO, Geneva. Kut, D. and Gu¨nes¸og˘lu, C. (2005), “Comparison of performance properties of polyurethane and polyacrylate coated fabrics”, Tekstil Maraton, Vol. 80, pp. 62-5 (in Turkish). Luo, Y., Hong, H. and Fangueiro, R. (2008), “Tensile and tearing properties of bi-axial warp knitted coated fabrics”, AUTEX Research Journal, Vol. 8 No. 1, pp. 17-20. Masteikaite, V. and Saceviciene, V. (2005), “Study on tensile properties of coated fabrics and laminates”, Indian Journal of Fibre & Textile Research, Vol. 30, pp. 267-72. ¨ ner, E. (2007), “Coating in textiles”, available at: www.uzaktanegitimplatformu.com (accessed O 15 March 2009). Rosato, D.V., Rosato, D.V. and Rosato, M.V. (2004), Plastic Product Material and Process Selection Handbook, Elsevier, Oxford. Rotary Screen System (2011), available at: www.coatema.de/eng/lab_solutions/modular_coating. php (accessed March 2011). Sen, A.K. and Damewood, J. (2001), Coated Textiles: Principles and Applications (Illustrated Edition), Technomic Publishing, Lancaster, PA. Corresponding author Yasemin Bulut can be contacted at:
[email protected]
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Properties of coated fabrics
221
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IJCST 23,4
Disposable hydrophilic antimicrobial laminated nonwoven bed sheet
222
Murat Onan Uludag Exporters’ Union, Bursa Textile and Confection Research and Development Center, Bursa, Turkey, and
Gulay Ozcan and Hakan Unal Textile Technology and Design Faculty, Istanbul Technical University, Istanbul, Turkey
Abstract
International Journal of Clothing Science and Technology Vol. 23 No. 4, 2011 pp. 222-231 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111136485
Purpose – The purpose of this paper is to develop a unique disposable bed sheet design which reduces infection risk and other related problems from patient to patient and others during staying period at hospitals. Design/methodology/approach – The unique disposable bed sheet consists of three layers which are laminated to each other by hot-melt technique. Upper and lower layers are different weights of 100 per cent polypropylene produced by spunbond technology. Plasma technology has been used to make the surface of the spunbond polypropylene sheets hydrophilic. Additionally, thermal bond 100 per cent polypropylene sheets, which have hydrophilic surfaces already due to chemical finish have been also used as upper layer. As core layer, different weights of 100 per cent viscose sheets, which have high liquid-absorption capacity have been used. All three layers have been laminated by hot-melt technique using etylene vinyl acetate interlayers between them. Antimicrobial effect has been achieved by the impregnation of silver and antibiotic-based chemicals onto the hydrophilic surface of upper layers. Quality control and performance tests of all these works have been performed according to ISO and BS norms. Findings – It is possible to have very good liquid suction capacity together with superb comfort properties, thanks to its viscose intermediate sheet and excellent wetback values. Moreover, it is initially cheap, hygienic and has enough strength against breaking and tearing. Research limitations/implications – Cheaper antimicrobial agents and different application amounts should be checked. Also, durability of the hydrophilicity given by plasma treatment has to be checked. Additionally, dermatological tests should be applied. Practical implications – It is expected that the infection risk at hospitals will be reduced. Moreover, hospitals will be able to use hygienic bed sheets, which would be preferable to the hospital management. Additionally, this unique design can be used for patients at home or for injured animals in veterinary clinics. Social implications – Additional staying period due to hospital infections and infections from patient to patient/hospital personnel/visitors/other people will be reduced. Moreover, it is expected that life quality will be raised and dead ratio will be decreased. Beside this, manpower loss and increasing costs due to hospital infections will be prevented. Originality/value – Design is new and unique. It has practical and social implications. Keywords Hospital bedding, Laminates Paper type Research paper
1. Introduction Despite of improvements in service quality, infections on patients, who stay at hospitals are still being observed worldwide and the risk of dead is being increased. Naturally, hospital personal is also effected by this situation. Hospital infections are important threats both for patients and environment (Ertek, 2008). It is known that only in the USA, two million people per year are effected by infections via hospitals and 90,000 people are dead. Hospital infections cost approximately 6.7 billion USD per year in the USA. This is 1.7 billion USD in England. In Norway, which has population of four million people only, this number is 132 million USD (Yalc¸ın, 2008). In Turkey, it is calculated that hospital infections cost 1,500 USD per patient. Staying period of the patients in hospitals because of infections varies from four days to 34 days (U¨nal, 2009). Staying periods in hospitals for different countries are shown in Table I.
Disposable nonwoven bed sheet 223
2. Material and method The structure and features of the components of developed product are shown in Figures 1 and 2: . antimicrobial, front face hydrophilic, back face hydrophobic, 100 per cent Polypropylene (PP) nonwoven upper layer; . 100 per cent cellulose viscose (CV) (viscose fiber), nonwoven medium layer which has high liquid-absorption capacity; . fully hydrophobic 100 per cent PP nonwoven bottom layer which prevents leakage; and . ethylenevinylacetate (EVA)-based net formed hot-melt material which bonds three layers. 2.1 Material 2.1.1 Nonwoven sheets. Nonwoven sheets used in this study and their functions are shown in Table II. Many multilayer combinations have been prepared by using Study
Country
1974 1980 1991 1993 1995 1997 1997 1998 1998 1999 1999 2001 2005
ABD ABD Hong Kong ˙Ispanya Tu¨rkiye Tu¨rkiye Fransa Trinidad Norvec¸ Meksika Meksika ˙Ingiltere Tayvan
(Westwood) (Haley) (French) (Diaz-Molina) (Erbaydar) (Yalc¸ın) (Leroyer)a (Orrett) (Andersen) (Navarette)a ( J Munoz)a (Plowman) (Chen) a
Note: Pediatri Source: U¨nal (2009)
Additional stay (day) 22.0 13.4 23.4 4.3 10.6 20.3 5.2 33.5 4.0 9.6 7.4 11.0 18.2
Table I. Additional staying days because of hospital infections
IJCST 23,4 4 1
224
3 4
2
Figure 1. Original sample
2010 2 9
1 4 2 4
Figure 2. Appearance of laminated sheets
3
Nonwoven type
Table II. Nonwoven sheets used in this study and their functions
Weight (g/m2)
% 100 PP (Spunbond)
15
% 100 PP (Spunbond)
25
% 100 PP (Spunbond)
35
% % % % % %
18 25 20 30 35 50
100 100 100 100 100 100
PP (Thermal bond) PP, Thermal bond CV CV CV CV
Source: U¨nal (2009)
Description and function As upper and bottom layer hydrophilic/hydrophobic and antimicrobial/microbial As upper and bottom layer hydrophilic/hydrophobic and antimicrobial/microbial As upper and bottom layer hydrophilic/hydrophobic and antimicrobial/microbial Only as upper layer hydrophilic and antimicrobial Only as upper layer hydrophilic and antimicrobial As middle layer high suction capacity As middle layer high suction capacity As middle layer high suction capacity As middle layer high suction capacity
nonwoven types and all of them have been numbered. Then, all of them have been tested according to international ISO and BS norms. 2.1.2 Antimicrobial chemicals. Antimicrobial chemicals and application conditions are shown in Table III. 2.2 Method 2.2.1 Hydrophilization of upper PP nonwoven sheets by plasma method. Cold oxygen plasma method under atmospheric pressure has been used to modify the surfaces (Sparavigna, 2006). Plasma conditions are shown in Table IV. PP nonwoven sheets which will be used as upper layers have been passed three times through the machine under the same conditions for 20 s each (U¨nal, 2009). 2.2.2 Lamination (hotmelt technique). This process has been realized via a professional press. The nonwoven sheets have been replaced one on another according to combinations done before. EVA-based hotmelt net has been replaced in each nonwoven pair sheets to bond them strictly. Then these prepared multilayer combinations have been pressed by hot press at 808C.
Disposable nonwoven bed sheet 225
3. Outcomes and interpretations 3.1 Applied tests and reference standards in the study Applied tests and reference standards in the study are shown in Table V. Regarding different multilayer nonwoven combinations, which have lower than 60 s mean liquid transfer values, five sample has been chosen because of having excellent wetback values (below 0.5 g): samples 1, 2, 7, 8 and 10. As a result of this, other tests have been applied on these samples by omitting rest samples (Figures 3-6).
Nano silver-based recipe ISys AG (g/l) Reputex 20 (g/l) Acetic acid (85%) (g/l) Impregnation unit Machine speed (m/dk) Cylinder pressure (bar) Total flotte (l) Flotte temperature (8C) Pick up (%)
Polihegzametilenbiguanid-based recipe
2.0 – pH 5.0-5.5 KU¨STERS foulard 20 2.4 50 20-25 40-45
– 20.0 pH 7.0-7.5
Table III. Antimicrobial chemicals and application conditions
Sources: Crabston and Gao (2008); Skirlo and Spaniol (2008)
Gas type Pressure Voltage (V) Machine speed (m/s) Source: U¨nal (2009)
O2 Atmosferik 3,500 15
Table IV. Plasma conditions
IJCST 23,4
Applied test
Reference standard
226
Weight measurement Thickness measurement Tensile strength and elongation Tearing strength Wetback Liquid transfer Air permeability Water vapour permeability Antimicrobial efficiency
TS 251 TS 4117 EN ISO 2589 TSE EN ISO 13934-1 TSE EN ISO 13937-2 EDANA 151.3.02 EDANA 150.5.02 TS 391 EN ISO 9237 BS 7209 AATCC 100 (Staphylococcus aureus)
Table V. Applied tests and reference standards in the study
Source: Cireli et al. (2007)
Mean liquid transfer time (s)
60
Figure 3. Mean liquid transfer time values (5-ml test liquid)
40 30 20 10 0
1 (5 ml)
2 (5 ml) 7 (5 ml) 8 (5 ml) 10 (5 ml) F (5 ml)
R (5 ml)
60 50 40 30 20 10 m l) I( 22 m l) III (2 2 m l) V I( 22 m l) V II (2 2 m l) IX (2 2 m l) X II (2 2 m l)
m l)
(2 2 U
(2 2 D
(2 2 C
(2 2
m l)
0 m l)
Mean liquid transfer time (s)
Disposable bed sheet combinations
A
Figure 4. Mean liquid transfer time values (22-ml test liquid)
50
Disposable bed sheet combinations
As we see in Figures 7 and 8, mean tear and tensile strength values of the samples 1, 7 and 10 are moderate while Samples 2 and 8 is better. Despite this, it is not expected to have any problem because of having tearing in width direction and being disposable material (Figures 9 and 10).
Disposable nonwoven bed sheet
Mean liquid transfer time (s)
1.6 1.4 1.2 1 0.8
227
0.6 0.4 0.2
R
(5
m l)
m l) F
(5 10
8
(5
m l)
m l) (5
m l) 7
(5
m l) (5 2
1
(5
m l)
0
Disposable bed sheet combinations
Figure 5. Mean wetback values (5-ml test liquid)
Mean wetback values (g)
2.5 2 1.5 1 0.5
V I( 22 m l) V II (2 2 m l) IX (2 2 m l) X II (2 2 m l)
l) (2
2
m
m l) III
I( 22
m l)
U
(2 2
m l)
m l)
(2 2 D
(2 2 C
A
(2 2
m l)
0
Mean tearing strength (N)
Disposable bed sheet combinations
20 18 16 14 12 10 8 6 4 2 0
1
2
7
8 10 A C D F R U I III VI VII IX XII Disposable bed sheet combinations
Figure 6. Mean wetback values (22-ml test liquid)
Figure 7. Mean tearing strength values
228
160 Mean tearing strength (N)
IJCST 23,4
Figure 8. Mean tensile strength values
140 120 100 80 60 40 20 0
1
2
7
8 10 A C D F R U I III VI VII IX XII Disposable bed sheet combinations
Mean air permeability values (L 105/m2.h)
38
Figure 9. Mean air permeability values
36 35 34 33 32 31 30 29 28
Mean water vapour permeability values (g/m2.h)
Figure 10. Mean water vapour permeability values
37
1
2 7 8 Disposable bed sheet combinations
10
1
2 7 8 Disposable bed sheet combinations
10
38 37 36 35 34 33 32 31 30 29 28
Air and water vapour permeability values of the samples 1, 2, 7, 8 and 10 are very good. Naturally, it is expected that these disposable bed sheets will be comfortable for patients. Antimicrobial tests have been done according to AATCC 100 standard by using Staphylococcus aureus bacteria, which is most common one in hospitals (Table VI).
Disposable nonwoven bed sheet 229
3.2 Cost analyze Table VII shows comparison of classical and disposable bed sheets. 4. Conclusions Table VIII summarizes the test results: (1) The best results belong to the Sample 8. Then, Sample 7 is coming. Moreover, the sample 1 is also usable despite of having lower tensile and tear strength values compare to samples 8 and 7. (2) When we look at successful samples again, we see that the samples are consist of light weight nonwoven layers as shown below: . plasma and polihegzametilenbiguanid applied PP upper layer 15 g/m2 þ CV medium layer 20 g/m2 þ bottom layer 15 g/m2 (sample 1); . plasma and nanosilver applied PP upper layer 15 g/m2 þ CV medium layer 20 g/m2 þ bottom layer 15 g/m2 (sample 7); and . plasma and nanosilver applied PP upper layer 15 g/m2 þ CV medium layer 35 g/m2 þ bottom layer 15 g/m2 (sample 8). (3) We can say that costs of the disposable bed sheets will be lower because of being lightweight structure. Beside this, the disposable bed sheet will be more flexible and easy to use.
Bacteria reduction after 24 h (%) Treated Untreated
Antimicrobial chemical ISys AG (nanosilver) Reputex 20 (Polihegzametilenbiguanid)
99.9 99.9
Classical hospital bed sheet Structure Usage Initial cost (TL) (180 £ 220 cm) Final cost for 30 washing cycle (TL) Source: Cireli et al. (2007)
100% CO, 50 thread/ cm total density, 30 times washing and reusing 7.7 0.53
0 0
Table VI. Antimicrobial test results
Disposable hydrophilic antimicrobial laminated nonwoven bed sheet (samples 1/7/8) 50-60% PP þ 50-40% CV, nonwoven Disposable 2, 31/2, 39/2, 77 –
Table VII. Comparison of classical and disposable bed sheets
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230
Table VIII. Summary of the test results
Liquid transfer U XII 2 IX 8 VI C 1 III F VII 7 D R I 10 A
Wetback
Tensile strength
8 7 1 2 10 A F D VII I C R IX U VII VI III
C F D I XII A 8 VII 2 IX VI III U R 7 1 10
Tearing Air Water vapour strength Elongation permeability permeability F C XII 10 D VI A I R U VII 7 8 1 IX III 2
10 A 8 2 D VII F C I VI 1 7 IX III XII U R
8 7 1 2 10
7 8 10 1 2
Note: From the best to the worst
(4) It is significant that all the successfull samples are plasma-treated samples. In other words, chemically treated, thermal-bond, hydrophilic samples were not good enough especially regarding wetback values. (5) Both polihegzametilenbiguanid and nanosilver-based antimicrobial agents are effective. (6) When we investigate costs of successful disposable bed sheets, we see that they are approximately three times cheaper than classical cotton made bed sheets regarding initial costs, but after several washings classical bed sheet is getting cheaper. Considering 30 washing cycles, the classical bed sheet is approximately four times cheaper. Despite of that, we believe that this cost difference can be ignored if we care about infection risk and other related problems such as man power loss, decreased life quality, raised dead ratio and additional staying expenses. References Cireli, A., Kılıc¸, B., Sarııs¸ık, M. and Okur, A. (2007), “Tıbbi Tekstiller ve Test Yo¨ntemleri, 5”, Ulusal Sterilizasyon Dezenfeksiyon Kongresi, Antalya. Crabston, R. and Gao, Y. (2008), “Recent advances in antimicrobial treatments of textiles”, Textile Research Jounral, Vol. 78 No. 1, pp. 60-8. Ertek, M. (2008), “Hastane Enfeksiyonları: Tu¨rkiye Verileri”, Hastane Enfeksiyonları Koruma Ve ¨ niversitesi Cerrahpas¸a Tıp Faku¨ltesi, ˙Istanbul, Kontrol Sempozyumu, ˙Istanbul U pp. s.9-s.14. Skirlo, S. and Spaniol, A. (2008), Basic Information and Pratical Experiences on Silver Ions Based ¨ rttemberg, Antimicrobial Agents, Finishing Department CHT R. Beitlich GmbH, Baden-W pp. s.1-s.32.
Sparavigna, A. (2006), Plasma Treatment Advantages for Textiles, Dipartimento di Fisica, Politecnico di Torino, Torino, pp. S.1-S.16. ¨ Unal, H. (2009), “Production of disposable, hydrophilic and antibacterial polypropylene nonwoven sheets”, Master thesis, Istanbul Technical University, Textile Technologies and Design Faculty, pp. s.73-s.76. Yalc¸ın, N. (2008), “Hastane Enfeksiyonları Maliyet Analizi”, Hastane Enfeksiyonları Koruma Ve Kontrol Sempozyumu, ˙Istanbul U¨niversitesi Cerrahpas¸a Tıp Faku¨ltesi, ˙Istanbul, Ocak, pp. s.15-s.22. Corresponding author Murat Onan can be contacted at:
[email protected]
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Disposable nonwoven bed sheet 231
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IJCST 23,4
A study on the beam pattern of ultrasonic sensor integrated to textile structure
232
Senem Kursun Bahadir University of Lille-North of France, Lille, France ENSAIT, Roubaix, France and Textile Engineering Department, Istanbul Technical University, Istanbul, Turkey
Fatma Kalaoglu Textile Engineering Department, Istanbul Technical University, Istanbul, Turkey
Sebastien Thomassey University of Lille-North of France, Lille, France and ENSAIT, Roubaix, France
Irina Cristian The “Gheorghe Asachi” Technical University of Iasi, Iasi, Romania, and
Vladan Koncar University of Lille-North of France, Lille, France and ENSAIT, Roubaix, France Abstract Purpose – During the past decades, several researchers have introduced devices that use sonar systems to detect and/or to determine the object location or to measure the distance to an object using reflected sound waves. The purpose of this paper is to use sonar sensor with textile structure and to test it for detection of objects. Design/methodology/approach – In this study, a sonar system based on intelligent textiles approach for detection of objects has been developed. In order to do this, ultrasonic sensor has been integrated to textile structures by using conductive yarns. Furthermore, an electronic circuit has been designed; PIC 16F877 microcontroller unit has been used to convert the measured signal to meaningful data and to assess the data. The algorithm enabling the objects detection has also been developed. Finally, smart textile structure integrated with ultrasonic sensor has been tested for detection of objects. Findings – Beam shape is presented related to identified object and compared with the actual one given in sensor’s datasheet in order to test the efficiency of the proposed method of detection. The achieved results showed that the determined beam pattern matches with the actual one given in its datasheet. Therefore, it can be concluded that the integration of sensor was successful. Originality/value – This is the first time in the literature that a sonar sensor was integrated into textile structure and tested for detection of objects. Keywords Sensors, Textiles, Intelligent agents, Ultrasonic devices, Microcontrollers Paper type Research paper International Journal of Clothing Science and Technology Vol. 23 No. 4, 2011 pp. 232-241 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111136494
1. Introduction Advanced researches in the electronic industry have led sensor and computing technologies to miniaturize and reduce cost. Owing to the miniaturization and reduction
cost of electronics, the field of e-textiles and wearable electronics is more and more extending. Thus, far, new sensing elements, functional fibers, flexible technologies, new chemical sensors, microelectromechanical systems actuators, etc. are now becoming a part of our environment by embedding them into textiles. Textiles have an indispensable role in our everyday life and recently, e-textiles start to take a great role in the wearable computing, health monitoring, smart human-machine interface, etc. (Katragadda and Xu, 2008). They generally made by integrating rigid/flexible electronics (sensors, actuators and cameras) to textile structures by using conductive materials like polymers, yarns, etc. (Post and Orth, 1997; Parker et al., 2002; Luthy et al., 2002; Weber et al., 2003; Jung et al., 2003; Park et al., 2002). In wearable sensor framework; although researchers have focused on using accelerometers, temperature, pressure sensors for activity detection like respiratory, electrocardiogram, body heat, contact pressure, other wearable sensors for physiological data have also been widely used. Furthermore, in nowadays general research trend is toward to use wireless communication, thus global positioning system, radio-frequency identification technologies are combined with these wearable e-systems (Kim et al., 2008; Mathie et al., 2004; Ling and Stephen, 2004; Krause et al., 2006; Morris and Paradiso, 2002; Oliver et al., 2006a, b; Ermes et al., 2008; Wade and Asada, 2007; Taccini et al., 2004; Subramanya et al., 2006; Maurer et al., 2006). In our wearable e-textile system, sonar sensor was used to detect the objects and to measure the distance to an object in the environment. This is the first time in the literature that sonar sensor was integrated to textile structure and tested for detection of objects. Sonar is a kind of device used for detecting, locating, determining objects or measuring the distance through the use of reflected sound waves. The frequencies used in sonar systems change from infrasonic to ultrasonic. The term ultrasonic refers to frequencies above that of audible sounds, which humans could not hear and it nominally indicates anything over 20,000 Hz (Cheol-Hong et al., 2007). In the nature, bats, dolphins and some other species communicate and navigate in the range of 20-100 kHz (Sethu Selvi et al., 2008). In industrial applications, ultrasonic sensors are widely used for distance measurement, proximity detection, object localization, mobile robot guidance, etc. (Ohtani and Baba, 2006; Llata et al., 2008) and recently for the process control of liquids to measure the concentrations, levels and flows through the use of reflected sound waves. They are widely preferred in robotic applications because of their low price, high efficiency and relatively simple structure (Berndhenning et al., 2000; Jongkyu et al., 2010; Puttmer, 2006). In our case, this ultrasonic sensor integrated e-textile structure can be considered for the applications like directional navigation where the visual sense is restricted such as lacking a wide field of view or visually impaired people or the overloaded drivers, cockpits, etc. 2. Ultrasonic signal processing 2.1 Distance measurement by ultrasonic sensor In sonar systems, electrical impulse is converted into sound waves and the sonar equipment as shown in Figure 1 picks up the echoes of reflected sound waves. An ultrasonic sensor wave is a sound speed of about c ¼ 344 m/s in 208C air at sea level. Distance measurement in ultrasonic sensor is based on the “time of flight” principle (Peter and Schweinzer, 2006). That means, the distance to an object is identified by the measurement of the time from transmission of a pulse to reception. In other words,
Beam pattern of ultrasonic sensor
233
IJCST 23,4
cted
le Ref
e wav
ect
Obj
234
r
eive
r/rec
de Sen
ave al w
in Orig
ance
Dist
Figure 1. Principle of active sonar
the distance (L) to an object is calculated by equation (1) (t: arrival time after reflection) (Cheol-Hong et al., 2007): L ¼ c * t=2 ðmÞ
ð1Þ
2.2 Object direction measurement There is a difficulty in measuring the azimuth of an object by using a single ultrasonic sensor. Figure 2 shows a drawing of the geometrical relationship in measuring azimuth of objects where they are vertically arranged at the same distance to sensor. Let us define O1, O2, O3 and O4 as objects and L1, L2, L3, and L4 as the distances measured, respectively, from the objects O1, O2, O3 and O4. The azimuth of objects can be expressed by using triangle rule as following: For object 2 : For object 3 :
u12 ¼ cos21 ðL1=L2Þ 21
u13 ¼ cos ðL1=L3Þ
ð2Þ ð3Þ
Since object 4 is outside of the sensor’s detection range, the azimuth value of this object cannot be determined by sensor. 3. Experiments 3.1 Materials and integration of sensor methodology In this study, LV-MaxSonarw-EZ3e (Maxbotix Inc., 2010) ultrasonic sensor was chosen due to its small dimensions and low power requirements, 2.5 to 5.5 V supply with low (2 mA) typical current draw. Figure 3 shows the ultrasonic sensor with its circuit. This ultrasonic sensor enables us to detect objects or to measure the distance through the use of reflected sound waves and it gives information from six to 254 in. To integrate the ultrasonic sensor into textile structure, 100 per cent stainless steel yarn with a lineal resistance of , 15 V/m was used to form electric circuit in the woven
Beam pattern of ultrasonic sensor
y Ultrasonic sensor
θ14 Sensor detection region
235
O1 L12
L4
O2
L1
L3
L2
θ12 θ13
Objects L13
O3
O4
Figure 2. Geometrical relationship in measuring azimuth of objects by using ultrasonic sensor
x
L14
F
G
C
N GND +5 B
TX
E
RX AN PW
Orange dot
H
D
M L
A
fabric. Besides, to form non-conductive area in the woven fabric, polyester microfibers with a yarn count of 330 dtex were used. To prevent the short circuits, fabric sample was designed as double-woven fabric and conductive yarns were hidden in the middle layer of structure as shown in Figure 4. The position of conductive yarns in the woven fabric was decided in order to match with the ground, common-collector voltage (Vcc) and analog voltage output of a given sensor device (Figure 5). Furthermore, to construct electrical circuit and to connect sensor with fabric, loops were formed among conductive yarns and snap fasteners were sewn onto these loops (Figure 6). 3.2 Experimental set up Measurements were performed using TekoPIC Programming Experimental Set Kit as shown in Figure 6(a). Our system includes power supply, ultrasonic sensor integrated
Figure 3. LV-MaxSonarw-EZ3e (Maxbotix Inc.) ultrasonic sensor
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236
Figure 4. 3D representation of the double-woven cloth (TexGen software)
tive duc Con arn y
G
Figure 5. Sample overview: conductive yarns corresponding with sensor ground, Vcc and analog voltage output pins
2.54 mm 7.62 mm
F
N GND +5 TX
Conductive yarn Conductive yarn Conductive yarn
E
RX AN PW
C
B
Orange dot
H
M
D L
A
Objects
Power supply
LCD display
Reset
Trigger input
Counter and interface and clock
Ultrasonic transmitter and ultrasonic receiver
Microcontroller in ultrasonic sensor circuit
Interface
PIC16F877 microcontroller
Figure 6. (a) Experiment set-up; (b) block diagram of system
Microcontroller 16F877
TekoPIC experimental kit VAN Vcc GND (V = 0)
(a)
Test sample
LCD display
(b)
to textile structure, microcontroller and a liquid crystal display (LCD) panel. To control the system, 16F877 peripheral interface microcontroller was used. Its code was written in the PIC C language by using MPLABwIDE software and then, to compile to assembler the HI-TECH Cw Compiler was used. LCD screen was used to display the distance values to an object. The block diagram of system is shown in Figure 6(b). As soon as the sensor is triggered, ultrasound will be transmitted and if any object is presented within working range, the ultrasound will be reflected back. A counter using 40 KHz clock frequency
measures the time taken by sensor from transmission of a pulse to reception. For continuous distance measurement, sensor is triggered at a regular time interval and accordingly, counter should be reset (Niranjan et al., 2004). Finally, by this control system, we have conducted a study to determine the working range of sensor between 50 cm and 2.5 m. 4. Results To determine the beam pattern of given ultrasonic sensor, experiments were conducted as shown in Figure 7, according to proposed experiment set-up above. First, consider the ultrasonic sensor is positioned at (0, 0) and to detect the border of working range, object is positioned to a distance starting from (0, 50) to (x, 250) in cm. Measurements were repeated in every 5 cm starting from 50 to 250 cm of y-axis. Then, the actual position of object at the border of working range was compared with the one measured by the sensor. Table I shows the comparison of actual distance and measured distance to an object. According to this table results, beam pattern of ultrasonic sensor integrated to textile structure was determined as shown in Figure 8(a). Furthermore, determined beam pattern of sensor was compared with the sensor’s beam pattern in its datasheet (Figure 8(b)). It is clear from the figure that the beam pattern that we determined in our study is similar to the sensor’s beam pattern given in its datasheet (Maxbotix Inc., 2010). Furthermore, achieved results show that the error between actual and measured distance increases as the distance to an object increases. If the object is in the range of 50-100 cm, the error will be 0-5 per cent and if the object is in the range of 200-250 cm, then the error will increase to 13-15 per cent (Figure 9).
Beam pattern of ultrasonic sensor
237
5. Conclusion In this study, for the first time in the literature, ultrasonic sensor is successfully integrated to textile structure. To integrate the sensor, a double-woven fabric was designed and to satisfy electrical connection in the fabric, 100 per cent stainless steel yarn was used as a conductive yarn. Then to observe the working range of sensor, fabric was connected with a control system that includes: power supply, microcontroller x (cm)
Object
d (0.0) Sensor
y (cm) 50
100
150
200
250
Figure 7. Experimental procedure to determine border of working range of sensor
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Table I. Results of experiments at the border of working range of sensor in one direction
Measurement no. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41
Position of object (x, y)
Actual distance (d) (cm)
Measured distance (d) (cm)
jErrorj
jErrorj%
(19, 50) (20, 55) (22, 60) (23, 65) (24, 70) (26, 75) (25, 80) (26, 85) (27, 90) (27, 95) (28, 100) (29, 105) (30, 110) (31, 115) (31, 120) (30, 125) (29, 130) (30, 135) (32, 140) (33, 145) (36, 150) (37, 155) (38, 160) (37, 165) (41, 170) (33, 175) (35, 180) (37, 185) (40, 190) (40, 195) (34, 200) (37, 205) (38, 210) (38, 215) (35, 220) (34, 225) (36, 230) (38, 235) (41, 240) (42, 245) (40, 250)
53.5 58.5 63.9 68.9 74.0 79.4 83.8 88.9 94.0 98.8 103.8 108.9 114.0 119.1 123.9 128.5 133.2 138.3 143.6 148.7 154.3 159.4 164.5 169.1 174.9 178.1 183.4 188.7 194.2 199.1 202.9 208.3 213.4 218.3 222.8 227.6 232.8 238.1 243.5 248.6 253.2
54 58 62 66 72 76 82 85 90 94 97 102 106 110 115 117 120 125 128 133 137 141 146 149 154 158 160 164 168 172 175 180 185 188 190 195 200 205 210 214 217
0.5 0.5 1.9 2.9 2.0 3.4 1.8 3.9 4.0 4.8 6.8 6.9 8.0 9.1 8.9 11.5 13.2 13.3 15.6 15.7 17.3 18.4 18.5 20.1 20.9 20.1 23.4 24.7 26.2 27.1 27.9 28.3 28.4 30.3 32.8 32.6 32.8 33.1 33.5 34.6 36.2
0.96 0.89 2.98 4.28 2.70 4.26 2.17 4.37 4.22 4.82 6.59 6.36 7.03 7.64 7.21 8.98 9.91 9.61 10.87 10.56 11.19 11.52 11.22 11.89 11.94 11.28 12.75 13.07 13.48 13.59 13.74 13.59 13.31 13.89 14.71 14.31 14.09 13.88 13.75 13.91 14.29
and LCD panel. The beam pattern of sensor was determined by replacing the objects in front of the sensor in various positions. The achieved results showed that the determined beam pattern matches with the actual one given in its datasheet. Therefore, it can be concluded that the integration of sensor was successful. Nevertheless, according to our results, it should be noted that as the distance to an object increases measurement error increases. Thus, to get right
250
Approximate beam pattern of sensor according to its datasheet
Beam pattern of ultrasonic sensor
20 ft Distance (cm)
200
Beam pattern of sensor between 50 cm and 250 cm 15 ft
150
239
10 ft 100 Tested area 5 ft 50 –50 –40 –30 –20 –10
0 10 (cm)
20
30
40
50
Sensor position (0.0) Sensor position (0.0) (a)
(b)
Source: Maxbotix Inc.
Figure 8. (a) Determined beam pattern of ultrasonic sensor integrated to the woven fabric and (b) beam pattern of sensor according to its datasheet
300.0 250.0 Distance (d) cm
Error: 13-15% 200.0 Error: 11-14% 150.0 Error: 6-11% 100.0 Error: 0-5% 50.0 0.0 (19, 50)
(28,100)
(36,150)
(34,200)
(40,250)
Distance (x, y) cm Actual distance
Measured distance
results, some coefficients could be added into programming language considering the errors due to the distance ranges. 6. Acknowledgements Appreciation is extended to ENSAIT, GEMTEX Laboratory and Istanbul Technical University, Textile-clothing Control and Research Laboratory, for their support in supplying materials and performing experimental work. The authors also wish to thank Cagri Bahadir for his suggestion during sensor selection.
Figure 9. Error differentiation between actual and measured distance
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References Berndhenning, S. and Karstendierks, P. (2000), “Ultrasonic sensor properties characterized by a PC-controlled scanning measuring system”, Ultrasonics, Vol. 38, pp. 852-6. Cheol-Hong, M., Young-Soo, R. and Hwa-Young, K. (2007), “An SoC embedded system implementation using an array sensor”, Proceedings of the 4th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), Haikou, Hainan, China, 24-27 August, IEEE Computer Society, Washington, DC. Ermes, M., Parkka, J., Mantyjarvi, J. and Korhonen, I. (2008), “Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions”, IEEE Transactions on Information Technology in Biomedicine, Vol. 12 No. 1, pp. 20-6. Jongkyu, P., Yub, J., Haksue, L. and Wonkyu, M. (2010), “Design of an ultrasonic sensor for measuring distance and detecting obstacles”, Ultrasonics, Vol. 50, pp. 340-6. Jung, S., Lauterbach, C., Strasser, M. and Weber, W. (2003), “Enabling technologies for disappearing electronics in smart textiles”, Proceedings of the IEEE International Solid-State Circuits Conference (ISSCC), San Francisco, CA, 9-13 February. Katragadda, R.B. and Xu, Y. (2008), “A novel intelligent textile technology based on silicon flexible skins”, Sensors and Actuators, Vol. A143, pp. 169-74. Kim, S., Leonhardt, S., Zimmermann, N., Kranen, P., Kensche, D., Mu¨ller, E. and Quix, E. (2008), “Influence of contact pressure and moisture on the signal quality of a newly developed textile ECG sensor shirt”, Proceedings of the 5th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2006), Hong Kong, China, 1-3 June, pp. 256-9. Krause, A., Smailagic, A. and Siewiorek, D.P. (2006), “Context-aware mobile computing: learning context-dependent personal preferences from a wearable sensor array”, IEEE Transactions on Mobile Computing, Vol. 5 No. 2, pp. 113-27. Ling, B. and Stephen, S.I. (2004), “Activity recognition from user-annotated acceleration data”, Proceedings of the 2nd IEEE International Conference on Pervasive Computing, Orlando, FL, 14-17 March, Springer, Frankfurt, pp. 1-17. Llata, J.R., Sarabia, E.G., Arce, J. and Oria, J.P. (2008), “Fuzzy controller for obstacle avoidance in robotic manipulators using ultrasonic sensors”, Proceedings of the 5th International Workshop on Advanced Motion Control (AMC’98), Coimbra, Portugal, pp. 647-52. Luthy, K.A., Mattos, L.S., Braly, J.C., Grant, E., Muth, J.F., Dhawan, A., Natarajan, K., Ghosh, T. and Seyam, A. (2002), “Initial development of a portable acoustic array on a large-scale e-textile substrate”, paper presented at MRS Fall Meeting, Materials Research Society, Boston, MA, 2-6 December. Mathie, M.J., Coster, A., Lovell, N. and Celler, B.G. (2004), “Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement”, Physiological Measurement, Vol. 25 No. 2, pp. R1-R20. Maurer, U., Rowe, A., Smailagic, A. and Siewiorek, D.P. (2006), “eWatch: a wearable sensor and notification platform”, Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2006), Cambridge, MA, 3-5 April, pp. 142-5. Maxbotix Inc. (2010), “LV-Maxsonarw-EZ3e data sheet”, available at: www.maxbotix.com (accessed May 2010). Morris, S. and Paradiso, J. (2002), “Shoe-integrated sensor system for wireless gait analysis and real-time feedback”, Proceedings of the 2nd Joint IEEE EMBS (Engineering in Medicine and Biology Society) and BMES (the Biomedical Engineering Society) Conference, Houston, TX, 23-26 October, pp. 2468-9.
Niranjan, D., Jaya, B.T. and Shamala, P. (2004), “A mobility aid for the blind with discrete distance indicator and hanging object detection”, paper presented at the IEEE Region 10th Annual International Conference, Chiang Mai, 21-24 November, pp. 663-7. Ohtani, K. and Baba, M. (2006), “A simple identification method for object shapes and materials using an ultrasonic sensor array”, Proceedings of the IEEE International Conference on Instrumentation and Measurement Technology (IMTC 2006), Sorrento, Italy, 24-27 April, pp. 2138-43. Oliver, N. and Flores-Mangas, F. (2006a), “HealthGear: a real-time wearable system for monitoring and analyzing physiological signals”, Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2006), Cambridge, MA, 3-5 April, pp. 61-4. Oliver, N. and Flores-Mangas, F. (2006b), “MPTrain: a mobile, music and physiology-based personal trainer”, Proceedings of the 8th International Conference on Human Computer Interaction with Mobile Devices and Services (MobileHCI’06), Espoo, Finland, 12-15 September, ACM Press, New York, NY, pp. 21-8. Park, S., Mackenzie, K. and Jayaraman, S. (2002), “The wearable motherboard: a framework for personalized mobile information processing”, Proceedings of the 39th Design Automation Conference (DAC 2002), New Orleans, LA, 10-14 June, pp. 170-4. Parker, R., Riley, R., Jones, M., Leo, D., Beex, L. and Milson, T. (2002), “Stretch – an e-textile for large-scale sensor systems”, paper presented at International Interactive Textiles for the Warrior Conference, Cambridge, MA, 9-11 July. Peter, K. and Schweinzer, H. (2006), “Localization of object edges in arbitrary spatial positions based on ultrasonic data”, IEEE Sensors Journal, Vol. 6 No. 1, pp. 203-10, February. Post, E.R. and Orth, M. (1997), “Smart fabric, or washable computing”, Proceedings of the 1st IEEE International Symposium on Wearable Computers, Cambridge, MA, 13-14 October. Puttmer, A. (2006), “New applications for ultrasonic sensors in process industries”, Ultrasonics, Vol. 44, pp. 1379-83. Sethu Selvi, S., Kamath, U.R. and Sudhin, M.A. (2008), “Andha Asthra – a navigation system for the visually impaired”, Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2008), Seoul, Korea, 20-22 August, pp. 137-42. Subramanya, A., Raj, A., Bilmes, J. and Fox, D. (2006), “Recognizing activities and spatial context using wearable sensors”, Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence (UAI’06), Cambridge, MA, 13-16 July, Vol. AI, p. 06. Taccini, N., Loriga, G., Dittmar, A. and Paradiso, R. (2004), “Knitted bioclothes for health monitoring in Engineering in Medicine and Biology Society, 2004”, Proceedings of the 26th International Conference of the IEEE Engineering in Medicine and Biology Society (IEMBS’04), San Francisco, CA, 1-5 September, Vol. 1, pp. 2165-8. Wade, E. and Asada, H. (2007), “Conductive fabric garment for a cable-free body area network”, IEEE Pervasive Computing, Vol. 6 No. 1, pp. 52-8. Weber, W., Glaser, R., Jung, S., Lauterbach, C., Stromberg, G. and Sturm, T. (2003), “Electronics in textiles the next stage in man machine interaction”, Proceedings of the 2nd CREST Workshop on Advanced Computing and Communicating Techniques for Wearable Information Playing, Nara Institute of Science Technology, Nara, Japan, 23-24 May. Corresponding author Senem Kursun Bahadir can be contacted at:
[email protected] To purchase reprints of this article please e-mail:
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Utilization of recycled post consumer carpet waste fibers as reinforcement in lightweight cementitious composites Mehmet Ucar Mechanical Engineering Department, Kocaeli Universty, Kocaeli, Turkey, and
Youjiang Wang School of Polymer, Textile and Fiber Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA Abstract Purpose – A large amount of post-consumer carpet waste is discarded into landfills. The need to recycle this waste is increasing due to the lack of available landfill spaces in many parts of the world, environmental concerns, and resource conservation. The purpose of this paper is to explore the use of this waste for a low-cost, high-volume application. Design/methodology/approach – Fibers from carpet waste have been successfully used as reinforcement in concrete, typically at 0.1-1 per cent volume fraction (fractions by weight are even lower), for enhanced toughness. In this study, lightweight cementitious composites were fabricated that were reinforced with recycled carpet fibers at up to 20 per cent fiber to cement weight ratios. Flexural, toughness, and impact properties of the lightweight cementitious composites were characterized. Findings – The density of the composites decreases with the increase of fiber content. In the three-point bending test, lightweight cementitious composites exhibited a ductile behavior, and the flexural strength increases with the density of the composites. The energy absorption measured by the drop weight impact test was not very sensitive to the material parameters due to the total absorption of the impact energy by the specimens. Originality/value – The density of the lightweight composites ranges from 0.7 to 1.0 g/cm3, which was about 30-40 per cent of the density of typical concrete. Besides being moisture and termite resistant, the lightweight composites were very tough and could be cut and fastened with ordinary tools and nails. The lightweight composites are suitable for applications such as underlayment and wall panels for buildings, as well as for outdoor structures. Keywords Construction materials, Reinforcement, Composite materials, Textile fibres, Recycling Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 4, 2011 pp. 242-248 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111136502
1. Introduction World fiber production has been steadily increasing in the past few decades, now exceeding 64 million tons per year. In the USA alone, about 11.9 million tons of textile waste was generated, accounting for 4.7 wt% of the total municipal solid waste, and 15.9 per cent of textile waste was recovered in 2007 (US Environmental Protection Agency (USEPA), 2008). The outlets of the recovered textile waste include reuse, material recycling, and energy recovery. To enhance the environmental benefits of recycling, more effort is needed on research and development for better technologies that are cleaner, more energy efficient, and less expensive. Considering the diversity
of fibrous waste and structures, many technologies must work in concert in an integrated industry in order to have any noticeable impact on fibrous waste recovery (Wang, 2010). Most of the fibrous waste is composed of natural and synthetic polymeric materials such as cotton, wool, silk, polyester, nylon, polypropylene, etc. Frequently, different types of polymers and other materials are integrated to form an article, such as blended textiles, carpet, conveyer belts, composites, to name a few. Post consumer carpet provides an example of complex materials systems that are very difficult to recycle. However, since carpet is more consistent in structure and material composition than most other single fibrous products, and because of the large volume of carpet waste, significant effort has been devoted to carpet waste collection and recycling. The US carpet industry consumes about 1.4 million tons of fibers per year, including nylon (60 per cent), polyolefin (29 per cent), polyester (10 per cent), and wool (0.3 per cent). Among the nylon face fiber, about 40 per cent is nylon 6 and 60 per cent is nylon 6,6. The type of carpet is classified according to the type of face fibers used. A nylon 6 carpet, for instance, contains not only nylon 6 face fibers but also backing fibers (polypropylene) and adhesive (latex and filler). About 70 per cent of the carpet produced is for replacing old carpet, typically after 5-10 years of service. The rate of carpet disposal is about 2-3 million tons per year in the USA (Carpet America Recovery Effort (CARE), 2006), and about 4-6 million tons per year worldwide. The tufted structure (Figure 1) is the most common type of carpet with a 90 per cent market share. It typically consists of two layers of backing (mostly polypropylene fabrics), joined by CaCO3-filled styrene-butadiene latex rubber (SBR), and face fibers (majority being nylon 6 and nylon 6,6 textured yarns) tufted into the primary backing. The SBR adhesive is a thermoset material, which cannot be remelted or reshaped. The compositions of typical carpet waste are shown in Figure 2. In a fiber recycling industry capable of processing a large amount of the waste discarded, a collection network is needed to provide sufficient and consistent supply of post consumer fiber waste at reasonable cost. Some technologies such as nylon 6 depolymerization can convert waste into desirable products, but they are only limited to certain types of waste such as nylon 6 carpet. Other technologies must coexist so that most of the waste collected can be utilized for profitable recycling, without quickly saturating any market of a product or having to discard some of the waste into landfills. As the past experience has shown, it cannot be economically competitive if only a fraction of the carpet waste collected can be recycled, while the rest has to be sent back to landfills. Many technologies are available and more are being developed to recycle fibrous waste (Wang, 2006, 2010). Using carpet waste fibers to make cement boards has been investigated in this study. To convert carpet waste into fibers for cement boards, only simple shedding
Recycled carpet waste fibres
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Face yarn (nylon etc) Primary backing (PP) Adhesive (CaCO3/latex) Secondary backing (PP)
Figure 1. Tufted carpet structure
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Face yarn 1291 Backing 170
244 238
Figure 2. Typical carpet composition
713 CaCO3
SBR Adhesive layer
(g/cm2)
is needed, avoiding expensive component identification and separation. Even unidentified waste stream and residue from many other recycling processes can be used. The overall process is low-cost and the market for the product is very large. 2. Lightweight cement board The lightweight cement boards developed in this study have a very high-fiber content, up to 20 wt% and are very light in weight (0.7-1.0 g/cm3) with a porous structure. In comparison, the typical concrete has a density of 2.4 g/cm3 and the typical lightweight concrete has a density of 1.7 g/cm3. The lightweight cement boards developed in this study can be easily cut with ordinary tools and they work well with nails and screws. The lightweight cement boards are prepared using fibers from post consumer carpet containing nylon and polypropylene fibers after coarse shredding. Fiber length ¼ 50-70 mm, and Portland cement: gray and white. Sample preparation involves the following steps: (1) cement, fibers and water are mixed in a container; (2) placed in a mold by hand; (3) allowed to cure for seven days; and (4) cut with ordinary saw for testing. Table I illustrates the fiber/cement/water ratios of the samples prepared and their densities. It is noted that density decreases with increase in fiber content, and it increases with increase in cement content.
Table I. Fiber/cement/water ratios and density
Sample no.
Fiber
1 2 3 4 5 6 7
0.200 0.159 0.150 0.128 0.200 0.150 0.100
Weight ratios Water 1.081 0.690 0.608 0.690 1.081 0.608 0.595
Cement
Density (g/cm3)
1 (gray) 1 (gray) 1 (gray) 1 (gray) 1 (white) 1 (white) 1 (white)
0.678 0.841 0.848 0.953 0.729 0.943 1.001
3. Flexural properties The flexural properties of the lightweight cement boards are measured in a three-point bending on an Instron machine. The specimens are about 30 mm in height. The test configuration is shown in Figure 3. Five specimens are tested for each sample. Typical test curves are shown in Figure 4. The flexural test specimens failed in a ductile mode. To characterize the toughness characteristics, toughness index (TI5) is used, which is shown in Figure 5. For brittle material, TI5 ¼ 1, for elastic-plastic materials, TI5 ¼ 9, and for strain softening materials, TI5 is between 1 and 9. The toughness index values for the test samples are summarized in Table II, from which is can be observed that all the samples show
Recycled carpet waste fibres
245
Load
50 30
100 160
(mm)
Figure 3. Three-point flexural test configuration
Fiber/cement ratio 1.5
Stress (MPa)
0.13 1 0.15 0.5 0.20 0.16 0 0
0.02
0.04
0.06
0.08
Strain
Figure 4. Typical flexural test curves (gray cement specimens)
Stress TI5 =
A
B d
A+B A
Strain 5d
Figure 5. Definition of toughness index
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similar toughness index values and their behavior is close to that of an elastic-plastic materials. Figure 6 shows that the flexural strength and modulus of the samples decrease with the fiber to cement ratio.
246
4. Impact properties The impact test is performed on an Instron Dynatub tester. The impact velocity is 2.15 m/s. The specimen dimensions are 100 £ 100 £ 28.3 (thickness) mm.
Fiber
1 2 3 4 5 6 7
0.200 0.159 0.150 0.128 0.200 0.150 0.100
Strength (MPa)
Table II. Flexural toughness index
Sample no.
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 0.000
Weight ratios Water 1.081 0.690 0.608 0.690 1.081 0.608 0.595
0.050
0.100
0.150
Cement
TI5
1 (gray) 1 (gray) 1 (gray) 1 (gray) 1 (white) 1 (white) 1 (white)
7.62 7.34 7.56 7.94 7.85 7.76 7.50
0.200
0.250
0.200
0.250
Fiber to cement ratio (a)
Modulus (MPa)
250 200 150 100 50 0 0.000
Figure 6. Flexural test results
0.050
0.100 0.150 Fiber to cement ratio (b)
Notes: (a) Strength; (b) modulus vs fiber to cenent ratio
Energy absorption and maximum force are recorded. Figure 7 shows that the impact energy is not sensitive to the fiber to cement ratio. This is due to the total absorption of the impact energy at the test level by the specimens, as most damages are not visible from the backside. The maximum impact force, however, decreases with the fiber to cement ratio and increases with the density of the samples (Figure 8).
Recycled carpet waste fibres
5. Summary A large amount of fibrous waste is disposed in landfills each year. This not only poses economical and environmental concerns to the society but also represents a waste of resources. In this study, lightweight cement boards are developed. Their characteristics include: lightweight, tough, easy to handle and install, moisture, mold, and termite resistant. This method of fiber recycling may work together with other technologies to maximize the use of waste collected. This method of recycling only requires simple shedding, thus avoiding expensive component identification and separation. Even unidentified waste stream and residue from many other recycling processes can be used. The overall process is low-cost and the market for the product is very large. Potential applications include underlayment board for tiles, wall panels replacing dry wall for wet locations, and outdoor patio tiles and stones.
247
12
Energy (J)
10 8 6 4 2 0
0
0.05
0.1
0.15
0.2
0.25
Figure 7. Impact energy vs fiber to cement ratio
Fiber to cement ratio
1.8
Maximum force (kN)
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
0
0.05
0.1
0.15
Fiber to cement ratio
0.2
0.25
Figure 8. Impact force vs fiber to cement ratio and specimen density
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References CARE (2006), 2005 Annual Report, Carpet America Recovery Effort, Dalton, GA, available at: www.carpetrecovery.org USEPA (2008), “Municipal solid waste in the United States: 2007 facts and figures”, EPA530-R-08-010, USEPA, Washington, DC, p. 177, available at: www.epa.gov/osw Wang, Y. (2006), “Carpet recycling technologies”, in Wang, Y. (Ed.), Recycling in Textiles, Woodhead Publishing, Cambridge, pp. 58-70. Wang, Y. (2010), “Fiber and textile waste utilization”, Waste and Biomass Valorization, Vol. 1 No. 1, pp. 135-43. Corresponding author Youjiang Wang can be contacted at:
[email protected]
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Active T-shirt
Active T-shirt
Yavuz S¸enol Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey
Taner Akkan
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Department of Mechatronics, ˙Izmir Vocational School, Dokuz Eylul University, Izmir, Turkey, and
Ender Yazgan Bulgun and Ozan Kayacan Department of Textile Engineering, Dokuz Eylul University, Izmir, Turkey Abstract Purpose – The purpose of this paper is to realize an electronic circuit design on the fabric surfaces to form a fully integrated functional active T-shirt structure. Design/methodology/approach – Functional products combining textile, electronics and the software have attracted great attention in recent years. The integration of the electrical and electronic devices on the garment surface using conductive threads is a challenging issue considering conductiveness, long durability, washability and manufacturing process. As an application, a group of light emitting diode (LED) lights controlled by a light sensor, accelerometer and related electronic control circuits were placed on a fabric construction. Findings – The brightness of LED lights is controlled by using a light sensor depending on the perceived ambient light intensity. LED lighting patterns are controlled by means of an accelerometer which senses the physical activities of the wearer, such as walking, running and standing. Originality/value – In this study, new construction methods have been successfully implemented and the active T-shirt has been realized with its related hardware and software. Keywords Thread, Fabric production processes, Light-emitting diodes, Conduction Paper type Research paper
1. Introduction Multi-disciplinary studies, which integrate various physical and technological properties on a single product are getting more common and their success will increase within the coming years by the help of advanced technological developments. The products with multi-functional structures have been developed rapidly and lots of materials and systems with different functions have been produced (Post et al., 2000; Reichl et al., 2006). Active textile products give some technological advances to the wearer thanks to the embedded electronic circuits, which evaluates sensory informations (Berzowska, 2006; Mura, 2008). Here, two types of technology are available. The first one is to mount electronic devices such as conducting wires, integrated circuits (ICs), light emitting diodes (LEDs) and batteries into garments. The second one is the creation of wires or electronic functions such as diodes, transistors and LEDs on the textile fibers. The most common preferred approach is the first category because of its technical simplicity and applicability. The authors would like to give thanks to TU¨BI˙TAK “The Scientific and Technical Research Council of Turkey” for financial support under Project Number 109M404.
International Journal of Clothing Science and Technology Vol. 23 No. 4, 2011 pp. 249-257 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111136511
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Construction of the electronic circuits on a cloth surface is possible using conductive threads (Berzowska and Bromley, 2007; Nakad, 2003). Conductive threads can carry electric current as power and electronic signals between the electronic circuits. The idea is very similar to printed circuit boards (PCB) on the electrical and electronic devices except using copper layer-based conductive pathways. Making those PCBs are very easy, cost effective and also highly reliable. Small PCBs for electronic circuits and sensors can be used in e-textile applications. However, it is not an overall solution for the textile projects because of their non-flexible structure (Buechley and Eisenberg, 2007; Buechley et al., 2008; Kim et al., 2009). 2. Implementing the active T-shirt 2.1 The conductive threads Three parameters are important for the conductive threads: electrical resistance, fray resistance and elasticity. The conductive thread has an electrical resistance proportional to its length, resistivity of the material and inversely proportional to its cross-sectional area. In this study, the selected thread is made of 100 per cent stainless-steel filaments with 500 dtex fineness and 14 ohm/m average linear resistivity (Bekaert, 2005). Fray resistance is important and it is related to the durability of the product and also must be high enough to avoid short circuits between adjacent thread lines. If elasticity is low, the thread can easily be broken and possibly open circuits may occur. Another problem is the thickness of the thread. Thickness is directly related to the electrical resistance value. The more thick threads have lower resistance values, which is very important for higher conductiveness to deliver battery power at exact voltage and the electrical signals without weakened. On the other hand, they are not easily sewed on the garment surface and also tend to fray easily. In our study, instead of sewing the conductive threads into the garment, we preferred attaching them to the interior surface of the cloth using interlinings. Interlinings not only cover and fix the conductive threads, but also support sufficient isolation between them. If more insulation required, another layer of interlining can be used, or initially they can be painted with insulating fabric paint before covering the threads. Voltage drop due to the thread resistance must be eliminated by choosing the most possible shortest pathways. Especially, the power supply must be close to the microcontroller board to avoid the voltage drop at the conductive threads. For example, the voltage drop for a microcontroller with 100 mA current draw from a 5 V power supply located at 50 cm distance is about 1.4 V with a 14 ohm/m conductor thread resistance value. This means the microcontroller gets only 3.6 V from the 5 V power supply. This is a very critical case since the microcontroller cannot run safely under 3 V. This problem can be overcome by either shortening the distance between the electronic components or using twisted threads with lower resistance values. The contact between the conductive threads and electronic circuit pads must be properly provided. In this study, the hot silicone gluing technique was used. The heavy parts, especially the microcontroller can also be fixed with glue or interlinings. The most heavy part, the polymer lithium ion battery was inserted to a pocket located at the upper left arm area. 2.2 The clothing design The first design idea is shown in Figure 1.
Light sensor
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RGB LED
Left LED strip
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Back Reverse exclamation
Front Strip positions
The first stage of the study is to develop the electronic control unit with sensors and LED interfaces. In this stage, LED driving software was realized to obtain basic light effects. In the second stage, all electronic components were placed into the garment construction. The connections between components were provided by textile-based conductive threads. In the third stage, the tests of the active T-shirt integrated with electronics hardware and software was performed. The main aim for using light sensors is to determine the light intensity and to optimize the illumination amount of LEDs. As it is known, the lights with low intensity can be visible in dark environment. In contrast to this, it is necessary to use the intense lights in bright fields. In this way, the energy requirements, or in other words, battery savings can be provided. The accelerometers are used to measure the acceleration. Single- and multi-axis models are available to detect magnitude and direction of the acceleration as a vector quantity, and can be used to sense orientation, vibration, etc. The LEDs are placed in the fabric construction into a band form. Textile-based conductive materials will be used for transferring the current for activating the LED lights. On the other hand, the functional requirements should be considered. In this study, new generation batteries such as Lithium Ion and Polymer Lithium Ion were examined for power-supply selection. 2.3 Electronic circuit design The electronic hardware of the active T-shirt consists of Lilypad modules (Buechley et al., 2008) and the LED strips mounted on a flat flexible printed board material. The most important component of the system is ATMEL AVR ATmega328V microcontroller. It has 10-bit analog to digital converter for six analog inputs, 12 digital outputs, a serial port, two 8 bit and one 16 bit timers, six pulse width modulation (PWM) modules for digital to analog conversions. The microcontroller unit has wide operating voltage from 2.7 V to 5.5 V. For this application 5 V was chosen as a main supply voltage to provide sufficient LED brightness. Battery power regulator regulates the voltage from the polymer lithium ion battery to 5 V. The polymer lithium ion batteries are powerful and lightweight batteries. Two sensors are present in this study. The first one is the light sensor to analyze the light intensity level of the environment. The second one is the three axes accelerometer to analyze the body movements. A vibration module and a buzzer module were used
Figure 1. The first-design idea
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as warning devices to the wearer. Three colors LED module has capable to show different colors for different situations. Sewing the entire electronic units through the pad holes is very easy due to the Lilypad circular structures. The LED strips were inserted into sewed transparent fabric bands. Electronic hardware has three data transferring options between the active T-shirt and the computers or personal digital assistants (PDA). All options use the same serial port on the microcontroller unit to transfer sensory data. The first option uses serial to universal serial bus (USB) conversion module with an USB cable. The second connection option is the wireless data transfer with available add-on Bluetooth module. The third one is an SD card data storage module to save data to be analyzed offline on computers. 3. Software 3.1 Microcontroller software Basically, the microcontroller C software code checks the sensors in every 20 msec and defines the condition flags comparing the sensory data with user defined set points. If computer connection or SD card write operation is permitted then the calculated data are updated at every 20 ms sensor scan periods. This scan period can be adjusted to define the sensor data sampling frequency. Then, the defined flag conditions activate or deactivate the LEDs. For power saving and increasing the visibility, the LEDs are blinked at every LED scan periods. Here, this period is defined as 100 msec. This infinite loop continues till either the user toggles the button on the upper middle button on the front T-shirt side or power switch is turned off. The whole software flowchart is shown in Figure 2. 3.2 Analysis software on MATLAB This software was to analyze the sensory data from the active T-shirt to modify the T-shirt software in a proper way. 4. Results In this study, an active T-shirt concept has been performed by combining textile and electronics. Various measurements, tests and analysis have been performed for the purpose of working on a textile-based structure. Following components have been mounted on the fabric surface: . microprocessor; . power module; . vibration module; . light sensor; . speaker; . accelerometer; . 3-color LED; . LED lights in strip form; and . on/off switch. All modules were connected by using electrically conductive stainless-steel yarn. On the fabric surface, the conductive threads were covered and fixed by interlinings
Active T-shirt
Start Initialize sensors and the outputs Read the command from serial connection if is avilable Read the sensor values and from the data packet Yes 20 ms refresh Yes Send packet
No
253
Command send ok? No Datermine status flags using accelerometer and light sensor data 100 ms refresh
No
Yes LED on/off and brightness control using status flags Command quit ok? Yes End
No
to ensure a reliable insulation. This method is entirely different from other insulation processes such as sewing, embroidery, 3D fabric paints, etc. The advantages of using interlinings are their technical simplicity, rapid applicability and their cost. The front and back view of the T-shirt are shown in Figure 3. Stainless-steel yarns with electrically conductive characteristics have been applied to the electronic circuit. There are two types of LED light on the garment. 3-color LED light was placed on the front side of the T-shirt. Instead of using single LEDs connected by conductive threads, group of LEDs on a flexible strip were placed on front and back side of the prototype T-shirt. The light intensity of the environment is a key factor for LED lights. The light sensor, mounted on the shoulder area, optimizes the illumination amount of LEDs. All LED lights on the front and back side of the garment are activated by the wearer’s rate of movements which is perceived by the accelerometer. Various measurements and tests have been realized and the results show that polymer lithium ion batteries are convenient selection in terms of their light weight and high-power capacity. Because of the light weight of the electronic components and conductive threads, after the implementation process, there is no significant weight increase for the T-shirt. The electronic circuit placement with thread contacts on the outer T-shirt surface is shown in Figure 4. The inner surface of the electronic circuit is shown in Figure 5.
Figure 2. The microcontroller software general flow chart
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Figure 3. The front and back view of the active T-shirt
Figure 4. Modules on active T-shirt
Three accelerometer channels and the light sensor data graphics are shown in Figure 6. The x-axes of the accelerometer shows the arm movements from standing to the running action. As seen from Figure 6, the wearer has different actions in different time intervals. The person is in the standstill state until four seconds, walking slowly between four and six seconds, quickly walking from six to 13 sec and running after 13 sec. The light intensity information obtained from the light sensor is very oscillatory because of the fluorescent lighting. The lamps were turned of at about ten seconds. The measurements have shown that for daylight the measured light intensity is very stable. As seen from Figure 6, the recorded data, especially the light intensity has some fluctuations. For reliable decision on sensor data, these undesirable fluctuations must be removed by some signal processing algorithms. Figure 7 shows running average
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Figure 5. Conductive threads and connections in the inner side of the prototype
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algorithm results using 200 msec windows. This algorithm or other filtering algorithms can also be implemented easily with the available microcontroller. 5. Conclusions The obtained results have shown that various electronic sensors, which are readily available in the market, can be installed on garment to sense various signals such as body temperature, heart rate, CO2 value of the surrounding environment, motion and the light. In this study, the realized circuit design of the active T-shirt will certainly enhance the visibility and appearance features of the product and the wearer as well. Therefore, the system can be preferably used by the security staff or the people who need such requirements. The active T-shirt prototype consists of nine different electronic modules mentioned above. In future studies, the desired functions for the prototypes can be supplied by using only necessary modules, so that, the final product can be formed much more easily and effectively. The connections and lines between the electronic components and the locations and mounting procedures of the modules can be improved in future works. Various signals can be obtained from the installed sensors in respect to body movements. With related signal analysis techniques, these signals can be converted into functional results. Being a casual garment, design studies have a critical role in developing such a prototype. Improvements can be resulted in a fully integrated garment in terms of weight and volume, etc. Data collection softwares on PC can be converted to mobile equipments such as PDA or cell phone. In this way, data logging and analyzing can be performed wirelessly with Blue tooth add-on module without any need to PC. References Bekaert Fibre Technologies (2005), “Bekinox stainless-steel filament yarn technical specification sheet”, Bekaert Fibre Technologies, available at: www.bekaert.com (accessed May 2005). Berzowska, J. (2006), “Personal technologies: memory and intimacy through physical computing”, Al & Society, Vol. 20, pp. 446-61. Berzowska, J. and Bromley, M. (2007), Soft Computation Through Conductive Textiles, available at: www.xslabs.net/papers/iffti07-berzowska-AQ.pdf (accessed April 2010). Buechley, L. and Eisenberg, M. (2007), “Fabric PCBs, electronic sequins, and socket buttons: techniques for e-textile craft”, Personal and Ubiquitous Computing, Springer, New York, NY. Buechley, L., Eisenberg, M., Catchen, J. and Crockett, A. (2008), “The LilyPad Arduino: using computational textiles to investigate engagement, aesthetics, and diversity in computer science education”, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI), Florence, Italy, pp. 423-32. Kim, H., Kim, Y., Binhee, K. and Yoo, H.-J. (2009), “A wearable fabric computer by planar fashionable circuit board technique”, Sixth International Workshop on Wearable and Implantable Body Sensor Networks, Berkeley, CA, 3-5 June, pp. 282-5. Mura, G. (2008), “Wearable technologies for emotion communication”, METU JFA, Vol. 25 No. 1, pp. 153-61.
Nakad, Z.S. (2003), “Architectures for e-textiles”, PhD thesis, Virginia Poytechnic Institute, Blacksburg, VA. Post, E.R., Orth, M., Russo, P.R. and Gershenfeld, N. (2000), “E-broidery: design and fabrication of textile-based computing”, IBM Systems Journal, Vol. 39, pp. 840-60. Reichl, H., Kallmayer, C. and Linz, T. (2006), “Electronic textiles”, in Aarts, E.H.L. and Encarnacao, J.L. (Eds), True Visions the Emergence of Ambient Intelligence, Wearable Computing Lab, Springer, Berlin Heidelberg, pp. 115-32. Corresponding author Ender Yazgan Bulgun can be contacted at:
[email protected]
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Modeling the tensile behaviour of needle punched nonwoven geotextiles
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Umit Halis Erdogan and Nilufer Erdem
Department of Textile Engineering, Dokuz Eylu¨l University, ˙Izmir, Turkey Abstract Purpose – The purpose of this paper is to propose a theoretical model to predict the mechanical behaviour of needle punched heavy geotextiles in uniaxial tensile test. Design/methodology/approach – The model was constructed using theory of layered composite materials and finite element method. The properties of a reference fabric were used as initial data in theoretical calculations and a commercially available finite element program was chosen to carry out stress analysis. A comparison is made between theoretical calculations and experimental data to evaluate the deformation mechanism of geotextile fabrics in uniaxial tensile test. Findings – The results indicate that compatible data were predicted in terms of stress values and stress distribution of fabrics. The inconstant lateral contraction of nonwoven fabrics in tensile test is also successfully simulated by the model. However, in the case of elongations, the model could not predict the strains of heavy geotextiles accurately. Originality/value – The study aims at predicting the mechanical behaviour of needle punched heavy geotextiles by using the structural and mechanical properties of a “reference fabric” instead of constituent fiber properties. Keywords Textiles, Soils, Tensile strength, Reinforcement, Drainage Paper type Research paper
1. Introduction Geotextiles, which are the members of geosynthetic group, are gaining more and more importance for complex construction projects in engineering by virtue of their many advantages. Geotextiles are permeable textile structures such as nonwoven and woven fabrics. Needle punched nonwovens, which are produced by the penetrating action of barbed needles, are amongst the most widely used geotextile materials. These types of geotextiles are felt like in appearance and are relatively thick (Adanur, 1995; Rawal and Anandjiwala, 2006). Needle punched nonwoven fabrics are characterized by high porosity, elongation and energy absorption properties which make them ideal for a wide range of geotextile applications (Ingold and Miller, 1988). Various mechanical and hydraulic functions such as reinforcement, separation, protection, drainage and filtration are provided by fabrics in a geotextile-soil system. Therefore, mechanical characterization of the fabric is very important in designing with geotextiles. However, several fiber and fabric parameters such as polymer and fiber type, orientation of fibers, fabric weight, fabric thickness and also method of International Journal of Clothing Science and Technology Vol. 23 No. 4, 2011 pp. 258-268 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111136520
This research is a part of a project supported by The Scientific Research Department of Dokuz Eylul University (Project No: 2005.KB.FEN.004). Their generous financial support of this project is gratefully acknowledged. The authors also thank Hassan Group for providing geotextile fabrics and for their technical support.
bonding have influence on the mechanical behaviour of nonwoven fabrics. Moreover, complexity of mechanical characterization of nonwoven fabric increases, because of the interaction of mechanisms like breakage, elongation, shear, bending and buckling during deformation. Nevertheless, several attempts were made to predict the mechanical behaviour of nonwovens under various kinds of loads. As a result of these studies, a number of theoretical models were developed. Backer and Peterson (1960) reported a fiber network theory for nonwoven fabrics based on fiber tensile properties and orientation of fibers. The following theories generally consider the fiber network theory and improve it by using different and/or new analytical and experimental methods such as energy method, orthotropic symmetry theory, theory of composite materials, finite element method, etc. (Hearle and Stevenson, 1963, 1964; Hearle and Newton, 1967; Hearle and Sultan, 1968; Bais-Singh et al., 1996; Liao and Adanur, 1999; Kim, 2004; Limen and Warner, 2005). In most cases, computer simulation and image analysis techniques were also used (Britton et al., 1983; Pourdeyhimi and Ramanathan, 1996; Pourdehyhimi et al., 1997, 1999). In the aforementioned studies, the properties of constituent fibers and structural arrangement of fibers in the web were commonly used to predict the mechanical properties of nonwoven fabrics. However, some specific mechanisms of deformation were ignored almost in each approach because of the complexity of problem. Moreover, interactions of fibers are generally neglected in the previous studies considering the properties of constituent fibers, but in needle punched fabrics inter fiber friction plays a predominant role in deciding the mechanical behaviour of fabric as reported by Hearle and Sultan (1968). In this study, a theoretical model was proposed to predict the mechanical behaviour of needle punched heavy geotextiles in uniaxial tensile test. We assumed that this type of geotextiles as a laminated composite considering the previous studies (Liao et al., 1997; Bais-Singh et al., 1998; Erdogan, 2008). The model was constructed using theory of layered composite materials and finite element method. The structural and mechanical properties of a “lightly bonded reference fabric” were used as initial data in theoretical calculations instead of constituent fiber properties and a commercial available finite element program “ANSYS” was chosen to carry out stress analysis. The nonlinear stress-strain behaviour of reference fabric was also considered in the model. The adequacy of the model was discussed by comparing theoretical and experimental results of geotextile samples in this study.
Tensile behaviour of geotextiles 259
2. Material and methods 2.1 Material The five needle punched nonwoven geotextile fabrics, made from polypropylene staple fibers, were supplied by a commercial geotextile producer. Figure 1 shows the production process of sample fabrics in this study. The weights of reference and sample fabrics are 100, 200, 300, 500 and 800 g/m2, respectively. 2.2 Experimental At first, the thickness of all samples was measured using a digital thickness gauge under 2 kPa pressure according to TS EN ISO 9863-1 (2006). Then, tensile behaviour of geotextile Staple fibers
Web formation (carding)
Lapping
Needle punching
Geotextile fabric
Figure 1. Flow chart for the production of geotextile fabrics
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samples was examined both in the machine direction (MD) and in the cross machine direction (CD) on a computer-controlled Shimadzu Autograph AG-IS series universal testing machine. The wide-width tensile test was performed according to TS EN ISO 10319 (1998), to minimize the errors which can be caused by edge curling of specimens and to avoid the extreme strains in strip test. The test length was kept as 100 mm and width as 200 mm and the fabrics were strained at a rate of 20 mm/min. The tensile behaviour of reference fabric was used as initial data in theoretical analysis to predict the mechanical properties of other samples. Therefore, material constants of reference fabric such as poisson’s ratio, shear modulus and elastic moduli were also obtained. In the nonwoven production line, all fibers in the card web are parallel to each other, but after lapping and punching, fibers in the layers of fabric are oriented at various directions following random or some known statistical distribution. Therefore, the orientation of fibers in a layer of nonwoven fabric is another parameter that needs to be defined as initial data in the theoretical analysis. However, it is very difficult to obtain fiber orientation distribution in heavy nonwovens such as needle punched geotextiles with experimental methods, because they consist of a large number of fiber layers (Pourdeyhimi, 2001). In our approach, orientation angles of layers in heavy nonwovens were simply derived considering the orientation angles of reference fabric and the number of web layers in the heavier sample fabrics. For this purpose, at first fiber orientation distribution of reference fabric was measured under a projection microscope. Finally, the orientation angle of layers in heavy samples was assigned to program considering both the number of web layers in fabrics and the fiber orientation distribution of reference fabric. 2.3 Model and theoretical formulations The basic principles of our model for nonwovens are similar to the layer theory and finite element model proposed in earlier publications (Bais-Singh and Goswami, 1995; Liao et al., 1997; Bais-Singh et al., 1998). We assumed that nonwoven fabrics are made up of fiber layers similar to composite materials. Thus, a layered nonwoven can be regarded as a laminate and each layer of fabric can be considered equivalent to a lamina. We also assumed that the nonwoven fabrics are formed by layered finite elements, and layers that make up the fabric are bound together at nodal points of the mesh of the finite element. As mentioned above, nonwovens especially heavy ones consist of a number of layers (placed at an angle) as shown in Figure 2. The axes in the X-Y coordinate system represent the global axes, such that the uniaxial loading direction and transverse directions of fabrics coincide with the Y and X axes, respectively. The local axes for an individual layer (lamina) are given by the 1-2 coordinate system, such that all fibers in the layer are oriented along the 1 direction and the direction 2 is perpendicular to the fibers. A unidirectional layer of fabric falls under orthotropic material category. If the layer is thin and does not carry any out of plane loads, one can assume plane stress conditions for the layer. The relationship of stress and strain for an orthotropic plane stress problem can be written as (Kaw, 1997): 2 3 2 32 3 11 0 Q11 Q12 s1 6 7 6 76 7 6 s2 7 ¼ 6 Q12 Q22 0 7 6 12 7 ð1Þ 4 5 4 54 5 g12 0 0 Q66 t12
Tensile behaviour of geotextiles
Y
1 θ
261 2
X
Figure 2. Layered structure of nonwoven fabric
where Q11 ¼ ðE1 =1 2 u12 u21 Þ; Q12 ¼ ðu21 E1 =1 2 u12 u21 Þ; Q22 ¼ ðE2 =1 2 u12 u21 Þ; Q66 ¼ G12 and E1 is the longitudinal Young’s modulus, E2 the transverse Young’s modulus, n12 and n21 the major and the minor Poisson’s ratios, G12 the in-plane shear modulus, s1, s2, t12 the layer stresses in the 1-2 coordinate and 11, 12, g12 the layer strains in the 1-2 coordinate. The global and local stresses in a layer are related to each other through the orientation angle of the layer. The relationship of stress and strain between the local and global system can be defined as (Kaw, 1997): 2 3 2 32 3 sx s1 sin2 u 22sinucosu cos 2 u 6 7 6 76 7 2 2 6 sy 7 ¼ 6 sin u 6s 7 cos u 2sinucosu 7 ð2Þ 4 5 4 54 2 5 txy t12 sinucosu 2sinucosu cos2 u 2 sin2 u and: 2
1x
3
2
cos2 u
6 7 6 6 1y 7 ¼ 6 sin2 u 4 5 4 gxy sinucosu
sin2 u cos2 u 2sinucosu
sinucosu
32
11
3
76 7 61 7 2sinucosu 7 54 2 5 g12 cos2 u 2 sin2 u
ð3Þ
where sx, sy, txy are the layer stresses in the X-Y coordinate, 1x, 1y, gxy the layer strains in the X-Y coordinate and u the orientation angle of the layer. By substituting equations (2) and (3) into equation (1), the stress-strain relationship of each layer in the global coordinate system can be expressed as: 2 3 2 32 3 1x sx Q11 Q12 Q16 6 7 6 76 7 6 sy 7 ¼ 6 Q12 Q22 Q26 76 1y 7 ð4Þ 4 5 4 54 5 txy gxy Q16 Q26 Q66
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where: Q11 ¼ Q11 cos4 u þ 2ðQ12 þ 2Q66 Þ sin2 u cos2 u þ Q22 sin2 u
ð5Þ
Q12 ¼ ðQ11 þ Q22 2 4Q66 Þ sin2 u cos2 u þ Q12 ðcos4 u þ sin4 uÞ
ð6Þ
Q22 ¼ Q11 sin2 u þ Q22 cos4 u þ 2ðQ12 þ 2Q66 Þ sin2 u cos2 u
ð7Þ
3
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Q16 ¼ ðQ11 2 Q12 2 2Q66 Þ cos u sin u 2 ðQ22 2 Q12 2 2Q66 Þ sin u cos u
ð8Þ
Q26 ¼ ðQ11 2 Q12 2 2Q66 Þ cos u sin3 u 2 ðQ22 2 Q12 2 2Q66 Þ sin u cos3 u
ð9Þ
Q66 ¼ ðQ11 þ Q22 2 2Q12 2 2Q66 Þ sin2 u cos2 u þ Q66 ðcos4 u þ sin4 uÞ
ð10Þ
If the stress of a material uniformly varies with strain, the equation (4) is valid. However, in some nonwovens, namely needle punched ones, deformation is nonuniform in uniaxial test (Adanur, 1995; Bais-Singh and Goswami, 1995). Figure 3 shows the nonuniform strain-stress curves of our reference fabric in MD and CD. The state of stresses and strains are not the same in different regions of curves due to various effects such as nonlinear stress strain behaviour of fibers, crimp of fibers and reorientation of staple fibers in the beginning of the test and shear effects. Therefore, a nonuniform stress-strain behaviour was assumed for each layer and the stiffness matrix of layer divided into two parts. In the initial part, stress varies nonlinearly with strain and in the second part stress varies linearly with strain. After reaching the maximum stress, the fibers and/or bonds start failing and the fabric stress drops to lower values, thus the theoretical calculations were not performed in these regions. The stress-strain relationship of a lamina can thus be given as: 32 2 3 2 ı 3 2 32 3 11 11 0 Q11 Q12 s1 Q11 0 0 76 6 7 6 7 6 76 7 6 s2 7 ¼ 6 0 0 0 76 12 7 þ 6 Q12 Q22 0 7 6 12 7 ð11Þ 54 4 5 4 5 4 54 5 g g 0 0 Q t12 0 0 0 12 12 66 The nonlinear part of the stiffness matrix contains only one stiffness term (Qı11 ), which relates the stress and strain components in the layer direction. The components of linear part of stiffness matrix are material constants, which are denoted in equation (1). 2,500 E+06 MD
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Figure 3. Stress-strain curves of reference fabric in the MD and CD
0,000 E+00 0
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If the strains are known at any point along the thickness of the laminate (fabric), the global stresses can be calculated for each layer by incorporating equations (4) and (11). Then stresses in all layers can be integrated using theory of composite materials to give the overall mechanical behaviour of the layered nonwoven. Thus, fabric stresses in the X-Y direction for each finite element in the symbolic matrix form can be given by: ı
½se ¼ ½ De ½1e þ½ De ½1e e
ð12Þ
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eı
where ½ D and ½ D are the material constitutive matrices of the element in the linear part and nonlinear part, respectively: T T ½se ¼ sx sy txy and ½1e ¼ 1x 1y gxy We incorporated the above finite element constitution relations into a commercial finite element program ANSYS to carry out stress analysis. Experimental data on the reference fabric tensile properties and web structure parameters are also supplied to program as input data. We have considered multi-linear stress-strain assumption in the nonlinear initial part of stress-strain curve of reference fabric. In the linear part, where the moduli are constant, we have considered orthotropic theory. In the multi-linear region 15 respective stress-strain values of reference fabric and in the linear region material constants of reference fabric, which are given in Table I, were used as initial data. 2.4 Geometry of the finite element mesh The needle punched nonwoven geotextiles were modeled considering wide-width tensile test. The initial geometry of fabric and the boundary conditions applied to the model are shown in Figure 4. Side AB and CD are constrained within the jaws. All translations and rotations are constrained on side AB. However, side CD is allowed to move only vertically. Both sides AD and BC are allowed to move freely in the transverse direction. “Structural Layered Composite” element was chosen to mesh the initial fabric model. This element type is suitable for the calculation of the behaviour of laminated structures with anisotropic nonlinearities (ANSYS User’s Manual). Uniformly distributed tensile load (negative pressure) was applied to models. The magnitudes of applied loads are different for different fabric samples and are slightly less than their failure initiation loads. The real constants for layers and elements are given in Table II. Fabric thickness measurement values are used to assign thickness value for each element. 3. Results and discussions Stress analysis of geotextile samples was performed in both MD and CD using the constructed theoretical model. The distribution of computed stresses in the tensile directions can be seen in Figure 5. Value Property Longitudinal modulus Transverse modulus In-plane shear modulus Poisson’s ratio
Symbol
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CD
E1 E2 G12 y12
2.70 MPa 2.36 MPa 0.91 MPa 0.36
2.36 MPa 2.70 MPa 0.88 MPa 0.29
Table I. Material constants of a layer in the linear part of stress-strain curves
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Figure 4. Initial geometry of fabric model
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Fabrics Reference Heavier samples Table II. Real constants for elements and layers
Fabric weight Layer thickness Element total thickness (g/m2) Total number of layers (mm) (mm) 100 200 300 500 800
2 5 8 14 22
1.30 0.59 0.44 0.28 0.23
2.60 2.96 3.56 4.01 5.20
As seen in the plotted contours, the state of stresses is not the same throughout the models because of constraints, imperfectly symmetric distribution of fibers within the fabrics and transverse contraction during tensile deformation. Maximum stresses are calculated near the jaws as a result of constraints. Particularly stresses are much higher in the four corners than the other parts. Minimum stresses are obtained near the free edges. Besides, critical stress distributions and concentrations are calculated around the center of the models. Consequently, meaningful stress data can be obtained from the stress distribution of computed models of needle punched nonwoven geotextile samples. The typical shape of the deformed fabric samples in the wide-width tensile tests is shown in Figure 6. The comparisons of Figures 5 and 6 show that experimentally obtained and theoretically computed configurations of geotextile samples are similar in uniaxial tensile tests. There is not any lateral contraction at the jaws of computed figures; however, contraction gradually increases to its maximum value at the center of the models. As given in Figure 6, very similar behaviour is observed during experiments due to the geometry of test. The inconstant lateral contraction of nonwoven fabrics in uniaxial tests is successfully simulated in the models. In the computed figures, critical stress concentrations were calculated around the center of models. On the other hand as seen in Figure 6, the experimental breaks usually occur around the center of specimens in uniaxial tensile tests. Therefore, the element stresses in the center of models were considered for comparison. Theoretically, and experimentally calculated parameters of reference and other fabric samples in the MD and CD are given in Tables III and IV, respectively.
Machine direction
Cross machine direction
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Figure 5. Distributions of computed stresses in simulated sample fabrics
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Figure 6. Deformation of fabric (500 g/m2) in uniaxial tensile tests
Fabric weight (g/m2)
Table III. Experimental and calculated stresses in MD
100a 200 300 500 800
1.97 4.05 5.11 7.36 7.87
Experimental Max displacement (mm) 131.25 148.54 171.36 208.72 223.81
Stress sx (MPa) 2.03 4.32 5.52 7.96 8.52
Theoretical Max displacement (mm) 73.15 152.95 202.72 299.76 312.58
Note: aReference fabric
Fabric weight (g/m2)
Table IV. Experimental and calculated stresses in CD
Stress (MPa)
100a 200 300 500 800 Note: aReference fabric
Stress (MPa) 1.61 3.45 4.34 6.62 8.31
Experimental Max displacement (mm) 108.00 197.20 229.86 217.39 236.01
Stress sx (MPa) 1.66 3.71 4.75 7.26 9.08
Theoretical Max displacement (mm) 59.40 136.65 180.15 283.86 348.14
As seen in Tables III and IV, predicted stresses in the center of plotted models are compatible with experimental ones and close to measured maximum stresses. Experimentally measured maximum stresses are predicted with almost 7-8 per cent average margin of error in the center of the models. In conclusion the agreement between the theoretical and experimental values is not poor in both MD and CD. However, in the case of elongations, the model could not predict the strains of heavy geotextiles in uniaxial tensile test accurately. As the fabrics become thicker, the difference between measured and computed displacements increases and higher displacements were predicted with respect to experimental measurements. In the model, the fibers that make up the fabric are assumed to be bound together only at nodal points of the mesh of finite elements, however in real fabrics bonded areas are not as homogeneous as in constructed model. Moreover, reorientation of fibers was restricted because of the increasing number of bonded areas in heavy fabrics. As a nature of bonding process the weak bonded zones can also occur in real fabrics. 4. Conclusion In this study, a theoretical model is proposed to predict the mechanical properties of heavy nonwoven geotextiles using composite layer theory and finite element method. In the theoretical analysis, the structural and tensile properties of a reference fabric is used as initial data. The nonlinear stress-strain behaviour of reference fabric in uniaxial direction was also considered in the analysis. The comparisons of theoretical and experimental values indicate that meaningful stress data can be obtained from the stress distribution of computed models. The calculated stresses in the center of the model, where the experimental breaks are usually observed, are close to measured maximum stress. Moreover, similar fabric configurations are observed in the experimental and computed results. In the case of elongations, predicted values are not very close to the experimental ones, because bonded areas in the real fabrics are not as homogeneous as constructed models. Consequently, the constructed model makes it possible to predict the stress distribution in heavy needle punched geotextiles form the properties of a light nonwoven. However, the elongation of heavy fabrics cannot be predicted with adequate accuracy. Therefore, further work is needed, which may consider the reorientation of fibers during deformation of heavy nonwovens exactly. References Adanur, S. (1995), Wellington Sears Handbook of Industrial Textiles, Technomic Publishing, Lanchaster, PA. ANSYS User’s Manual (2005), ANSYS 7.0 – User’s Manual, ANSYS Inc., Canonsburg, PA. Backer, S. and Peterson, D.R. (1960), “Some principles of nonwoven fabrics”, Textile Research Journal, Vol. 30, pp. 704-11. Bais-Singh, S. and Goswami, B.C. (1995), “Theoretical determination of the mechanical response of spun-bonded nonwovens”, Journal of Textile Institute, Vol. 86, pp. 271-89. Bais-Singh, S., Biggers, S. and Goswami, B.C. (1998), “Finite element modeling of the non-uniform deformation of the spun-bonded nonwovens”, Textile Research Journal, Vol. 68, pp. 327-42. Bais-Singh, S., Rajesh, D.A. and Goswami, B.C. (1996), “Characterizing lateral contraction behavior of spunbonded nonwovens during uniaxial tensile deformation”, Textile Research Journal, Vol. 66, pp. 131-40.
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Britton, P.N., Sampson, A.J. and Gettys, W.E. (1983), “Computer simulation of mechanical properties of nonwoven fabrics part I: method”, Textile Research Journal, Vol. 53, pp. 363-8. Erdogan, U.H. (2008), “An investigation about in use properties of polypropylene fibers used in geotexiles by different methods”, PhD thesis, Dokuz Eylu¨l University, ˙Izmir. Hearle, J.W.S. and Newton, A. (1967), “Nonwoven fabric studies part XIV: derivation of generalized mechanics the energy method”, Textile Research Journal, Vol. 37, pp. 778-97. Hearle, J.W.S and Stevenson, P.J. (1963), “Studies in nonwoven fabrics part III: the anisotropy of nonwoven fabrics”, Textile Research Journal, Vol. 33, pp. 877-88. Hearle, J.W.S and Stevenson, P.J. (1964), “Studies in nonwoven fabrics part IV: prediction of tensile properties”, Textile Research Journal, Vol. 34, pp. 181-91. Hearle, J.W.S. and Sultan, M.A.I. (1968), “A study of needled fabrics part III: the influence of fiber type and dimensions”, Journal of Textile Institute, Vol. 59, pp. 137-47. Ingold, T.S. and Miller, K.S. (1988), Geotexitles Handbook, Thomas Telford, London. Kaw, K. (1997), Mechanics of Composite Materials, CRC Press, New York, NY. Kim, H.S. (2004), “Orthotropic theory for the prediction of mechanical performance in thermally point-bonded nonwovens”, Fibers and Polymers, Vol. 5, pp. 139-44. Liao, T. and Adanur, S. (1999), “Computerized failure analysis of nonwoven fabrics based on fiber failure criterion”, Textile Research Journal, Vol. 69, pp. 489-96. Liao, T., Adanur, S. and Drean, J.Y. (1997), “Predicting the mechanical properties of nonwoven geotextiles with the finite element method”, Textile Research Journal, Vol. 67, pp. 753-60. Limen, S. and Warner, S.B. (2005), “Adhesive point bonded spunbond fabrics”, Textile Research Journal, Vol. 75, pp. 63-72. Pourdeyhimi, B. (2001), “Fiber orientation distribution in heavy nonwovens”, NCRC Newsletter, Vol. 3, p. 7. Pourdeyhimi, B. and Ramanathan, R. (1996), “Measuring fiber orientation in nonwovens part I: simulation”, Textile Research Journal, Vol. 66, pp. 713-22. Pourdeyhimi, B., Dent, R. and Davis, H. (1997), “Measuring fiber orientation in nonwovens part III: fourier transform”, Textile Research Journal, Vol. 67, pp. 143-51. Pourdehyhimi, B., Dent, R., Jerbi, A., Tanaka, S. and Deshpande, A. (1999), “Measuring fiber orientation in nonwovens part V: real webs”, Textile Research Journal, Vol. 69, pp. 185-92. Rawal, A. and Anandjiwala, R. (2006), “Relationship between process parameters and properties of multifunctional needlepunched geotextiles”, Journal of Industrial Textiles, Vol. 35, pp. 271-85. TS EN ISO 9863-1 (2006), Geosynthetics-determination of Thickness at Specified Pressures, Turkish Standards Institution, Ankara. TSE EN ISO 10319 (1998), Geotextiles – Wide-width Tensile Test, Turkish Standards Institution, Ankara. Corresponding author Umit Halis Erdogan can be contacted at:
[email protected]
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Textile materials with a pH-sensitive function
A pH-sensitive function
Lien Van der Schueren and Karen De Clerck Department of Textiles, Ghent University, Zwijnaarde, Belgium
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Abstract Purpose – The purpose of this paper is to develop textile materials with a pH-sensitive function. Design/methodology/approach – As a start point, the feasibility of incorporating pH-indicators in conventional textiles using standard dyeing processes was investigated. Next, a pH-indicator was incorporated into a nylon nanofibrous structure by adding the dye to the polymer solution before the start of the electro-spinning process. Findings – The authors’ results proved that it is possible to develop a pH-sensor using conventional textiles dyed by a standard dyeing process. Also, the incorporation of a pH-indicator dye into a nanofibrous structure was possible. Moreover, reproducible samples could be obtained. Furthermore, the majority of the obtained textile structures showed a clear colour change with a change in acidity. This halochromic behaviour was, however, different from the behaviour of the dyes in solution due to dye-fibre interactions. Originality/value – The knowledge obtained in this study can lead to the development of a textile pH-sensor. This sensor can be used in a broad field of applications since a colour change is a non-disturbing but clear signal which can perform a first warning function. Keywords Textiles, Acidity, Alkalinity, Colours technology Paper type Research paper
1. Introduction Colour changing textiles have recently gained much interest from the academic world. Although previously categorized as unwanted, colour-changing textiles can be used in a broad field of applications. The reason for this is that a colour change is a non-disturbing, but clear signal which can perform a first-warning function (Bamfield, 2001). A whole range of triggers can cause a colour change. The most known chameleon textiles have temperature and light as stimulus for the colour change and are designated as thermochromic and photochromic systems (Mather, 2008). Despite of the whole range of possible applications, much less is known about halochromic systems. The degree of acidity is, however, an important parameter in daily live and a pH-sensitive sensor could, therefore, be very useful (Yuqing et al., 2005). Literature about halochromism is mainly focussed on the development of new halochromic dyes (Griffiths and Cox, 2000; Koh et al., 2003). The following step – the application of these dyes on a substrate material – is not yet studied in detail. This step is, however, essential if these newly developed dyes want to be used in practice (Van der Schueren and De Clerck, 2010). The major aim in the current study is, therefore, applying pH-sensitive dyes on textile materials. The newly developed halochromic dyes mentioned above are, however, not yet available on the market. On the other hand pH-indicators, which are normally used to determine the pH of a solution, are easily available and also exhibit the desired halochromic properties.
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Electro-spinning from polymer solutions is a process which is able to produce nanofibrous nonwovens. It is based on the application of an electric field. This field is applied between the tip of a nozzle, through which the polymer solution is flowing, and a collector plate. Because of the applied voltage, the droplet at the tip of the nozzle deforms and a Taylor cone is formed. Next, a jet is drawn from this cone, which elongates due to bending and splaying. The so-formed nanofibres are deposited on the collector plate. The obtained nanofibrous structure shows some unique characteristics such as an extremely high-surface area, a high porosity and a small-pore size (de Vrieze et al., 2010). These properties can be useful in a whole range of applications, one of them being wound dressings since bacteria cannot reach the wound area while exchange of liquids and gases with the environment is still possible. Incorporating pH-sensitive dyes into nanofibrous structures would lead to a unique material. A great advantage is that the dyes can be added at the start of the production process and that thus the extra functionalisation step in the procedure can be avoided. However, before being able to incorporate the dyes into nano nonwovens, it is essential to investigate them in conventional textiles. In this study, pH-indicator dyes were applied on different textile materials. First, the incorporation was studied in conventional cotton and nylon. The functionalisation was realized by dyeing the fabrics using standard dyeing processes. Next, a pH-indicator was added to a nylon solvent solution and electro-spun. Finally, the halochromic behaviour of the produced structures was investigated. 2. Materials and methods 2.1 Materials Cotton fabric was supplied by Utexbel (Ronse, Belgium), nylon 6 and 6.6 fabrics were supplied by Concordia Textiles (Waregem, Belgium). The pH-indicator dyes, hydrochloric acid, acetic acid and sodium hydroxide were obtained from Sigma-Aldrich. Also the nylon 6.6 pellets used for electro-spinning were supplied by Sigma-Aldrich. 2.2 Methods Conventional dyeings were performed in a Mathis Labomat BFA-8 dyeing machine using a direct dyeing process for cotton and an acid dyeing process for nylon. During these processes, the dyebath was first heated from room temperature to 1008C at a heating rate of 38/min. Next, the bath was kept at 1008C for 30 min after which the bath was cooled to 408C at a cooling rate of 9.98/min. When dyeing cotton, sodium chloride was used to increase the exhaustion. The dyebaths for dyeing nylon were set at pH 5 using acetic acid. In the electro-spinning process, the polymer solution was pumped from a 20 ml syringe into a 15.24 cm long needle with an inner diameter of 1.024 cm. A KD Scientific Syringe Pump Series 100 regulated the flow rate of the solution at 3.5 ml h2 1. The tip to collector distance was fixed at 6 cm. The voltage was set at 25 kV. The morphology of the electro-spun structures was examined using a scanning electron microscope (FEI QUANTA 200 F). Prior to the SEM-measurements, the sample was coated with gold using a sputter coater (Balzers Union SCD 030). The pH-values were measured using a combined reference and glass electrode from VWR. The UV-Vis spectra were recorded with a Perkin-Elmer spectrophotometer.
3. Results and discussion 3.1 Conventional textiles Cotton and nylon were dyed with a set of pH-indicators. The results of this first screening are summarized in Table I. It is clearly seen that certain pH-indicator dyes show good characteristics as dyes for cotton and/or nylon. The results also indicate that the halochromic properties can disappear once the dyes are incorporated in a textile fabric by a dyeing process. On the other hand, enough pH-indicator textile systems remain their halochromic behaviour and thus are worth to study in more detail. The dye Brilliant Yellow was chosen to study more in depth. Brilliant Yellow (Figure 1) is anionic diazo dye and is used as a pH-indicator in solution in the neutral region. Its colour is changing from yellow to orange in the pH-range 6.5-8.0. The optimum dye conditions of the pH-indicator on cotton were found by evaluating the exhaustion at different dye and salt concentrations. The results suggest that a dye concentration of 0.3 per cent omf and a salt concentration of 30 per cent omf would give a high exhaustion (Figure 2) with in the meantime an acceptable colour depth. The water fastness of the dyed fabric was however low. Therefore, an after-treatment was performed with a cationic fixation agent which resulted in an improvement of the water fastness of two units on the greyscale. To characterize the halochromism of Briliant Yellow on cotton, the fabric was immersed in water baths with a specific pH. Next, the colour of the samples was measured with UV-Vis spectroscopy. The results of these measurements are shown in Figures 3 and 4, both for the untreated and treated cotton fabrics. It is seen that the after-treatment has an influence on the colour, as could be expected since the fixation agent forms a complex with the dye (Broadbent, 2001). Furthermore, it was also found that there is a difference in halochromism of the dye depending on the medium in which the dye is located since the pH-range of Brilliant Yellow on cotton is broader than the range of Brilliant Yellow in solution.
Ethyl Orange Methyl Orange Methyl Red Rosolic acid Alizarin Red Alizarin Brilliant Yellow Xylenol Blue
Cotton
Polyamide 6
Polyamide 6.6
XX XX XX X XX XX X XX
X X – X X X X X
X X – X X X X X
Notes: X ¼ good dyeing properties; XX ¼ pH-sensitivity
HO N
N
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Table I. Screening of pH-indicators on conventional textiles
O ONa S O O NaO
N
S
N
O OH
Figure 1. Molecular structure brilliant yellow
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(%) exhaustion
90 80 70 60
Figure 2. Exhaustion of the dyebath as a function of the dye and salt concentration
50
0.1:10
0.2:10 0.3:10 0.5:5 0.5:10 0.5:30 0.7:10 Dye concentration: salt concentration (% omf)
1:10
Figure 3. Normalized Kubelka-Munk spectra of brilliant yellow on cotton treated with fixation agent at pH 3, 6 and 9
Kubelka-Munk (A.U.)
pH = 3 pH = 6 pH = 9
200
300
400
500 NM
600
700
800
1.2
Figure 4. Normalized Kubelka-Munk of brilliant yellow on untreated and treated cotton as a function of pH
Kubelka-Munk (A.U.)
1 0.8 0.6 Untreated Untreated Treated Treated
0.4 0.2 0 2
3
4
5
6 pH
7
8
9
10
3.2 Nanofibrous nonwovens The pH-indicator Ethyl Orange was added to the polymer solution before the start of the electro-spinning process. It was seen that the pH-indicator addition had no influence on the process since it still was possible to spin in steady state. Droplets were, however, noticed when a high concentration of Ethyl Orange was used, probably due to the insolubility of the dye at those high concentrations (Figure 5). Table II lists the average fibre diameter of nylon 6.6 nonwovens with different amounts of Ethyl Orange. It is seen that the diameter is not influenced by the dye addition. The obtained samples showed pH-sensitive properties, but the dye release was enormous. Therefore, the obtained material cannot be used as pH-sensor. To check the feasibility of producing halochromic nonwovens, another pH-indicator, Alizarin, was added. With this pH-indicator, the dye release was significantly less and a clear colour change was observed. This is shown in Figure 6 in which the halochromism of Alizarin incorporated in a nanofibrous structure is presented.
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4. Conclusions Our results proved that it is possible to develop a pH-sensor using conventional textiles dyed by a standard dyeing process. Also the incorporation of a pH-indicator into a nanofibrous structure was possible. Moreover, the fibre diameters were not influenced
Figure 5. Droplets in an electro-spun nonwoven with 5.4 per cent omf ethyl orange
Dye concentration (% omf) 0.16 0.32 0.54 1.35 5.4
Average fibre diameter (nm)
SD (nm)
181 186 186 181 178
20 21 22 19 23
Table II. Average fibre diameter of electro-spun nonwovens with varying amount of ethyl orange
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Figure 6. Normalized Kubelka-Munk of Alizarin in a nylon 6.6 nonwoven
Kubelka-Munk (A.U.)
1 0.8 444 nm 531 nm
0.6 0.4 0.2 0 0
5
10
15
pH
by the dye concentration and reproducibility could be obtained. Furthermore, the majority of the obtained textile structures showed a clear colour change with a change in acidity. This halochromic behaviour was, however, different from the behaviour of the dyes in solution due to dye-fibre interactions. References Bamfield, P. (2001), Chromic Phenomena, Technological Applications of Colour Chemistry, Royal Society of Chemistry, Cambridge. Broadbent, A. (2001), Basis Principles of Textile Coloration, Society of Dyers and Colourists, Cambridge. de Vrieze, S., Westbroek, P., van Camp, T. and de Clerck, K. (2010), “Solvent system for steady-state electrospinning of polyamide 6.6”, Journal of Applied Polymer Science, Vol. 115 No. 2, pp. 837-42. Griffiths, J. and Cox, R. (2000), “Colour and halochromic properties of azo dyes derived from 10-methyl-9-methylene-9,10-dihydroacridine as coupling component”, Dyes and Pigments, Vol. 47 Nos 1/2, pp. 65-71. Koh, J., Greaves, A.J. and Kim, J.P. (2003), “Synthesis and spectral properties of alkali-clearable azo disperse dyes containing a fluorosulfonyl group”, Dyes and Pigments, Vol. 56 No. 1, pp. 69-81. Mather, R. (2008), “Intelligent textiles”, Review of Progress in Coloration and Related Topics, Vol. 31 No. 1, pp. 36-41. Van der Schueren, L. and De Clerck, K. (2010), “The use of pH-indicator dyes for pH-sensitive textile materials”, Textile Research Journal, Vol. 80 No. 7, pp. 590-603. Yuqing, M., Jianrong, C. and Keming, F. (2005), “New technology for the detection of pH”, Journal of Biochemical and Biophysical Methods, Vol. 63 No. 1, pp. 1-9. Corresponding author Lien Van der Schueren can be contacted at:
[email protected]
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Thermo-physiological comfort of a PES fabric with incorporated activated carbon Part II: wear trials R. Splendore Associazione Tessile e Salute, Biella, Italy
Thermophysiological comfort 283 Received 16 December 2010 Revised 23 February 2011 Accepted 23 February 2011
F. Dotti Dipartimento di Scienze dei Materiali e Ingegneria Chimica, Politecnico di Torino, Torino, Italy
B. Cravello Associazione Tessile e Salute, Biella, Italy, and
A. Ferri Dipartimento di Scienze dei Materiali e Ingegneria Chimica, Politecnico di Torino, Torino, Italy Abstract Purpose – The purpose of this paper is to consider the thermal-physiological comfort performances of a sport shirt made of a polyester (PES) fabric with incorporated activated carbon. After having characterized the modified PES fabric in Part I, the results of a wear trial campaign are shown and discussed in this work. Design/methodology/approach – The wear trials have been carried out under a controlled physical activity. A short-and-intense effort and an intermittent effort of milder intensity were carried out twice by each volunteer: once wearing a shirt made of the modified PES fabric and the other one wearing an analogous shirt made of a conventional PES fabric. Findings – When sweating was moderate, the modified PES shirt was judged as more comfortable on the average. As the effort became harder, the modified PES fabric turned out to be less comfortable than the conventional one. In the final recovery stage, the conventional PES was still more comfortable than the modified PES. This behaviour was justified according to the findings of Part I: at the beginning, the prevailing effect was the adsorbing ability of carbon particles that buffer sweat impulses, giving the user a pleasant dry sensation. Then, when sweating became intense, the lower evaporative cooling of the modified PES fabric became the key factor governing the physiological comfort of the garment. This is confirmed by a slightly higher skin temperature measured during the modified PES fabric trials. Finally, a post-exercise chill sensation was felt with the modified PES fabric, due to a longer drying time. Originality/value – The paper presents a comprehensive study of the thermo-physiological comfort of a fabric containing activated carbon particles. Keywords Wear trial, Thermo-physiological comfort, PES, Activated carbon, Thermal testing, Fabric testing, Clothing Paper type Research paper
The authors gratefully acknowledge the Piemonte Regional Government, which financed this work within the HITEX project (D.G.R No. 227-4715).
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1. Introduction The performances of fabrics for sport and active wear have been continuously improved in recent years and nowadays a variety of fabrics are available on the market in order to satisfy the needs of the most demanding customers (Buirski, 2005). Sweat absorption and rapid drying are two critical functions that must be fulfilled by a sportswear fabric. To keep the wearer’s body dry, fabrics should be able to wick moisture away from skin and distribute it over the surface, reducing drying times (Wong and Li, 2004). A variety of technological solutions have been proposed to improve the liquid management of hydrophobic fibres such as polyester (PES): for instance, a structured cross-sectional shape distributing liquid on a wider surface is the principle exploited in Coolmaxe technology. Using micro-fibres is another way to enhance liquid management since the finest the fibre diameter, the larger the yarn surface area (Umbach, 1993). Finally, a number of chemical treatment such as enzymatic and alkali treatments can be carried out to obtain a hydrolyzed PES (Hsieh, 1998; Zeronian et al., 2003). Recently, the inclusion of activated carbon particles derived from recycled coconut shell has been presented on the market as an effective way to modify moisture absorption of a man-made fibre. Thanks to their huge surface on which a liquid can be absorbed, activated carbon particles provide moisture adsorption and odour control. In Part I, a conventional and a carbon-particle containing PES fabrics have been compared as far as the comfort-related properties are concerned and a double effect has been observed due to carbon particle inclusion: fabric hydrophilicity dramatically increased but, on the other hand, drying time lengthened (Splendore et al., 2010). These two effects act in opposite directions as far as comfort is concerned: a hydrophilic behaviour is desired for absorbing sweat but liquid must be quickly evaporated to provide cooling. However, fabric physical characterization does not provide an exhaustive comfort evaluation. In Figure 1, the five-level system for the analysis of the physiological properties of textiles and garment proposed by Umbach (1988) is shown. Three out of five levels involve the subjective evaluation of a panel
Level 5 Field test Level 4 Limited field test Level 3 Controlled wear test in climatic chamber, physiological data/subjective ratings Level 2 Biophysical analysis of garment (manikin)
Figure 1. Procedure for the analysis of the physiological properties of textiles and garment
Level 1 Biophysical analysis of textiles (skin model)
of people who tested the garment both in a controlled environment and in field. Using human subjects to evaluate clothing will reduce control but it is the only way to provide a realistic and comprehensive comfort evaluation (Parson, 2003). The user performance tests are especially needed when level 1 findings did not give a univocal response about comfort, as it happened for the fabrics investigated in this work. Two long-sleeved shirts, one made of the carbon-containing PES fabric and the other one of a conventional PES fabric, were worn by four volunteers (two men and two women, about 30 year old) during two physical tests, one short and intense and the other one intermittent and milder. All subjects were healthy and exercises regularly. To study the effect of a protract contact between skin and a carbon-particle-including fabric, a patch test was carried out and skin physiological parameters investigated. Residual detergent, a responsible of textile-induced dermatitis (Belsito et al., 2002), may be present in a larger amount on a carbon-particle-containing fabric than in a conventional one as carbon particles tends to retain detergent. The aim of the work was to evaluate whether carbon particle inclusion would increase the overall comfort of the garment both on an objective and subjective evaluation scale. 2. Materials and experiments The conventional PES and the modified PES fabrics have the same honeycomb structure. This knitting construction is frequently used in sportswear because it provides space between skin and textile, thus avoiding a “clingy” sensation in case of sweating. A detailed characterization of the two fabrics is presented elsewhere (Splendore et al., 2010). The fabric characterization pointed out that the modified PES fabric has an enhanced hydrophilicity with respect to the conventional one but, on the other hand, water desorption is slow and the drying time of the active carbon containing fabric is longer than that of the conventional PES. Moreover, thermal resistance and water vapour resistance of the modified fabric are slightly worse with respect of conventional PES. In Figure 2, a picture of two long-sleeved shirts tailored with the two fabrics is shown. The tailoring of the two items is the same. 2.1 Patch tests Patch tests were carried out with an internal standardized method to evaluate any change in skin physiology of the four volunteers due to a protract contact with the fabrics. Transepidermal water loss (TEWL), pH, moisture content and erythema index were measured by means of the Cutometer MPA580 on two delimited areas on the inner forearm at time zero. An area was subsequently covered with a 4 £ 4 cm2 fabric sample while the other one was let free from any covering. After 24 hours, the fabric was removed and skin parameters were evaluated again on both areas. In order to take into account daily variability, the uncovered area was used as a control zone in the following way: for each skin parameter, the value measured on the test area immediately after the removal of the fabric was divided by the value measured on the control area at the same time. Skin parameters were evaluated into the climatic chamber at 238C and 50 per cent of relative humidity. 2.2 Wear trials A wear trial campaign was conducted in a climatic chamber with temperature and relative humidity set to 278C and 60 per cent, respectively. The temperature was set to quite a high value, so that the sweating was abundant. An athletic performance
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Figure 2. The two long-sleeved shirt
(a)
(b)
Notes: (a) Made of carbon-particle containing PES; (b) made of conventional PES
depends on personal training level, kind of training, environmental conditions and clothing configuration. In this work, the environmental conditions were fixed, while the personal training level, the kind of training and the clothing configuration were assumed as factors in a general full factorial design. The software Minitab 15 was used for randomizing the runs. The four volunteers involved in the wear trials, though being all amateurs, have different training levels. Thus, four levels were assigned to this factor. The clothing configuration factor has two levels as two shirts were used in the trials, one containing active carbon particles and the other one without them. Finally, each volunteer trained according to two kinds of training: a short-and-intense one and a long-and-milder one. A summary of the design of experiments is shown in Table I. The wear trials were replicated once. Thus, the total number of runs was 16. The observations were collected under the same environmental conditions in the same laboratory, thus they are all included in one single block. The volunteers acclimatized for 30 min; the test procedure was explained in detail prior the test taking place. Temperature sensors were attached at different body locations (chest, shoulder-blade, deltoid, elbow) and the basal temperature of the bare-breasted subjects was measured for 10 min before the volunteer wears the shirt. The bare-breast phase was aimed at ensuring that the basal physiological skin
Table I. Summary of the design of experiments
Number of factors Name of the factors Levels of factors Replicates Blocks Total runs
3 Personal training level; clothing configuration; kind of training 4; 2; 2 1 1 16
temperature was approximately the same in the two wear trials for each subject. Then, the subject rested for 10 min before starting the physical activity wearing the clothing configuration under investigation. The clothing configuration included the long-sleeved shirt under investigation, cycling shorts, short socks and gym shoes. Two trial sets were carried out by each volunteers in different days, one simulating an intense-and-short strain and the other one a intermittent strain of medium intensity. In the first case, the subject cycled on a cyclo-ergonometer Tunturi Bike T6 (Eve srl, Milan) according to the VO2 max test. Starting from 30 W, the pedal resistance increased by 20 W every 2 min so that the strain increased stepwise. In this test, the volunteer must reach his/her anaerobic threshold and then he/she must continue cycling in anaerobic conditions for some minutes, according to his/her endurance. This phase was followed by a recovery phase during which the volunteer cycled at 30 W for 5 min. Finally, the volunteer rested for 30 min. In the second wear trial, an intermittent physical effort was performed: the pedal resistance was set to 90 W and a 10-min cycling activity was repeated three times. The volunteer stayed at rest for 10 min between one cycling phase and the next one. Finally, a 30 min rest followed. A questionnaire was prepared to monitor the volunteers sensations during the different steps of the VO2 max test. The questionnaire, reported in the Appendix, was answered after 6 and 12 min from the beginning of the physical activity, in correspondence of a mechanical power of 65 and 110 W, respectively, and after 15 and 30 min from the end of the physical activity.
Thermophysiological comfort 287
3. Results and discussion The statistical analysis of the patch test data was generated using Minitab 15. The analysis of variance (ANOVA) was used to test the effect of the fabric and that of the subject on physiological skin parameters. The results are shown in Table II. The p-values are well above the significant level, except for pH. This means that pH is the only skin parameter influenced by the fabric. Nevertheless, pH values remain within a physiological limit for both fabrics; that is, none of the two fabrics cause any pathological change in skin pH. The upper body skin temperature profiles are shown in Figures 3 and 4 for the two sets of wear trials. An upper body skin temperature was defined in the following way: T UB ¼ 0:357 · T Shoulder þ 0:357 · T Chest þ 0:143 · T Deltoid þ 0:143 · T Elbow
ð1Þ
where the weights take into account the relative extension of the skin areas. The upper body skin temperature rather than the mean skin temperature defined in the UNI EN
Variable TEWL pH Moisture content Erythema index Note: p-values in the ANOVA
Factor: fabric 0.314 0.000 0.341 0.172
Table II. Patch test results
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Figure 4. Upper body skin temperature in the three-cycle test
PES
34.50
34.00
33.50
33.00
32.50 0
10
20
30 40 Time (min)
50
60
70
Note: Mean value among the volunteers
Upper body skin temperature (°C)
Figure 3. Upper body skin temperature in the VO2 max test
Modified PES Upper body skin temperature (°C)
288
35.00
33.50 Modified PES PES 33.00
32.50
32.00 0
10
20
30
40
50
60
70
80
90
100
Time (min)
Note: Mean value among the volunteers
ISO 9886 has been used in this work because the upper body skin temperature is supposed to be more influenced by the shirt than the mean skin temperature. In Figure 3, the temperature trend in the VO2 max test is shown. When the subject wore the shirt at 10 min, skin temperature increased and reached an approximately steady value. In the first 10 min of activity (from 20 to 30 min), when the physical effort was of mild to medium intensity, the temperature stayed almost constant. Then, a steep increase in skin temperature was shown in correspondence to the recovery phase
(from 35 to 40 min). This means that the increase of the upper body skin temperature shows some delay with respect to the production of metabolic heat (the time needed by heat to reach the outer surface). The upper body skin temperature in the three-cycle test is shown in Figure 4. Since the intensity of the physical activity was lower, the maximum temperature reached in the three-cycle test was lower by about 18C with respect to the VO2 max test. The temperature peaks are slightly higher for the modified PES fabric in both training tests. Since the evaporative rate of the modified fabric is slower, as demonstrated by the lengthening of the drying time, a lower amount of metabolic heat is removed during the physical activity and this leads to a higher skin temperature. Moreover, the thermal resistance of the modified fabric is slightly higher than that of PES fabric, as shown in Part I, and this contributes to a more difficult heat removal. It can be observed that a lower temperature is measured when wearing the modified PES fabric at the end of the test in both the VO2 max (Figure 3) and the three-cycle test (Figure 4). This effect is due to a longer drying time of the modified PES fabric, that is 25 per cent longer as reported in Part I. The activated carbon particles made the fabric more hydrophilic and this has the counterfeiting effect of drying time lengthening. So the presence of a wet fabric in contact with skin keeps its temperature lower. During the three-cycle test, the relative humidity of the thin air layer between skin and garment has been evaluated via a small sensor, called smart button, that was positioned on the chest and spaced out from skin and textile thanks to a small grid. The main aim of the three-cycle test was exactly that of investigating the microclimate. In fact, in the VO2 max test, the humidity sensor reached a saturation value and no interesting trends could be observed. Owing to the bent position adopted by the wearer during cycling, the best location for a microclimate measurement was found to be the chest. The humidity of the microclimate increased dramatically at the beginning of the physical activity at 20 min. Thus, unlike skin temperature which showed a delay, microclimate humidity is a prompt signal that metabolic heat has begun to being produced. The increase in the microclimate humidity is due to the sweat impulses occurring from the beginning of the physical activity. As shown in Figure 5, microclimate humidity was found to be lower with the modified PES shirt on. Thus, despite a similar water vapour permeability and a lower air permeability, the modified PES fabric guarantees a drier microclimate thanks to the carbon particle inclusion. This was confirmed by the wettability measurement that was found to be greater for the modified PES than the conventional one. The sensorial differences perceived by the volunteers when wearing the two shirts during the VO2 max were captured through the questionnaire reported in the Appendix. For each question, a score was assigned to each answer: the lowest score was assigned to the most uncomfortable sensation and the highest score to the most comfortable one. The scores reported in Table III are the weighted sum of the subjects’ answers, where the weights are the answers frequencies. In the last row in Table III, the sum of the absolute differences was reported in order to point out the entity of difference between the shirts scores. At rest, the scores obtained by the modified fabric were generally better. As reported in Part I, the modified fabric has a larger thermal diffusivity than the PES fabric. Thermal diffusivity is the transient state thermal property describing the rate of temperature propagation through the material (Hes and de Araujo, 1996). This property quantifies the cool feeling immediately after
Thermophysiological comfort 289
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80.0
290
Relative humidity (%)
75.0 70.0 65.0 60.0 Modified PES 55.0
Figure 5. Humidity of the microclimate in the three-cycle test
PES
50.0 0
10
20
30
40
50
60
70
80
90
100
Time (min)
Note: Mean value among the volunteers
putting a garment on. Thus, the better comfort sensation experienced in the first min of the wear trial could be due to the higher thermal diffusivity of the modified PES fabric. At 6 min, the clothing comfort (question 4) and humidity acceptability (question 2) were better for the modified PES shirt while thermal acceptability (question 1) was worse. This result reflects the modified fabric features that is slightly thicker and more insulating than the conventional fabric and contains carbon particles that buffer the sweat impulses keeping the body drier. At 12 min, the scores of the two shirts are more similar to each other as shown by the small values of the absolute difference sum. This result could be ascribed to the difficulty of the subject in detecting any difference between the two shirts when the volunteer is psychologically involved in a hard physical work. The main difference was observed in the recovery phase 15 min after the end of the physical activity: it is noteworthy that the conventional PES fabric was felt much more transpiring (question 3) than the modified one at that time. This outcome is attributable to the fact that the modified fabric stays wet for a longer time after the end of the physical activity and this feature brings an occlusive sensation to the wearer. Finally, 30 min after the end of the physical, activity both shirts were dry again and the modified PES obtained a better score on humidity acceptability as it happened at the beginning of the test. From the experiments under two sorts of training, conclusions concerning the possible end-uses of the modified PES can be drawn: this material with its superior ability to remove sweat from skin is suitable for sports activities of soft-to-medium intensity in a cool-to-mild environment. Its use is not recommended during intense physical training in a hot environment, when thermoregulation becomes of primary importance, due to the slow desorption of the liquid from the active carbon particles which reduces the heat rate from the body. 4. Conclusion In this work, thermo-physiological comfort of a sport long-sleeve shirt has been investigated via wear tests. A hard and a medium intensity physical activity were
3.25 4 3.75 3.25
3.5
3.75
4.5
3.75
Note: Abs. diff. – absolute difference
Q1 – Thermal acceptability Q2 (ex5) – Humidity acceptability Q3 – Clothing transpiring feature Q4 – Clothing comfort Sum 0.5 1.75
0.75
0.25
0.25
3
3
3.5
2.5
2.75
3
3
3.25
0.25 1.5
0
0.5
0.75
2
1.5
1.5
1.5
2.25
1.5
1.25
1.5
0.25 0.5
0
0.25
0
2.5
1.5
1.75
2
2.75
3.25
1.75
3.25
0.25 3.25
1.75
0
1.25
0.5 2.25
3 2.5
2.25 3
0.75
2.5
3.25
0.75
3.5
3.75
0.25
12 min after the At rest just before the 6 min after the beginning 15 min after the end of the 30 min after the end of beginning of the beginning of the test of the VO2 max test VO2 max test VO2 max test the VO2 max test Mod. pes Pes Abs. diff. Mod. pes Pes Abs. diff. Mod. pes Pes Abs. diff. Mod. pes Pes Abs. diff. Mod. pes Pes Abs. diff.
Thermophysiological comfort 291
Table III. Results of the questionnaire
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carried out in a quite warm and humid climate (278C and 60 per cent RH). The results were interpreted also in the light of the fabric physical measurements presented in Part I. The modified PES fabric was generally judged as more comfortable at rest and under a moderate physical activity thanks to the carbon particle inclusion that adsorb sweat impulses. The carbon including fabric turned out to be less comfortable at the end of the physical activity due to the lengthening of the drying time which brings about an unpleasant post-exercise chill sensation. According to the results of the physical characterization (Part I) and the wear tests (Part II), the modified PES seems to be ideal for realizing sportswear to be used in mild conditions as far as the physical effort and climatic conditions are concerned. For the fabric to be used in sportswear for extreme conditions, the liquid management of the modified PES should be improved with the aim of speeding up the fabric drying time. This goal should be achieved only by promoting the desorption rate of water from the active carbon containing PES. Up to now, we could not find any data on this issue in literature. References Belsito, D.V., Fransway, A.F., Fowler, J.F. Jr, Sherertz, E.F., Maibach, H.I., Mark, J.G. Jr, Mathias, C.G., Rietschel, R.L., Storrs, F.J. and Nethercott, J.R. (2002), “Allergic contact dermatitis to detergents: a multicenter study to assess prevalence”, J. of Am. Acad. Dermatol., Vol. 46 No. 2, pp. 200-6. Buirski, D. (2005), “Market overview”, in Shishoo, R. (Ed.), Textile in Sports, Woodhead Publishing in Textiles, Cambridge, pp. 15-24. Hes, L. and de Araujo, M. (1996), “Effect of mutual bonding of textile layers on thermal insulation and thermal contact properties of fabric assemblies”, Tex. Res. J., Vol. 66 No. 4, pp. 245-50. Hsieh, Y.L. (1998), “Enzymatic hydrolysis to improve wetting and absorbency of polyester fabrics”, Text. Res. J., Vol. 68 No. 5, pp. 311-19. Parson, K. (2003), Human Thermal Environments, Taylor & Francis, New York, NY. Splendore, R., Dotti, F., Cravello, B. and Ferri, A. (2010), “Thermo-physiological comfort of a PES fabric with incorporated activated carbon – Part I: preliminary physical analysis”, Journal of Clothing Technology and Clothing Science, Vol. 22 No. 5, pp. 333-42. Umbach, K.H. (1988), “Physiological tests and evaluation models for the optimization of the performance of protective clothing”, in Mekjavic, I.B., Banister, E.W. and Morrison, J.B. (Eds), Environmental Ergonomics, London, pp. 139-61. Umbach, K.H. (1993), “Moisture transport and wear comfort in micro-fibre fabrics”, Melliand English, Vol. 2, pp. 78-80. Wong, A.S.W. and Li, Y. (2004), “Relationship between thermophysiological responses and psychological thermal perception during exercise wearing aerobic wear”, Journal of Thermal Biology, Vol. 29, pp. 791-6. Zeronian, S.H., Wang, H.Z. and Alger, K.W. (2003), “Further studies on the moisture-related properties of poly(ethylene terephtalate)”, Journal of Applied Polymer Sciences, Vol. 41 Nos 3/4, pp. 527-34.
Thermophysiological comfort
Appendix Questionaire for thermo-physiological
comfort assessment of clothing
Date: ___________________________Hour: ____________ Subject no. __ __________________________ Item of clothing ____________________________________
293 (1) How do you judge your thermal comfort condition? Acceptable (1)
Just acceptable (2)
Hardly acceptable (3)
Non acceptable (4)
Hardly acceptable (3)
Non acceptable (4)
(2) How do you judge your humidity condition? Acceptable (1)
Just acceptable (2)
(3) How do you judge your clothing ? Transpiring (5)
Non Transpiring (1)
I don't know
(4) How do you feel your clothing on the skin ? Comfortable
Fairly comfortable
Slightly uncomfortable
Uncomfortable
Corresponding author A. Ferri can be contacted at:
[email protected]
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IJCST 23,5
294 Received 7 January 2011 Revised 8 March 2011 Accepted 8 March 2011
Predicting compression and surfaces properties of knits using fuzzy logic and neural networks techniques Selsabil El-Ghezal Jeguirim Textile Research Unit, ISET Ksar-Hellal, Ksar Hellal, Tunisia and ENSISA Laboratoire de Physique et Me´canique Textiles (LPMT), Mulhouse, France
Mahdi Sahnoun, Amal Babay Dhouib and Morched Cheickrouhou Textile Research Unit, ISET Ksar-Hellal, Ksar Hellal, Tunisia, and
Laurence Schacher and Dominique Adolphe ENSISA Laboratoire de Physique et Me´canique Textiles (LPMT), Mulhouse, France Abstract Purpose – The purpose of this paper is to model the relationship between manufacturing parameters, especially finishing treatments and instrumental tactile properties measured by Kawabata evaluation system. Design/methodology/approach – Two soft computing approaches, namely artificial neural network (ANN) and fuzzy inference system (FIS), have been applied to predict the compression and surface properties of knitted fabrics from finishing process. The prediction accuracy of these models was evaluated using both the root mean square error and mean relative percent error. Findings – The results revealed the model’s ability to predict instrumental tactile parameters based on the finishing treatments. The comparison of the prediction performances of both techniques showed that fuzzy models are slightly more powerful than neural models. Originality/value – This study provides contribution in industrial products engineering, with minimal number of experiments and short cycles of product design. In fact, models based on intelligent techniques, namely FIS and ANNs, were developed for predicting instrumental tactile characteristics in reference to finishing treatments. Keywords Textile industry, Fuzzy inference, Neural networks, Finishing treatments, Knitted fabric, Tactile properties, KES-F, Surface properties of materials Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 5, 2011 pp. 294-309 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111166239
1. Introduction The integration of fabrics tactile characteristics for product development, quality control and market research in textile industry is widely increasing. These tactile characteristics can be evaluated using sensory or instrumental approaches. The sensory evaluation provides description of sensory attributes as perceived by a group of trained assessors or novice consumers (Civille and Dus, 1990; Brand et al., 1998; Mackay el al., 1999; Giboreau et al., 2001; Meilgaard et al., 1999; Philippe et al., 2003, 2004; Pense´-Lhe´ritier et al., 2006; Strazdiene et al., 2006). Whereas, the instrumental evaluation can be performed
by several devices, such as the Kawabata (1975, 1980, 1982) evaluation system. This system enables accurate and reproducible measurement of fabric low-stress mechanical properties, namely tensile and shearing, bending, compression, and surface properties at low stress, simulating the forces encountered when handling a fabric. Several investigators have used statistics and multivariate analysis, such as multiple factor analysis and principal component analysis (PCA) for analyzing the relevant instrumental and sensory properties data (Zeng et al., 2008). Furthermore, a wide range of statistical or empirical methods have been proposed for modelling the relationship between instrumental measurements and sensory properties. In particular, PCA (Bishop, 1996; Danzart, 1998; El-Ghezal Jeguirim et al., 2010), Weber-Fechner’s law (Matsuo, et al. 1971) and Steven’s power law (Elder et al., 1984), regression analysis (Inoue et al., 2010) have been usually applied. Although classical computing techniques are relatively efficient to analyse sensory data, some limitation related to the non-linear relations in this domain has been reported (Zeng et al., 2008). Currently, new methods based on intelligent techniques (fuzzy logic, neural networks, etc.) are used to treat a great number of textile applications (Sette and Van Langenhove, 2003; Vassiliadis et al., 2010), such as predicting the mechanical properties of fabrics (Park et al., 2001; Stylios et al., 2002; Stylios and Powel, 2003; C¸ay et al., 2007; Karthikeyan and Sztandera, 2010) and the sewing performance (Jaouadi et al., 2006; Hui et al., 2007). These methods have shown many advantages in characterizing some complex concepts related to sensory evaluation such as comfort. Moreover, the intelligent techniques are suitable for modeling complex relations such as the relation between sensory data and mechanical parameters, exhibiting advantages in performance over more conventional mathematical techniques. Zeng et al. have developed a fuzzy inference system (FIS) for modelling the relationship between sensory attributes and the mechanical features (Zeng et al., 2004). Hui et al. have developed a neural network to predict the consumer sensory data from fabric properties (Hui et al., 2004). Moreover, neural network and FIS-based models were developed for predicting sensory attributes or physical features of knits from production parameters, such as count and twist of yarns, spinning type and English gauge of knitting machine (Zeng et al., 2004; El-Ghezal Jeguirim et al., 2009). However, there has been no published literature, which focuses on the prediction of tactile characteristics from the finishing treatments. In this research, an attempt has been made to model for the first time the effect of some finishing treatments, namely bleaching, dyeing, bio-polishing, softening, emerizing and calendering on the compression and surface characteristics. For this purpose, artificial neural network (ANN) and FIS-based models were developed. A comparison of the prediction performances of these both models was then performed. 2. Materials and methods 2.1 Materials In this investigation, Jersey knitted fabrics were industrially produced. The knitting machine gauge was equal to 28. The used yarns were 100 percent cotton and their count was equal to 25 tex. These fabrics were treated by boiling and the following finishing stages (Table I): (1) Bleaching or dyeing. Two dyeing processes have been used: jet dyeing and air flow machine.
Compression and surfaces properties 295
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Table I. Characteristics of test knitted fabrics
No.
Bleaching or dyeing
Bio-polishing
Softening
Emerizing
Calendering
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
Bleaching Bleaching Bleaching Bleaching Air-flow dyeing light shade Jet dyeing Bleaching Bleaching Bleaching Bleaching Jet dyeing Air-flow dyeing light shade Air-flow dyeing dark shade Jet dyeing Air-flow dyeing light shade Air-flow dyeing dark shade Bleaching Jet dyeing Air-flow dyeing light shade Air-flow dyeing dark shade Jet dyeing Air-flow dyeing dark shade Bleaching Jet dyeing Air-flow dyeing light shade Jet dyeing Air-flow dyeing dark shade Air-flow dyeing light shade Air-flow dyeing dark shade Jet dyeing Air-flow dyeing light shade Air-flow dyeing dark shade Bleaching Jet dyeing Air-flow dyeing light shade Air-flow dyeing dark shade Jet dyeing Air-flow dyeing light shade Air-flow dyeing dark shade Bleaching Jet dyeing Air-flow dyeing light shade Air-flow dyeing dark shade Bleaching Jet dyeing Air-flow dyeing light shade Bleaching Air-flow dyeing dark shade Air-flow dyeing dark shade Jet dyeing
Yes Yes No No Yes Yes Yes No No Yes Yes Yes Yes No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No No No No No No No Yes
Yes No Yes Yes Yes Yes Yes No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes No No No No No No No Yes Yes Yes Yes Yes Yes Yes No No No No No No No Yes Yes Yes No Yes No Yes
Yes No Yes No No No No No Yes No No No No Yes Yes Yes No No No No No No Yes Yes Yes Yes No No No Yes Yes Yes Yes Yes Yes Yes No No No Yes Yes Yes Yes Yes Yes Yes No Yes Yes No
Yes Yes Yes Yes Yes Yes Yes Yes Yes No No No No Yes Yes Yes No No No No Yes Yes No No No No Yes Yes Yes Yes Yes Yes No No No No No No No No No No No No No No No No Yes No (continued)
No.
Bleaching or dyeing
Bio-polishing
Softening
Emerizing
Calendering
51 52 53 54 55 56 57 58 59 60 61 62 63 64
Air-flow dyeing Air-flow dyeing Jet dyeing Jet dyeing Jet dyeing Air-flow dyeing Bleaching Air-flow dyeing Air-flow dyeing Air-flow dyeing Air-flow dyeing Air-flow dyeing Air-flow dyeing Bleaching
Yes Yes No Yes No No Yes Yes No No Yes No Yes Yes
Yes Yes No No No No Yes Yes Yes No No No No No
No No Yes Yes No No No No No No Yes Yes Yes Yes
No No Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes
light shade dark shade
light shade dark light dark dark light light
shade shade shade shade shade shade
(2) Enzymatic bio-polishing. This treatment is carried out for the purpose of preventing from the producing of pill caused by the friction on the surface of woven and knitted fabric. (3) Softening. This finish aim is to confer to fabrics a softer feeling. (4) Emerizing. It consists in draining the tensioned fabric with emery paper covered rollers. (5) Calendering. It consists in treating fabrics with pressurized rollers. 2.2 Evaluation of surface and compression properties The KES-F (Kawabata evaluation system for fabrics) was developed in the 1970s in Japan by Kawabata (1975, 1980, 1982). This instrument measures various mechanical (compression, tensile, shear, and bending) and surface properties of fabrics using small deformations that imitate the effect of fingers, or the entire hand, while touching and crumpling the fabrics. In the present study, eight properties were measured under standard conditions, including compression, thickness and surface properties of the knitted fabrics. The measured mechanical parameters using KES-F instruments are shown in Table II. In the case of knitted fabrics, anisotropy has to be taken into consideration. Hence, each surface parameter P has two values, representing the wale and course directions of the fabric, noted, respectively, P-W and P-C. Different tests were performed in textile standard conditions (20 ^ 28C and 65 ^ 5 percent RH). The samples, 20 cm £ 20 cm, were relaxed and preconditioned 24 hours prior to testing. 2.3 Artificial neural network Different ANN structures and learning algorithms are available in the literature. Among these structures, multilayer perceptron has been successfully applied (Haykin, 1999). A typical multi-layer neural network is shown in Figure 1. Each neuron receives a signal from the neurons of the previous layer and these signals are multiplied by separate synaptic weights (Wij). The weighted inputs are then
Compression and surfaces properties 297
Table I.
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summed up and passed through a transfer function, which converts the output to a fixed range of values. The output of the transfer function is then transmitted to the neurons of next layer. This process is continued and finally the output is produced at the output node. Predicted output is then compared with the desired output and an error signal is generated. The error signal is then minimised in iterative steps by adjusting the synaptic weights using a suitable training algorithm. Back-propagation algorithm developed by Rumelhart et al. (1986) is the most popular among the existing neural network algorithms. Network weights are adapted iteratively until some appropriate stopping criteria are met and the best weight vector that corresponds to the best generalization is achieved. 2.4 Fuzzy logic A fuzzy set is an extension of a classical crisp set. A fuzzy set contains elements with only partial membership ranging from 0 to 1 to define uncertainty for classes that do not have clearly defined boundaries (Zadeh, 1965; Zimmerman, 1996). If X is the universe of discourse and its elements are denoted by x, then a fuzzy set A in X is defined as a set of ordered pairs as A ¼ {x, mA(x)jx [ X} where mA(x) is the membership function of x in A. Once the fuzzy sets are chosen, a membership function for each set is created. A membership function is a typical curve that converts the input from 0 to 1, indicating the belongingness of the input to a fuzzy set. This step is known as “fuzzification”. Membership function can have various forms, such as triangle, trapezoid, sigmoid and Gaussian. The linguistic terms are then used to establish fuzzy rules. Fuzzy rules provide quantitative reasoning that relates input fuzzy sets with output fuzzy sets.
Apparatus Parameter
Table II. Fabric mechanical parameters measured on KES-F instruments for knitted fabrics
KES-FB3
Compression and thickness
KES-FB4
Surface
Parameter symbol LC WC RC T0 TM MIU MMD SMD
Inputs
Hidden layer
Description
Unit
Linearity of pressure-thickness curve Compressional energy Compressional resilience Thickness at 50 Pa Thickness at 5,000 Pa Coefficient of friction Mean deviation of MIU, frictional roughness Geometrical roughness
– gf cm/cm2 % mm mm –
Outputs
x1
X1...Xp: input of the network yj
xi
Figure 1. A multilayer ANN
y
Y : output of the network ϕ : transfer function
xN
wji
≡ Σ
ϕ
– mm
A fuzzy rule base consists of a number of fuzzy if-then rules. For example, in the case of two inputs and single output fuzzy system, it could be expressed as follows: If x is Ai and y is Bi then z is Ci where x, y and z are variables representing two inputs and one output; Ai, Bi and Ci, the linguistic values of x, y and z, respectively. The output of each rule is also a fuzzy set. Output fuzzy sets are then aggregated into a single fuzzy set. This step is known as “aggregation”. Finally, the resulting set is resolved to a single output number by “defuzzification”.
Compression and surfaces properties 299
3. Results and discussion 3.1 Instrumental mechanical properties In order to represent the finishing treatments effect on instrumental mechanical properties, the PCA has been applied. This statistical technique offers a simple and reliable way to compare samples and to find the correlations between the original variables. In addition, the PCA allows the reduction of the dimension number of the representation. In this case, the first three components explain 71.7 percent of the total variance. Such a large cumulated percentage value indicates that the interpretation of the results can be restricted to these three dimensions. Figure 2 shows the attributes projection on the three-dimensional correlation circles. The first principal component, accounting for 33.6 percent of the total variance, shows a positive correlation between frictional roughness (MMD-W) and compressional resilience (RC) (Figure 2(a)). These properties are negatively correlated with compressional energy (EC) and thickness at 5,000 Pa (TM). The second principal component, describing 23.3 percent of the total variance, reveals that the friction coefficients (MIU-R and MIU-C) are negatively correlated with geometrical roughness (SMD-C and SMD-W). Concerning the third principal component, representing 14.8 percent of the total variance, it shows a positive correlation between 3rd axis 14.81% SMD C SMD W
MIU W MIU C
F1011 F1110
F1110
F0110 R1010 B1010
B0001
MMD C
R1001 R0001 J1011 F1001 4/8 E B1011 4/8 D J0011 B1110 F1111F0000 J1000 R1111 J1001 R1011 J1010 F0011 R0100 F0100 F1010 J0000 J0110 F0111 B0100 B1001 R1000 J1111 B0011B1101 B1100 J0111 B1111 F0101 F1101 F0010F1100 J1100 R1101 R0110 F1000 R0000 J1101 B1000 AB/2 R0101 B0110 J0101 R0011 JB/2 J0010 R0111 R0010 B0010 B0000 J0100 B0111 B0101 R1010
R1100
J0001
MMD W
2nd axis 23.3%
F0001
Notes: (a) On the first and second axis; (b) on the second and third axis
Figure 2. PCA: product map for all the produced fabrics
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the friction coefficients (MIU-R and MIU-C) and between geometrical roughness (SMD-C and SMD-W) (Figure 2(b)). The obtained product maps (Figure 2) show that, comparing the effects of dyeing and bleaching on the sensory properties of the four fabrics, the same attribute had not the same tendency and can present two different variation tendencies with different ratio. Therefore, a statistic variation tendency analysis seems necessary. For this reason, the variation intensity and precision are calculated, according to the method developed by Sahnoun. First, the variation rate is calculated as follow (equation (1)): C Ti ¼
P O2 2 P O1 P O1
ð1Þ
where P01 and P02 are the attribute values of the fabrics Fi1 and Fi2, respectively. These fabrics have one finishing treatment T which varies from T1 to T2. The sum of positive coefficients CTþ and negative coefficients CT2 can be calculated. The global sum CTtot is determined as (equation (2)): C Ttot ¼ C Tþ þ C T2 ð2Þ The variation intensity is defined as (equation (3)): C Ttot I¼ n
ð3Þ
With n: number of fabrics couples having only one varying finishing treatment T. In the same way, the variation precision ICP is defined as (equation (4)): Max C Tþ ; jC T2 j IC T ¼ ð4Þ C Ttot It can be considered that if the values of variation intensity and precision are lower than, respectively, 0.1 and 0.7, the tendency is not confirmed. Dyeing and bleaching effects. The variation intensity and precision are used first in order to detect the effect of dyeing and bleaching processes on the compression and surface properties of studied fabrics. We note: . B-J, B-F and B-R the attributes variations comparing bleaching with dyeing in jet machine, in air-flow machine with light shade and in air-flow machine with dark shade, respectively. . R-J the attributes variations comparing dyeing in air-flow with that in jet machine. . R-F the attributes variations comparing dyeing in air-flow machine in light shade with that in dark shade. From these results (Table III), other structure parameters and finishing treatments being equal, we can assume that bleaching confers to fabrics more important the frictional roughness (MMD-W) and lower values of compression properties LC and EC compared with those of fabrics dyed in air-flow machine in the dark shade. It is also noted that fabrics dyed in air-flow machine are characterized by a more important frictional roughness (MMD-W) and lower compression linearity LC than those of fabrics dyed in jet machine although the air-flow permits a soft circulation
B2F MIU-C MMD-C SMD-C MIU-W MMD-W SMD-W LC EC T0 TM RC
B2J I IC
I
IC
0.0 0.0 0.0 0.0 2 0.3 0.0 0.1 0.3 0.1 0.1 0.0
1.0 2 1.3 1.5 1.7 2 1.0 1.7 1.0 1.0 1.0 1.0 2 1.3
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
B2R
1.5 2 22.0 2 3.1 1.5 4.8 2 2.3 2 2.3 2 1.6 1.9 2 3.4 2 2.0
R2J
R2F
I
IC
I
IC
I
IC
0.0 0.0 0.0 0.0 0.2 0.0 2 0.1 2 0.1 0.0 0.0 0.0
1.6 2 20.3 2 3.0 5.7 1.1 2.0 2 1.1 2 1.1 1.3 2 1.1 2 57.2
0.0 0.0 0.0 0.0 20.1 0.0 0.1 0.0 0.0 0.0 0.0
3.5 14.7 2.3 1.4 21.0 21.6 1.5 1.9 21.8 1.3 24.2
0.0 0.0 0.1 0.0 2 0.4 0.0 0.3 0.3 0.0 0.1 0.0
1.2 2 1.7 1.3 1.8 2 1.0 4.7 1.0 1.0 1.0 1.0 2 1.8
Compression and surfaces properties 301 Table III. The variation intensity and precision of dyeing and bleaching effects
of fabrics. The dyeing shade has also a significant effect on the compression and surface properties. Dyeing in the dark shade gives to fabrics a lower frictional roughness (MMD-W) and more important compression linearity LC, geometrical roughness (SMD-C) and thickness at 5,000 Pa TM than those of fabrics dyed in light shade. Finishing effects. The aim of this second part is to study the effect of different finishes, namely bio-polishing, softening, emerizing and calendering, on the compression and surface properties of studied fabrics. Fabrics treated by bio-polishing have the least thickness at 50 and thickness at 5,000 Pa (T0 and TM) (Table IV). This result was expected since the bio-polishing treatment consists in treating the cellulosic fibers by cellulases in order to eliminate hairs. Bio-polishing decreases the compression energy (EC) and linearity (LC). In fact, the bio-polishing eliminate pills, and so, compression phase of pills. Assuming that all other structure parameters and finishing processes are identical, the softening treatment procures to studied fabrics more important compression resilience (RC). Softeners confer to fabrics a softer feeling and improve many mechanical properties such as the elasticity and suppleness, and consequently the compression resilience. It can be noticed also that softeners increase frictional roughness (MMD-W) and geometrical roughness (SMD-W). Bio-polishing I IC MIU-C MMD-C SMD-C MIU-W MMD-W SMD-W LC EC T0 TM RC
0.0 0.0 0.0 0.0 0.3 0.0 2 0.1 2 0.2 20.1 20.1 0.1
1.1 21.7 23.9 1.3 1.0 21.7 21.1 21.0 21.4 21.1 1.4
I
Softening IC
0.0 0.0 0.0 0.0 0.1 20.1 0.0 0.0 0.0 0.0 0.1
2 3.5 2 1.4 2 10.0 3.6 1.6 2 1.3 2 1.7 2 6.8 1.9 2 1.0 1.2
Emerizing I
IC
0.1 2 0.1 2 0.1 0.1 0.0 2 0.1 0.0 0.1 0.1 0.0 2 0.0
1.3 21.1 21.2 1.2 2.1 21.5 3.3 1.1 1.3 1.2 21.7
Calendering I IC 0.0 0.0 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0
2 2.0 2 1.4 1.3 2 4.1 2.2 1.4 2 6.4 5.5 2 32.9 2 1.4 2 2.9
Table IV. The variation intensity and precision of finishing effects
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As emerizing gives to fabrics little, dense and regular hairs, this treatment increases the thickness at 50 Pa T0 and the compression energy (EC). Emerizing decreases the geometrical roughness (SMD-C) and increases the coefficient of friction (MIU). In fact, hairs caused by this treatment make stitch wale reliefs less apparent and the sensor slide movement over the fabric surface easier. Calendering provides to the studied fabrics, a more important geometrical roughness (SMD), although it flats fabrics hairs. This effect can be explained by the fact that this finish presents any permanence, and it has to be combined with other chemical finishes. 3.2 Input space reduction In this investigation, five finishing treatments, namely bleaching or dyeing, bio-polishing, softening, emerizing and calendering were taken as input data in the prediction models. The 11 compression and surface properties were used as output data. In order to reduce the number of input variables, the PCA was applied (Fukunaga, 1990). The PCA performs a linear transformation of an input variable vector for representing all original data in a lower dimensional space with minimal information lost. In this case, the two first components (Table V), representing the original variable vector in the direction of its two first largest eigenvectors of the variable covariance matrix, are taken as input data. 3.3 Optimisation of parameters of neural and fuzzy models Neural network models. Building an appropriate network structure and optimizing the learning parameters influence largely the prediction performance of ANN model. The important structural parameters to be determined are the number of hidden layers and the number of neurons in each hidden layer. These parameters depend on the complexity of the function or the modelled process. Only one hidden layer was used in this investigation, as it is sufficient for any degree of accuracy (Ertugrul and Ucar, 2000). Consequently, only the number of hidden neurons becomes critical. In this case, the optimal hidden neurons number was optimised by trial and error method. The network was trained using different number of neurons in the hidden layer from one to ten sequentially. It was found that seven hidden neurons provided the best prediction performance in terms of root mean square error (RMSE). Moreover, when the network is too much trained, it memorizes the training set and does not generalize well. The training holds a key to an accurate solution, hence the criterion to stop training must be very well described. The cross-validating stopping rule is used for ending training in this research. When the error in the cross-validation increased, the training was stopped because the point of best generalization was reached. The data set was divided into training, cross-validation and test sets at random. From the 64 samples, we used 52 (81 percent) samples as training set, six samples (9 percent) as cross-validation set and six samples (9 percent) for testing the prediction performance of model. The data were scaled to fall between 2 1 and þ 1. The log sigmoid and the linear transfer functions were used as activation function for the hidden neurons and the output neuron, respectively. Fuzzy logic models. In this investigation, a fuzzy variable for each compression and surface characteristic were constructed. The input data of fuzzy systems are two first
no. X1 X2 no. X1 X2 no. X1 X2 no. X1 X2
1 1.92 2 0.61 17 2 0.73 0.66 33 1.85 2 2.13 49 2 3.82 2 0.90
2 2.09 1.15 18 21.21 0.38 34 2.16 22.81 50 3.63 0.78
3 21.77 0.12 19 20.35 1.04 35 3.09 22.36 51 3.10 3.66
4 2 0.76 1.65 20 2 2.17 1.22 36 2 1.53 2 3.09 52 2 1.23 2 0.37
5 4.14 0.40 21 20.73 2.12 37 20.71 0.35 53 22.06 21.76
6 3.69 0.41 22 2 1.70 1.15 38 2 0.42 1.29 54 1.35 2 0.94
7 3.37 0.26 23 1.23 21.50 39 21.52 0.43 55 21.88 3.51
8 22.59 4.98 24 1.59 21.78 40 21.40 20.66 56 20.95 2.65
9 2 2.73 2 0.22 25 1.75 2 1.72 41 2 1.10 0.15 57 2.55 1.09
10 1.86 2.42 26 22.78 22.35 42 20.38 20.42 58 20.66 20.69
11 2.66 0.65 27 2.99 1.23 43 2 2.96 2 0.89 59 0.07 1.04
12 3.47 1.17 28 3.49 1.63 44 20.87 20.86 60 22.96 3.57
13 21.97 0.25 29 20.85 20.22 45 21.50 20.68 61 22.57 21.85
14 2 0.67 2 1.01 30 2.05 2 2.08 46 0.15 2 1.77 62 2 1.49 2 0.73
15 20.45 20.79 31 2.43 22.43 47 21.16 1.58 63 1.29 21.06
16 2 2.36 2 0.50 32 2 2.06 2 1.51 48 2 2.87 2 1.91 64 1.97 2 0.35
Compression and surfaces properties 303
Table V. Reduced input data
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PCA components (Table IV). These values are converted to three fuzzy subsets: small (S), medium (M) and big (B). The trapezoidal membership functions are adapted (Figure 3). In fuzzy inference, the Mamdani method was used for calculating the output inferred by a set of m fuzzy rules (Mamdani and Assilian, 1975). Mamdani fuzzy inference method is the most commonly applied fuzzy methodology. Under the Mamdani method, there is a fuzzy set for each output variable that needs defuzzification. Each output variable is partitioned into five fuzzy subsets: very small (VS), small (S), medium (M), big (B) and very big (VB) (Figure 3). The fuzzy rules are extracted from the fabric samples of a learning base. The rules extraction is adjusted for each attribute in order to take into account different situations. The centroid method is used for defuzzification. The fuzzy systems evaluation is first generated relating to the learning data. Hence, we can effectively resolve the conflicts between different rules and then decrease the information lost by selecting only the most influential rules. Then, the all input/output data are used for validating the effectiveness of the model. For example, the obtained rules of the geometrical roughness SMD-C model are shown in Figure 4. It is observed that for inputs variables equal to 2 3.2 and 2 1.3, respectively, two rules (rules 4 and 6) are active and the corresponding output data is equal to 1.36. Membership function plots 1
Small
Membership function plots
Medium
Big
1
0.5
Figure 3. Membership functions of input and output variables
0 –1
VerySmall
Big
VeryBig
0 –0.8 –0.6 –0.4 –0.2
X1 = –3.2
0
0.2
0.4
0.6
0.8
1
0
1
2
X2 = –1.3
SMD-C = 1.36
2 3 4 5 6 7 8 9 10 11 4.2 –3.8
3
4
5
6
7
8
9
10
Output variable
1
–3.8
Medium
0.5
Input variable
Figure 4. Fuzzy model rules of SMD-C
Small
4.2 1.1
2.3
1. If (X1 is Big) and (X2 is Small) then (attribute is VerySmall) 2. If (X1 is Medium) and (X2 is Small) then (attribute is VerySmall) 3. If (X1 is Big) and (X2 is Big) then (attribute is VerySmall) 4. If (X1 is Small) and (X2 is Small) then (attribute is VerySmall) 5. If (X1 is Big) and (X2 is Medium) then (attribute is VerySmall) 6. If (X1 is Small) and (X2 is Medium) then (attribute is Small) 7. If (X1 is Medium) and (X2 is Medium) then (attribute is Medium) 8. If (X1 is Medium) and (X2 is Big) then (attribute is Medium) 9. If (X1 is Medium) and (X2 is Small) then (attribute is Medium) 10. If (X1 is Medium) and (X2 is Big) then (attribute is Big) 11. If (X1 is Big) and (X2 is Big) then (attribute is VeryBig)
3.4 Prediction performances of neural and fuzzy models The prediction performances of neural and fuzzy models were evaluated according to two statistical criteria, namely the RMSE and mean relative percent error (MRPE): vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u N u1 X RMSE ¼ t e2 ð5Þ N 1 N 1 X ðT 2 Y Þ £ 100 MRPE ¼ £ N 1 T
Compression and surfaces properties 305
ð6Þ
where N: data number, e: prediction error e ¼ Y 2 T, where T: the real attribute score and Y: the estimated attribute score. In order to assess the robustness of neural models, the prediction performance in unknown points (test set) has been evaluated to check if models are able to correctly predict points not involved during model generation. The statistical performance criteria values, namely RMSE and MRPE, in training, validation and test sets are shown in Table VI. Table VI shows that the neural models have similar prediction performances in training, validation and test sets. These results confirm the robustness of the developed models. The mean statistical performance criteria values of neural and fuzzy models as well as the standard deviation are shown in Table VII. Table VII reveals that the neural and fuzzy models have a good performance in predicting the surface and compression properties of the knitted fabrics from the finishing treatments. In fact, it is observed that, excepting the frictional roughness MMD-W, linearity of pressure-thickness curve LC and compressional energy WC predicted with ANN, all others properties have an acceptable MRPE values (, 10 percent). In addition, the obtained RMSE values are lower than the mean variations of experimental values expressed by standard deviation values, except the frictional roughness MMD-W and compressional energy WC predicted with ANN. Moreover, the prediction performances of neural and fuzzy models are compared according to the RMSE (Figure 5). This comparison revealed that the fuzzy models
MIU-C MMD-C SMD-C MIU-W MMD-W SMD-W LC EC T0 TM RC
MRPE-train
MRPE-valid
MRPE-test
RMSE-train
RMSE-valid
RMSE-test
2.70 5.85 8.06 2.55 20.02 9.03 16.69 19.95 4.09 2.68 3.97
1.80 6.49 6.85 1.57 17.58 7.74 10.73 11.59 5.50 2.31 4.51
3.29 5.70 11.09 6.64 16.90 6.76 25.53 21.95 6.57 2.87 13.23
0.08 0.10 0.16 0.07 0.50 0.18 0.06 0.07 0.06 0.02 1.80
0.05 0.11 0.10 0.04 0.46 0.13 0.04 0.04 0.07 0.02 1.89
0.10 0.11 0.17 0.17 0.49 0.13 0.08 0.07 0.08 0.03 5.40
Table VI. Prediction results of neural models in training, validation and test sets
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306 Table VII. Summary of prediction results of neural and fuzzy models
Neural models RMSE MRPE MIU-C MMD-C SMD-C MIU-W MMD-W SMD-W LC EC T0 TM RC
0.08 0.10 0.15 0.08 0.49 0.17 0.06 0.06 0.06 0.02 2.39
2.67 5.89 8.23 2.84 19.49 8.69 16.96 19.36 4.45 2.67 4.89
Fuzzy models RMSE MRPE 0.07 0.11 0.12 0.07 0.30 0.09 0.03 0.03 0.06 0.01 2.71
SD
2.47 5.97 6.15 2.44 11.40 4.53 8.58 8.09 4.30 1.72 5.78
0.28 0.29 0.19 0.28 0.39 0.19 0.07 0.04 0.09 0.01 2.75
Comparison of fuzzy and neural prediction performance
Standard deviation and RMSE
3
Figure 5. Comparison of fuzzy and neural prediction performance
Standard deviation RMSE-Neural RMSE-Fuzzy 2
1
0 MIU-C MMD-C SMD-C MIU-W MMD-W SMD-W
LC
WC
T0
TM
RC
Fabric mechanical parameters measured on KES-F
are slightly powerful than the neural models. The RMSE criterion is lower for fuzzy models compared to those for neural models for all properties excepting the compression resilience (RC) case. 4. Conclusion This study provided contribution in industrial products engineering, with minimal number of experiments and short cycles of product design. In fact, models based on intelligent techniques, namely FIS and ANNs, were developed for predicting instrumental tactile characteristics in reference to finishing treatments. The performances of the proposed models were evaluated by means of statistical criteria, namely the RMSE and MRPE. The obtained results have revealed that the successful ability of neural and fuzzy models to predict the compression and surface properties of knitted fabrics from the finishing process. In fact, the MRPE values
were acceptable (, 10 percent) and the RMSE values were lower than the mean variations of experimental values. The comparison of prediction performances of neural and fuzzy models displayed that fuzzy models are slightly better than neural models. In addition, the major drawback of neural model is that it acts like a “black box” without revealing any physical information about the mechanics of the process.
Compression and surfaces properties 307
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[email protected]
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Compression and surfaces properties 309
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A small deflection model for yarn bending in a plain weave fabric Mohammad Ghane, Iman Azimpour and Seyed A. Hosseini Ravandi
310
Department of Textile Engineering, Isfahan University of Technology, Isfahan, Iran
Received 10 August 2010 Accepted 14 April 2011
Abstract Purpose – The purpose of this paper is to establish a simple and practical elastica model for the deflection of weft (warp) in a plain wave fabric. Design/methodology/approach – The weft yarn is considered as an elastic beam fixed supported at the ends and deflected in the middle by a vertical load. An analytical model, based on the elastic theory and small deflection case is adopted to study the factors affecting the deflection of the yarn. To investigate the model, yarns with different rigidities are used. A total of five different yarn counts are produced in the same ring spinning system and then used as weft yarn in a plain weave fabric. All other parameters of the yarns and the fabrics are kept identical. Fresh fabrics are analyzed and the maximum deflection of the weft is measured using the microscope. The actual curves of the deflected weft are then compared with the theoretical curves. Findings – The experimental curves show to agree well with the theoretical model. The results also show that as yarn linear density decreases, the deflection increases. Originality/value – The paper shows that while the large deformation “elastica” theory is typically used for woven fabric modeling, the small deflection theory can be useful for rapid computation. Keywords Weft deflection, Elastic beam, Fixed-fixed beam, Small deflection, Fabric testing, Yarn testing Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 5, 2011 pp. 310-320 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111166248
1. Introduction A major source of attention for many researchers has been thread deflection shape and geometry because it affects many of the fabrics’ different characteristics. For instance, surface properties of the fabric such as yarn protrusion, friction, touch, etc. are affected by thread deflection in the fabric. Visual properties of the fabric surface such as light reflection and luster are also affected by thread bending. More importantly, mechanical performance of the fabric depends to a large extent on the geometry and shape of thread deflection in the fabric. An early attempt in modeling thread deformation was made by Pierce (1937), who assumed a plain geometry for the deformation of threads in a plain weave fabric, neglecting yarn rigidity. This model was widely accepted and used. Kawabata proposed a three-dimensional model based on the assumption that weft and warp axes were on straight lines (Kawabata et al., 1973). A saw tooth model was also proposed by Leaf and Kandil (1980), which yielded acceptable experimental results. A number of studies were devoted to the analysis of the different factors affecting weft deflection in the fabric structure (Hosseini Ravandi and Ghane, 2000; Hosseini Ravandi and Ghane, 2004). The model used in these studies was based on a fixed-fixed The authors would like to express their sincere thanks and gratitude to the Deputy for Research of Isfahan University of Technology for financial support.
beam deflected in the middle by a vertical load. Influence of normal load, thread spacing, and yarn bending rigidity were studied on yarn protrusion from the fabric surface. It was shown that yarn bending rigidity and thread spacing had significant effects on the protrusion of the yarn from the fabric surface. The authors also reported an acceptable agreement between predicted and experimental results. The bending behavior of woven structure and yarns has also been investigated by different authors (Lomove et al., 2000; Sagar and Potluri, 2004; Weidong and Zhaoqun, 2006). The main objective of the present work is to describe a useful and practical model for the deflection of yarns in a plain fabric structure. A fixed-fixed beam deflected by a concentrated load in the middle and the case of small deflection equations are adapted to model the deflection of the weft in a plain weave fabric. While, the large deformation “elastica” theory is typically used for woven fabric modeling, the small deflection theory can be useful for rapid computation.
Yarn bending in a plain weave fabric 311
2. Theory 2.1 Small deflection equation A method to obtain the small deflection equation is to use the geometry of the bent beam as shown in Figure 1. Consider an element with the length of dL along the beam. It can be shown that: du ¼
dL 1 du Or ¼ r r dL
ð1Þ
And the slope of the tangent to the curve is: tan u ¼
dy dx
ð2Þ
where, r is the radius of the curvature and u is the angle between the tangent to the curve and the x-axis. If the deflection is very small relative to the length of the beam, the angle u will be very small and, thus, tanu < u and dL < dx and the deflection will be carried to the small deflection case. Substituting these approximations in equations (1) and (2), we will have:
r dq
+x q
dL dx
dy
+y
Figure 1. Geometry of a bent curve
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1 du dðtan uÞ dðdy=dxÞ d 2 y ¼ ¼ ¼ ¼ 2 r dL dL dx dx
ð3Þ
This is the small deflection equation for a bent beam. Consider an elastic beam bent by the applied moment (M). Using classical theories of elasticity, it can be shown that the curvature of the neutral line (1/r) is (Timoshenko and Young, 1969; Nash, 1998): 1 M ðxÞ M ðxÞ ¼ ¼ r EI B
ð4Þ
And, from equations (3) and (4), the governing differential equation in the case of small deflection will be: 1 d 2 y M ðxÞ M ðxÞ ¼ ¼ ¼ EI B r dx 2
ð5Þ
2.2 Fixed-fixed beam modeling The beam principles have been used widely to study the bending behavior of textile fabrics (Pierce, 1930; Matsuo, 1969; Szablewski and Kobza, 2003; Kocik et al., 2005). The shape and curve of a bent filament yarn have been studied and the bending rigidity of the yarn calculated using a fixed supported beam model (Ghane et al., 2008). In this work, the weft is considered as an elastic beam supported at the ends and deflected in the middle by a vertical load. This mechanical model is adopted for a weft in a fresh (unset) plain weave fabric where the weft is clamped by the friction force at the intersects and deflected by a normal load inserted by the warp. A schematic diagram of a wave of the bent weft in a plain weave fabric is shown in Figure 2(a). The consecutive warps A, B, and C are marked by circles. As the tangent to the curve of the deflected weft is equal to zero at points A and C, the deflected weft is assumed to be fixed supported by the adjacent warps (warps A and C in Figure 2(a)). The distance between the supports is very small (two times the warp spacing) so that the weft can be considered to behave as an elastic beam. The vertical load is applied by the warp B in the middle of warps A and C (Figure 2(a)). The same model can be considered for the bending of warps deflected by a vertical load applied by wefts. The assumptions made here in order to model the deflection of the weft are: . the cross-section of the yarns is assumed to be circular; . the yarns are incompressible and behave in a perfectly elastic manner during bending; . the case of small deflection equations is applied to the model; and . the vertical load is concentrated on a point in the middle of the deflected yarns. Figure 2(b) shows a free diagram of the central line of the weft modeled as a fixed-fixed beam deflected in the middle by a concentrated load, pin the middle. The maximum moment at the ends and in the middle of the beam is equal to PL/8. The reaction force at supports is equal to P/2. The governing differential equation of the beam can be solved using the double integration method and boundary conditions.
Yarn bending in a plain weave fabric
P
313
B x
A
C
L L/2 y (a)
P
M = PL/8
M = PL/8
x P/2
M = P/2
Y
L L/2
Figure 2. Bending deflection and free diagram of the mechanical model
y (b)
Notes: (a) Fixed fixed bent beam (weft); (b) free diagram of the central line
Consider the center of the coordinate at the left support. The variable moment at any given point, at a distance x with 0 # x # L/2, is: M ðxÞ ¼
PL Px 2 8 2
Applying the value of M(x) in equation (5), we have: d 2y P L x 2 0 # x # L=2 ¼ dx 2 B 8 2
ð6Þ
ð7Þ
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Integration from both sides of the above equation gives: Z Z 2 d y P L x 2 0 # x # L=2 ¼ dx 2 B 8 2
ð8Þ
And then:
314
dy P ¼ dx B
Lx x 2 2 4 8
þ C1
0 # x # L=2
ð9Þ
Applying the boundary condition at x ¼ 0, dy/dx ¼ 0 so C1 ¼ 0. Again integration from both sides of equation (9) gives: Z Z dy P Lx x 2 0 # x # L=2 ð10Þ ¼ 2 4 dx B 8 And then: y¼
P B
2 Lx x3 2 þ C2 16 12
0 # x # L=2
ð11Þ
Applying the boundary conditions at x ¼ 0, y ¼ 0 so C2 ¼ 0 and we have: y¼
Px 2 ð3L 2 4xÞ 48B
0 # x # L=2
ð12Þ
Applying the same procedure for L/2 # x # L and using two boundary conditions at x ¼ L, dy/dx ¼ 0 and at x ¼ L, y ¼ 0, it can be shown that: y¼
PðL 2 xÞ2 ð4x 2 LÞ 48B
L=2 # x # L
ð13Þ
Appling the model to a bent yarn in a plain weave fabric, the maximum deflection in the middle of the bent yarn in the case of small deflection is: Y¼
PL 3 PL 3 ¼ 192EI 192B
ð14Þ
where: Y, maximum deflection in the middle of the beam (weft). P, vertical load (loaded by warp yarn). L, distance between supports (distance between two adjacent warps). E, elastic modulus of the weft yarn. I, moment of inertia of the cross-section of the weft yarn. Rearranging equation (14) gives: P 192Y ¼ B L3
ð15Þ
The above equation shows that the ratio of P/B can be calculated from the geometric parameters of the fabric, i.e. thread spacing and yarn deflection. If the rigidity of the yarn is available, the normal load P can then be estimated. 3. Experimental 3.1 Sample preparation In order to study, the effect of weft yarn diameter on yarn protrusion, five different yarn counts were spun. The yarns were produced on a short staple carded cotton spinning system and a ring spinning machine was used. The constituent fibers were 100 percent cotton. The English twist factor of the yarns was set to 3.50 and identical for all yarn types. All the parameters of the yarn production line were also identical. The English Cotton Count of the yarn types were; 11.2, 15, 19.2, 23.2, and 26.5 Ne. In this way, the only independent variable was linear density, and different yarn diameters yielded different yarn rigidities. The produced yarns were then used as the weft in a weaving machine to prepare plain fabrics. The warp yarns were the same for all fabric types and were cotton-polyester with an English Cotton Count of 20/1 Ne. The percentages of polyester and cotton in the yarn were 65 and 35 percent, respectively. The warp and weft thread densities were also 24 and 22 ends/cm, respectively. Grossberg’s suggestion (Hearle et al., 1969) was used to estimate the diameter of the yarn as follows: sffiffiffiffiffiffi Ty d ¼ 4:44 ð16Þ £ 1023 r In which, d is yarn diameter (cm), Ty is the linear density of the yarn (Tex), and r is the density of the fibers (g/cm3). 3.2 Measurement of weft deflection Cross-sectional images of the fabrics were required for measuring maximum deflection of the weft yarn. Using a special mold, grey fabrics were impregnated in an epoxy resin, sk20 with a ratio of 1:2. The set was then left to be cured for 24 hours. The resin was able to penetrate deeply into the fabric spaces to make a solid structure after curing. This is necessary both to prevent the threads from sliding aside during the cutting process and to make microscopic observations of the samples possible. The sample was then removed from the mold and placed in a microtome cutter machine SLEE-4055. The warps and wefts were located along the horizontal and vertical directions, respectively. In order for the weft wave to be clearly observed, cutting was carried out in the weft direction and the surface of the molded sample was polished. The microtome was adjusted to obtain cuttings 25 microns thick from the layers of the molded sample. The cuttings were then observed under a MOTIC microscope (B3 with a magnification of £ 100) which was equipped with a closed circuit camera connected to a computer. A special software, MOTIC IMAGE 1.2, on the computer allowed any real distance on the object to be calculated from the images by defining the magnification of the microscope ( £ 100) for the software. For each fabric type, ten samples were examined and the average values of the maximum deflection were calculated and reported in Table I. Figures 3-7 show typical images of the weft wave for different yarn counts.
Yarn bending in a plain weave fabric 315
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3.3 Estimation of the ratio P/B In this study, the geometric parameters of the fabrics including warp spacing (L/2) and maxim deflection (Y) are given; hence, P/B ratio can be calculated from equation (15). This value shows the force needed to deflect a beam with unit rigidity to certain geometry. The results are provided in Table I. While a vertical load is applied by the warp on the weft, an equal vertical load is also applied in the opposite direction by the weft on the warp. The same equations can be applied again for the deflection of the warp yarns. If we have the vertical load, P, the maximum deflection of the warp can be estimated from the deflection of the weft. 4. Results and discussion The values for maximum deflection of the weft were measured using the method described above (Table I). In order to confirm the validity of the small deflection equations, the shape of the actual bent weft in the fabric was compared with the theoretical curve. Using the appropriate software, the x-y coordination of some of the points were extracted from the actual curve of the outermost layer of the weft (Figures 3-7). The theoretical curve of a bent beam under conditions identical to those of the deflected weft was plotted according to equations proposed by the model (equations (12) and (13)). The value of P/B needed for the plot was calculated according equation (15) using the value for maximum deflection of the weft in the fabric (Y) and warp spacing (L/2). Yarn count (Ne)
Table I. Some specifications of the fixed-fixed bent beam
Figure 3. Weft yarn curve (11.2 Ne)
Figure 4. Weft yarn curve (15 Ne)
11.2 15 19.2 23.2 26.5
Diameter d (mm)
Maximum deflection Y (mm)
P/B (mm2 2)
0.261 0.226 0.200 0.182 0.170
0.272 0.331 0.394 0.418 0.442
90.24 109.82 130.72 138.68 146.65
The calculations were carried out for all yarn types. Typical plots of the actual curves and the theoretical curves of a bent weft for different yarn counts are shown in Figures 8-12. Comparison of the actual curves with the theoretical ones reveals that the deviation of the theoretical and the actual curves increases slightly as the diameter of the weft
Yarn bending in a plain weave fabric 317
Figure 5. Weft yarn curve (19.2 Ne)
Figure 6. Weft yarn curve (23.2 Ne)
Weft Yarn Deflection (µm)
Figure 7. Weft yarn curve (26.5 Ne)
500 450 400 350 300 250 200 150 100 50 0
Theoretical Actual
0
200
400
600 L (µm)
800
1,000
Figure 8. Plots of theoretical and actual curves of the bent weft (Ne ¼ 11.2)
Figure 10. Plots of theoretical and actual curves of the bent weft (Ne ¼ 19.2)
Figure 11. Plots of theoretical and actual curves of the bent weft (Ne ¼ 23.2)
Weft Yarn Deflection (µm)
Figure 9. Plots of theoretical and actual curves of the bent weft (Ne ¼ 15)
500 450 400 350 300 250 200 150 100 50 0
Theoretical Actual
0
200
400
600
800
1,000
600
800
1,000
600
800
1,000
L (µm)
Weft Yarn Deflection (µm)
318
500 450 400 350 300 250 200 150 100 50 0
Theoretical Actual
0
200
400 L (µm)
Weft Yarn Deflection (µm)
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500 450 400 350 300 250 200 150 100 50 0
Theoretical Actual
0
200
400 L (µm)
Weft Yarn Deflection (µm)
500 450 400 350 300 250 200 150 100 50 0
Yarn bending in a plain weave fabric
Theoretical Actual
319
0
200
400 600 L (µm)
800
1,000
yarn decreases. The reason for this is that in the case of the finer weft yarn, deflection increases leading to a lower accuracy of the small deflection equations. Another point that should be considered is that the cross section of the yarn is assumed to be circular whereas in the fabric structure the cross section may deviate from the circular shape leads to less accuracy of the equations. However, the shapes of the actual bent weft are reasonably close to that of the theoretical curves. This confirms the validity of the model. It can be concluded that the small deflection equations can be adapted to predict the shape of the weft deflection in plain weave fabrics with an acceptable accuracy. The large deflection correction for the deflection of the weft will be investigated in future work. The results of this work shows that the ratio of normal load to rigidity of weft yarn (P/B) can be obtained by the model presented. The flexural rigidity of the weft is obtained then the value of the normal load P can be estimated. The flexural rigidities of some cotton yarns measured by Leaf et al. (1993). Some other methods are also described in the literature to measure the flexural rigidity of yarns (Ghane et al., 2008; Abbot and Grosberg, 1966; Du and Yu, 2005). The normal load, P, is not uniformly distributed at all intersection points in the fabric structure. One major source of variation in the normal load is the mass variation of yarns. The irregularity of the yarns causes variation in their diameter. This, in return, causes variation in rigidity and normal load and consequently may leads to variation of P/B. 5. Conclusions A theoretical model was adopted for weft deflection in a plain fabric. The model was based on a fixed-fixed beam deflected in the middle by a vertical load. The weft was considered as an elastic beam fixed supported at the ends by adjacent warps and deflected in the middle by a warp. Small deflection equations were used to estimate the ratio of normal load to rigidity of weft yarn (P/B). Maximum deflection of weft in the fabric was measured using the microscopic method. The actual and theoretical curves of a bent weft in the fabric were compared. The results showed an acceptable agreement between the actual curve and the theoretical equation. It can be concluded that the elastic equations in the small deflection case can be adopted for the deflection of weft (warp) in a plain weave fabric.
Figure 12. Plots of theoretical and actual curves of the bent weft (Ne ¼ 26.5)
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References Abbot, G.M. and Grosberg, P. (1966), “Measurement of fabric stiffness and hysteresis in bending”, Tex. Res. J., Vol. 36 No. 10, pp. 928-30. Du, Z. and Yu, W. (2005), “Analysis of bending properties of worsted wool yarns and fabrics based on quasi-three-point bending”, J. Tex. Inst., Vol. 96 No. 6, pp. 389-99. Ghane, M., Sheikhzadeh, M., Halabain, A.M. and Khabouri, S. (2008), “Bending rigidity of yarn using a two supports beam system”, FIBERS & TEXTILES IN Eastern Europe, Vol. 16 No. 3, pp. 30-2. Hearle, J.W.S., Grosberg, P. and Backer, S. (1969), Structural Mechanics of Fibers, Yarns and Fabrics, Wiley-Interscience, New York, NY, p. 332. Hosseini Ravandi, S.A. and Ghane, M. (2000), “Study of fundamental factors affecting fabric surface protrusion (part I)”, J. Tex. Inst., Vol. 91 No. 1, pp. 100-6. Hosseini Ravandi, S.A. and Ghane, M. (2004), “Study of fundamental factors affecting fabric surface protrusion (part II)”, J. Tex. Inst., Vol. 95 Nos 1-6, pp. 277-81. Kawabata, S., Niwa, M. and Kawai, H. (1973), “The finite-deformation theory of plain weave fabrics, part 1: the biaxial deformation theory”, J. Tex. Inst., Vol. 64 No. 1, pp. 21-46. Kocik, M., Zurek, W., Krucinska, I., Gersak, J. and Jakubczyk, J. (2005), “Evaluating the bending rigidity of flat textiles with the use of an instron tensile tester”, FIBERS & TEXTIELS in Eastern Europe, Vol. 13 No. 2, pp. 31-4. Leaf, G.A.V. and Kandil, K.H. (1980), “The initial load-extension behavior of plain-woven fabrics”, J. Tex. Inst., Vol. 71 No. 1, pp. 1-7. Leaf, G.A.V., Yan, C. and Chen, X. (1993), “The initial bending behavior of plain woven fabrics”, J. Tex. Inst., Vol. 84 No. 3, pp. 419-28. Lomove, S.V., Truevtzer, A.V. and Cassidy, C. (2000), “A predicting model for the fabric to yarn bending stiffness ratio of plain woven set fabric”, Textile Res. J., Vol. 70 No. 12, pp. 1088-96. Matsuo, T. (1969), “Bending of woven fabrics”, J. Tex. Mach. Soc. Japan, Vol. 15 No. 1, pp. 19-33. Nash, W.A. (1998), Schaum’s Outline of Theory and Problems of Strength of Materials, 4th ed., McGraw-Hill, New York, NY. Pierce, F.T. (1930), “The handle of cloth as a measurable quantity”, J. Tex. Inst., Vol. 21, pp. T377-T416. Pierce, F.T. (1937), “The geometry of cloth structure”, J. Tex. Inst., Vol. 28, pp. T45-T69. Sagar, T.V. and Potluri, P. (2004), “Computation of bending behavior of woven structure using optimization technique”, Textile Res. J., Vol. 74 No. 10, pp. 879-86. Szablewski, P. and Kobza, W. (2003), “Numerical analysis of Pierce’s cantilever test for the bending rigidity of textiles”, FIBERS & TEXTIELS in Eastern Europe, Vol. 11 No. 4, pp. 54-7. Timoshenko, S. and Young, D.H. (1969), Elements of Strength of Materials, 5th ed., Van Nostrand, New York, NY. Weidong, Y. and Zhaoqun, D. (2006), “Determination of the bending characteristic parameters of the bending evaluation system of fabric and yarn”, Textile Res. J., Vol. 76 No. 9, pp. 702-11. Corresponding author Mohammad Ghane can be contacted at:
[email protected]
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Estimation of safe fabric length during automatic vertical feeding of fabrics into work stations J. Amirbayat Department of Textile Engineering, Amirkabir University of Technology, Tehran, Iran
Estimation of safe fabric length 321 Received 9 August 2010 Accepted 14 November 2010
Abstract Purpose – The purpose of this paper is to provide an estimation of safe fabric length during automatic vertical feeding of fabrics into work stations. Design/methodology/approach – The analysis is based on the application of the energy method and taking advantage of dimensionless groups. Findings – Limits of the safe maximum force and length are obtained for a fabric of known properties and given friction coefficient between the fabric and supporting bed. Originality/value – The paper demonstrates how to calculate the buckling force of a horizontally positioned fabric where the weight cannot be neglected and how to calculate the maximum length of such a fabric which can be pushed into a work station without buckling. Keywords Automatic feeding, Fabric buckling, Energy analysis, Dimensionless groups, Feeding devices, Deformation Paper type Research paper
1. Introduction In certain types of textiles and clothing operations, such as sewing, some types of jet printing and so on, the fabric is pushed forward over a horizontal support intermittently and may buckle if the axial force exceeds a critical level causing operational problems. The buckling in this case is different from the ordinary instability cases for two reasons. One is the fabric weight and the other is restriction of the force from forward motion due to the fixed distance between the feeding mechanism and the operating station. The problems of classical buckling even for special cases such as columns of variable cross-sections or columns on elastic foundation can be accurately estimated by applying the energy methods by assuming a reasonable buckling shape and calculating the different energies of deformation (Den Hartog, 1987). These energies are all proportional to the square of the central deflection which will cancel out after applying the principle of conservation of energy, and the critical force can be calculated (Timoshenko and Gere 1961). In the case of horizontal buckling of fabrics, the distributed weight has a constant value independent of the location along the length and as a result, the energy for lifting the weight contains the first power of the central deflection which cannot be cancelled out and therefore a different method should be applied. Except for some studies by Clapp and Peng (1990) in buckling of heavy fabrics, the only notable work on horizontal buckling, to the author’s knowledge, is the empirical work by Gershon and Grosberg (1992) who adapted the experimental results supplied by the late professor Lindberg and estimated the maximum length of the fabric to be pushed forward during feeding into sewing station without buckling.
International Journal of Clothing Science and Technology Vol. 23 No. 5, 2011 pp. 321-328 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111166257
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The study although original, contains an arbitrary assumption for the maximum slope of the buckling curve, which is a matter of discussion. Assuming a larger angle results in smaller critical load and smaller angles give higher values. In fact for zero slope, i.e. the beginning of buckling, the critical load becomes infinite as mentioned by the authors. The present study includes in-plane (membrane) strain energy of the fabric which converts to different energies after the instability. This helps to work out the central deflection and a suitable buckling shape from which the energies can be calculated[1]. It is also assumed that the fabric is Newtonian and the bending stiffness is independent of the membrane modulus. After formulating the energies, at first the buckling force for a fabric of given properties fixed at one end and pushed through a slot at a distance, from the fixed end is calculated. After this stage, the critical length of a fabric for which the friction force buckles it, is worked out. The latter is a new approach in-line with the previously mentioned empirical work. 2. Geometrical considerations With regard to the shape of the buckled fabric which is similar to a column with both ends built-in, the following sine curve is considered for the buckling shape, Figure (1): pX y ¼ y0 sin2 : ð1Þ l The central deflection is unknown and will be determined from the geometry. The length of the buckled curve in excess to that of the span is: Z l Z 1 d¼ ds 2 l ¼ ð1 þ y 2 Þ1=2 dx 2 l: n
0
Approximation for small slope:
1 þ y2
1=2
1 < 1 þ y2 2
and integration gives:
d¼
p2 2 y: 4l 0
ð2Þ
q Feeder Operation Station
+ F
+
Figure 1. Buckled fabric (Fixed distance)
The compressive deformation of the fabric before instability is:
d1 ¼ J 0 l
ð3Þ
where J0 is the force normalized with respect to the membrane modulus, Y. Since the force does not follow its line of action and does not perform any extra work, the fabric retains no in-plane strain after buckling, as shown in the Appendix. In absence of any compression in the buckled fabric, d1 only provides for d after the instability: p2 2 y J 0l ¼ 4l 0 or 2l ð4Þ y0 ¼ ð J 0 Þ1=2 : p With known value of y0, the buckling shape is completely defined and the energies can be calculated. 3. Energies of deformation In the following derivations, stress, modulus and the bending stiffness are based on unit width which is the common procedure in the mechanics of the sheet materials. 3.1 Imposed membrane strain energy The membrane energy stored to the fabric under the force, which is the work performed by the feeder, which starts from zero and increases to F, is one-half the product of the force and the total movement: UC ¼
1 2 F l 2Y
ð5Þ
UC ¼
1 Y J 20 l: 2
ð5aÞ
or:
3.2 Bending energy of buckled fabric The bending energy due to the buckling is given by: Z U # B ¼ B=2 0" l ; ð y000 Þ " 2 ¼ ð24&dxÞ #
where B is the bending stiffness, i.e. rigidity per unit width. Substitution for the curvature from the assumed shape, equation (1), gives: Z 4p 4 B 2 1 2px dx cos2 U B ¼ 4 y0 l l 0 The value of the limited integral is one-half of the base, l, which results: UB ¼
4p 2 B J 0: l
ð6Þ
Estimation of safe fabric length 323
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3.3 Potential energy The energy due to elevation of the heavy fabric with areal density of w during the initial buckling is: Z 1 U P ¼ w ydx: 0
324
Substitution for the buckling shape, central deflection from equation (4) and integration results: wl 2 UP ¼ ð J 0 Þ1=2 : ð7Þ p 4. Balance of the energies The energy for buckling and lifting the weight is provided by the strain energy stored in the stable fabric and therefore sum of the energies given by equations (6) and (7) is equal to the work input, UC, given by equation (5a): 4p 2 B wl 2 1 J0 þ ð J 0 Þ1=2 ¼ Y J 20 l p l 2
ð8Þ
It is now possible to start from equation (8) and solve either for the dimensionless force or for the critical length as follows. 4.1 Buckling force After rearranging and introducing two dimensionless groups; J1 ¼ Yl 2/B and J2 ¼ wl 2/B, equation (8) can be written as: 8p 2 2J 2 þ ¼ J 0: J1 pJ 1 ðJ 0 Þ1=2
ð9Þ
Equation (9) can be numerically solved for determination of the dimensionless critical force J0 regardless of its cause, when the material properties and the span length are known. Figures (2) and (3) show variations of the dimensionless force with the dimensionless groups[2]. For no fabric weight, J2 ¼ 0, equation (9) gives a critical force twice the value for Euler’s column with both ends built-in. The reason is lack of movement of the force after buckling where the bending energy should be provided by the stored energy only. 4.2 Critical length In order to solve for the critical length, when the fabric is pushed over a rough surface, equation (9) should be rearranged leaving only one term containing the length. Denominator of the first term can be written as: Y 2 wl 2 J1 ¼ : Bw 2 Y and the ratio of the dimensionless groups in the second term as J2/J1 ¼ wl/Y.
Estimation of safe fabric length
Dimensionless Force, F/Y
0.12 0.1 0.08
325
0.06 J2 = 500 0.04 0.02
J2 = 100 10
0
0.5
1
2
1.5
2.5
3 × 105
J1,Y12/B
Figure 2. Variations of the critical force with J1
0.05
Dimensionless Force, F/Y
0.045 0.04 0.035
J1 = 200,000 J1 = 100,000
0.03 0.025
J1 = 600,000
0.02 0.015 0.01 0.005 0
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
J2,W13/B
Defining G1 ¼ Y 2/Bw 2 and G2 ¼ wl/Y, which are combinations of J1 and J2, and expressing the force in terms of the friction coefficient, f, and the fabric weight, J0 ¼ fwl/Y, equation (9) takes the form of: 8p 2 G1 G22
þ
2 ¼ f: pð fG2 Þ1=2
ð10Þ
Equation (10) has only one term, G2, containing the length which causes buckling and can be numerically calculated as a function of G1, which are a combination of fabric properties and the friction coefficient. Figures (4) and (5) show the variations of the safe fabric length in dimensionless form with the friction coefficient and G1.
Figure 3. Variations of the critical force with J2
326
Figure 4. Variations of the critical length with the friction coefficient
160 Dimensionless Critical, Length W/Y
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140 120 100 80 G1 = 0.1 60 G1 = 1
40
G1 = 1,000
20 0
0
0.1
0.2
0.3
0.4
0.6
0.5
0.7
Coefficient of friction, f
Dimensionless Critical Length, Wl/Y
18
Figure 5. Variations of the critical length with G1
16 14 12
f = 0.4
10 8
f = 0.6 f = 0.8
6 4 2
0
1
2
3
4
5
6
7
8
9
10
3/Bw2
G1, Y
5. Conclusions It is possible to derive equation (10) from equation (8) directly bypassing the calculation of the critical force, but J0 is important on its own merit. If for any reason, excess friction due to an increase in the friction coefficient or a jam, the force increases the pre-determined level; the operation can be stopped automatically by signal processing. This follows from the idea of designing intelligent sewing machines suggested by Stylios (1991) in his editorial comments, nearly two decades ago. 5.1 Critical force Decreasing the critical force with increasing J1 is its appearance in both denominators of the terms in the left-hand side of equation (9). Higher values of J1 result from a limper
and longer fabric which requires smaller buckling force. High in-plane modulus also helps in reducing the dimensionless force, F/Y. Effect of J2 on the critical force is quite opposite to the effect of J1. This group can be expressed as W/(B/l 2), where W is the weight per unit width of the fabric and B/l 2 is directly proportional to the buckling load of a weightless column of given length and stiffness. Increasing the weight will increase the critical force. For J2 ¼ 0, the curves give twice the Euler’s buckling forces in dimensionless form. 5.2 Critical length Effect of the friction coefficient on the critical length, Figure (4), is obvious from equation (10). For zero friction the equation gives G2 ¼ 1 and any length of the fabric can be fed with no instability problem. On the contrary, higher friction coefficients require shorter safe lengths. It is interesting to compare the rather small effect of G1 with the effect of the friction coefficient. The difference between the critical lengths for G1 ¼ 0.1 and G1 ¼ 1,000 is negligible for small values of f and is about 20 per cent for very high frictions. Except for a sharp drop of the curves at the beginning which start from infinity because of zero modulus which stores infinite energy (equation 5), the effect of G1 becomes almost insignificant as mentioned in the previous paragraph. Gradual decrease of the critical length with increasing G1 is mainly due to increasing the modulus which causes lower stored membrane energy. The effects of low stiffness, which can cause instability of a shorter length, and lower weight which needs smaller force to lift a longer fabric, almost cancel each other in the denominator. In fact for infinite G1, equation (10) shows that the dimensionless lengths become only functions of the friction coefficients. Notes 1. Including the in-plane strain energy was first mentioned by Gerchon and Grosberg who decided to follow a different approach. 2. These dimensionless groups have been shown to be the ratio of the in-plane energy to the bending energy and the ratio of the potential energy to the bending energy, respectively, during the complex buckling of the flexible sheets. References Clapp, T.J. and Peng, H. (1990), “Buckling of woven fabrics”, Textile Res. J., Vol. 60, pp. 285-92 and 641-645. Den Hartog, J.P. (1987), Advanced Strength of Materials, Dover, New York, NY. Gershon, D. and Grosberg, P. (1992), “The buckling of fabric during feeding into automatic sewing stations”, J. Text. Inst., Vol. 83 No. 1, pp. 35-49. Stylios, G.K. (1991), “Intelligent sewing machines, the future of garment manufacture”, Int. J. Cloth. Sci. Technol., Vol. 3 No. 5. Timoshenko, S. and Gere, J.M. (1961), Theory of Elastic Stability, McGraw-Hill, New York, NY. Further reading Amirbayat, J. and Hearle, J.W.S. (1986), “Complex buckling of flexible sheets”, Int. J. Mech. Sci., Vol. 28 No. 6, pp. 339-58.
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Appendix The in-plane deformation of the buckled fabric, if any, is given by: Z 1 d2 ¼ 1 dx 0
with:
328
1 ¼ J 0 cos u: Substitution for and cosu in terms of the gradient and applying approximation for small slope, as in the case of d in the main text results: Z 1 dx d2 ¼ J 0 : 2 2 2 2 0 1 þ ðp =2l Þy0 sin ð2px=l Þ After integration we get:
d2 ¼ J 0
l 1=2 K 2 2p 1 þ ðp =2Þ y20 =l 2
where: K ¼ tan
21
"
p2 1 þ 2 y20 2l
1=2
#l 2p x tan : l 0
For both limits of x ¼ 0 and x ¼ l, values of K are given by (N 2 1) p where N is a positive integer. The acceptable value for x ¼ 0 is 0, and for x ¼ l is 2p to give d2 ¼ J0l at y0 ¼ 0:
d2 ¼
1þ
J 0l 2 1=2 : y0 =l 2
ðp 2 =2Þ ·
For small values of the initial central deflection compared with the length and comparing the second term of the denominator of the above equation with equation (2) of the text for d shows that: J 0l d2 ¼ : ð1 þ ðd=l ÞÞ The total recovered in-plane deformation is d þ d2: J 0l ¼ d þ
J 0l : ð1 þ ðd=l ÞÞ
Solving for d gives:
d ¼ lðJ 0 2 1Þ and:
d2 ¼ l which are both impossible and show that the force disappears and starts from zero for next feeding step which causes the buckled fabric to collapse.
Corresponding author J. Amirbayat can be contacted at:
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Development and optimisation of image analysis technique for fabric buckling evaluation Jurgita Domskiene˙, Eugenija Strazdiene˙ and Paule Bekampiene˙ Department of Clothing and Polymer Products Technology, Faculty of Design and Technologies, Kaunas University of Technology, Kaunas, Lithuania
Fabric buckling evaluation
329 Received 12 September 2010 Revised 23 January 2011 Accepted 23 January 2011
Abstract Purpose – The purpose of this paper is to optimise parameters of digital image analysis to investigate the deformation behaviour of woven sample and to detect the onset and variation of wrinkling that occurs due to bias-tensioned fabric buckling. Design/methodology/approach – Using models of predescribed shape, the relationship between the digitized gray scale intensities and wrinkles of the surface are analysed and conditions of specimen illumination and filtering procedures are chosen. Findings – It is proposed to convert acquired images to binary to record the onset of buckling and to estimate critical buckling parameters of stretched woven samples. The threshold value is determined as mean value of approximated histogram of stretched specimen centre line. It is defined that profile curve and gray scale disperse presented by parameter CV can be used to obtain additional information and to compare behaviour of different samples during bias tension. Research limitations/implications – Proposed image analysis technique allows detection of the onset of buckling wave formation and evaluation of surface waviness changes in woven samples different in colour and weave type tension. However, the behaviour of fabric samples with sharp multicoloured and complicated patterns cannot be assessed by gray scale imaging. Originality/value – The proposed approach can be adjusted to investigate different wrinkling problems – buckling during simple shearing or picture frame test, seam puckering, draping. Keywords Fabric, Image analysis, Threshold, Gray scale, Buckling, Bias tension, Deformation Paper type Research paper
1. Introduction Textiles have attracted the attention of scientists and engineers due to their low weight and good formability properties. Textile materials are widely used in apparel or soft furniture production, interior or exterior decoration, in advanced architecture projects and various technical applications. Formability of woven textile material is referred to shear deformations when angle between two yarn systems are changed at crossover points. In plane shear behaviour of textiles is the most studied mechanical property and this mode of deformation is analysed in terms of experimental (Alamdar-Yazdi and Amirbayat, 2000; Bekampiene˙ and Domskiene˙, 2009; Boisse et al., 2005; Domskiene and Strazdiene, 2005; Pavlinic and Gersˇak, 2003; Peng et al., 2004; Zhu et al., 2007; Xue et al., 2005) and analytical (Cavallaro et al., 2007; Dolatabadi and Kovarˇ, 2009a, b; Ruı´z and Gonza´lez, 2006; Peng et al., 2004; Potluri et al., 2006; Lebrun et al., 2003) investigations. Two tests are mainly used for the shear properties investigations: picture frame (lozenge framework of four rigid and articulated bars) and bias tension (principal directions at 458 angle with regard to the tension direction). Deformed plain
International Journal of Clothing Science and Technology Vol. 23 No. 5, 2011 pp. 329-340 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111166266
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fabric looses form stability when critical shear deformations are exceeded and out of plain wrinkles are formed because of fabric buckling. Regarding the limit of shear deformations when buckling phenomenon is observed many researchers used analytical models to obtain accurate and reliable characterization of wrinkling (Zhu et al., 2009; Xue et al., 2002). Previous studies (Domskiene and Strazdiene, 2005) proved new criterions for fabric formability evaluation by critical buckling parameters when the onset of buckling wave was defined during uniaxial bias tension experiment. It was proposed to adjust image analysis method to commit the moment when stretched fabric looses it stable form and starts to buckle. The study of buckling and post buckling behaviour is important aspect for future developments, especially in draping (Lin and Stylios, 2009) and shape-forming analysis, and in designing reliable equipment for shear testing (Potluri et al., 2006; Lebrun et al., 2003). A significant number of image analysis methods are applicable for the textile quality and behaviour evaluation. Digital image analysis technique enables the estimation of textile (yarn, woven, knitted non-woven) structure parameters ( Jeong and Jang, 2005; Lien and Liu, 2006; Tehran et al., 2006) and automated visual inspection to detect defects (Abouelela et al., 2005; Juciene˙ and Dobilaite˙, 2008; Kim et al., 2005; Xin et al., 2002) and to evaluate wrinkled fabric (Abril et al., 2008; Militky´ and Mazal, 2007; Stylios and Sotomi, 1993; Xin et al., 2010). Displacements and strain fields of deformed sample are calculated carrying out digital image correlation analysis (Willems et al., 2009; Zhu et al., 2009). Whereas, image processing methods are widely used there is no universal system and individual programming of each particular task is necessary. Owing to the investigations of many researchers the conditions of image recording are very important therefore illumination, contrast, distance, magnification have to be controlled and optimised for the particular problem. With scanner application, it is possible to control all mentioned parameters and to warrant their constancy but it is difficult to adjust this method to acquit images of woven specimen during tension. Furthermore, front lighting is mainly used for the inspection of flat objects and for the wrinkled surface evaluation oblique illumination when light source is placed perpendicularly to a camera helps to highlight surface irregularities (Behera, 2004). The processing of acquired images is the second image analysis task when resulting image is prepared for a specific application. Owing to surface texture images of a fabric sample are naturally noisy and gray scale intensity variations arise not only from surface wrinkling. The procedures of image filtering have to be chosen with reason to reduce shadows produced by the fabric surface texture while shadows produced by wrinkles have to be left. The aim of presented investigations is to apply digital image analysis method to investigate the deformation behaviour of woven sample and to detect the onset and variation of wrinkling that occur due to stretched fabric buckling. Using models of predescribed shape, the relationship between the digitized intensities and wrinkles of the surface are analysed. It is proved that surface waviness can be evaluated by gray scale variation CV and profile curve of acquired image. 2. Methodic Models of certain shape (Figure 1) which simulate the buckling wave were used to optimise the conditions of image acquisition and processing and to define quantitative
criterions for the buckling wave evaluation during uniaxial tension. The shape of fabric buckling wave was assessed during production of models. The models of A group have one concave or convex wave with specific slow changes of height presented by the same radius (Figure 1(a)). The models of B group have complicated wave with several peaks. The surface waviness was described by the changeable parameters of models: wave width am and wave depth hm for the A group models and total waves width am and total wave depth hm for the B group models (Figure 1(b)). Totally, 40 models were prepared for the digital image analyses. The digital image of object is described in a form of a two-dimensional matrix whose elements include quantified values of the intensity function, referred as gray scale levels. Digital camera was used to acquire images of models when illumination (4,000 K CFL) and distance (< 30 mm) were controlled (Figure 2). The images were captured using a spatial resolution of 2560 £ 1920 pixels and a gray level range of 8 bit (where 0 is black and 255 is white).
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3. Lighting techniques Correct illumination is critical to an image analysis because improper lighting can cause inaccurate image and unrepeatable analysis results. To ensure optimal illumination image analysis of prepared models was performed changing the angle between light source and model plane. In this research, the dark room was used to eliminate the influence of environmental illumination on quality of acquired images. am
A group
hm d = 21 mm
d = 21 mm
d = 21 mm
am B group
22 mm
a2m
22 mm
a1
a2m h2m h1m
hm
Figure 1. Frontal view and geometrical parameters of A group model (a) and principal of surface waviness parameters measurement for A and B group models (b)
Image acquisition Image card
Lighting angle 0 – 90°
PC
Image processing Object Screen
Profile curve
Histogram Standard deviation S Mean I
Gray Value
Light source
Distance ≈ 30 mm
Camera Changeable angle of illumination
150 100 50 0
0
255
200 400 600 800 Distance (pixels)
Figure 2. The scheme of image acquisition and processing
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The influence of illumination on the acquired digital images and variation of gray scale is shown in Figure 3. It is obviously that placing a light source from one side nearly perpendicular to a camera (lighting angle 08) provides perverted information about surface roughness but this technique can be used to find insignificant surface Model A of concave wave
332
Model A of convex wave
One side lighting (angle 0°)
I
I
50 100 150 200 250
50 100 150 200 250
pixels
pixels
Two side lighting (angle 0)
I
I
50 100 150 200 250
50 100 150 200 250
pixels
pixels
Two side lighting (angle 45)
I
I
50 100 150 200 250
50 100 150 200 250
pixels
pixels
Two side lighting (angle 90)
Figure 3. Image analysis of models with concave and convex waves: digital image and gray scale profile curve
I
I
50 100 150 200 250
50 100 150 200 250
pixels
pixels
irregularities such as flat buckling wave. The profile curves obtained changing illumination conditions of the same object proves the sensibility of acquired image to surface waviness (Figure 4). Two-side lighting (angle 08) shows no significant surface roughness changes however clear shadows due to wavy surface are recorded when the same model is illuminated from only one direction (lighting angle 08). Directional lighting of wavy surface provides shadows and variation of gray scale in the image presents the heights of shaped waves. As analysis of the same model shows (Figure 3) the concave and convex waves are recorded differently. It is easier to recognise concave shape of wave because in the image it is fixed as sharp jump of gray scale intensity as in a case of convex wave three intensity picks of gray scale represents the one wave. According to the investigation of the same shape model images when angle between lighting source and model plane changes can be stated that two-side lighting allows to record images where concave and convex waves can be separated but real place of waves are estimated almost exactly by front illumination (lighting angle 908). The variation of gray scale CV (Table I) confirms that the same level of surface irregularity is presented differently in a case of concave and convex wave type and near values of CV is estimated when images of model are recorded using front illumination. No regular disagreement and relationship between model colour and gray scale variation CV was estimated (Table I).
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4. Filtering Digital image filtering involves the computer processing of images that have been converted to numerical form. The input images were smoothed using Gaussian blur filter of 3 £ 3 pixel size to reduce the effect of noise (noise is produced from woven
Gray scale value I
250 200 150 Two side lighting
100
One side lighting
Figure 4. The profile curves of deformed specimen when one-side and two-side lighting are used
50 0 Specimen width, pixels
Lighting Type of wave shape Model colour
Gray Black White
One-side lighting (angle 08) Concave Convex wave wave 0.697 0.721 0.783
0.960 0.773 0.972
Two-side lighting (angle 08) Concave Convex wave wave 0.345 0.851 0.882
0.696 0.834 0.918
Two-side lighting (angle 458) Concave Convex wave wave 0.460 0.903 0.931
0.521 0.9251 0.927
Two-side lighting (angle 908) Concave Convex wave wave 0.668 0.771 0.871
0.663 0.789 0.879
Table I. The variation of gray scale CV for the same model changing model colour and wave shape
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fabric surface irregularities, illumination, camera imperfections) without effecting the information corresponding to surface buckling. When Gaussian blur filter is applied new value of each gray scale pixel is set to a weighted average of 3 £ 3 pixel’s neighbourhood. A higher value of blur radius will produce a higher amount of blur. The profile curves obtained from deformed specimen images and smoothed by different radius were compared (Figure 5). The value 3 of filtering radius rf was defined as the most suitable for the buckling wave evaluation during woven specimen bias tension. Smoothing filter rf ¼ 3 reduces the gray scale scattering but the range of profile curve remains the same (Figure 6). Some misalignments between profile curve obtained from input image and after smoothing is observed at the beginning of tension (1 ¼ 2/3%) (Figure 5). A specimen cut in bias is limp and non-uniform surface of it is presented as variation of gray scale and CV parameter because no pretension load is used during the test. Even rise of gray scale variation CV shows the certain changes in specimen surface roughness when buckling wave arises. 5. Threshold procedure Image processing by threshold procedure was used to recognize the moment when bias stretched woven specimen starts to buckle. Thresholding is a technique to separate the information in an image by turning all pixels below some threshold to zero and all pixels above that threshold to 1. When a binary image is created each pixel is colored
Gray scale variation CV
0.20
Figure 5. The profile curves of deformed specimen changing smoothing radius rf of input image
0 1 2 3 4 5 6 7
0.15 0.10 0.05 0 0
2
4
6
8
10
Specimen elongation e (%)
Profile curve of input image
200 150 100 50
Profile curve of processed image
0
250
Gray scale value I
Gray scale value I
250
Figure 6. The profile curves of input image and processed by 3 £ 3 Gaussian blur image of non-deformed woven sample (a) and stretched up to 15 percent of elongation sample (b)
rf
200 150 100
Profile curve of input image Profile curve of processed image
50 0
Specimen width (pixels)
Specimen width (pixels)
(a)
(b)
white or black, depending on a pixel’s value. To determine the value of threshold is the major issue in binary image processing. In this study, the threshold value was determined as mean value of approximated histogram of the stretched woven specimen. As analysis of various samples has shown this technique is able to commit the surface waviness changes for woven samples different in colour and weave (Figure 7). Threshold was automatically applied to the images taken at each 1 percent step of the specimen elongation. The starting point of buckling wave formation was considered to be the moment when the sharp closed contour of one colour spot which does not changes the place during tension was recorded.
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6. Image analysis The surface roughness can be evaluated by criterion of gray scale variation CV determined in a certain zone of deformed specimen image. The disperse of gray scale intensity expressed through variation coefficient CV: S CV ¼ ; I Input image
ð1Þ
Binary images of light (yarns of two colour) woven panama weave sample (yarn density 22 cm–1)
Buckling elongation ecr = 13 mm Threshold 154, e = 0 mm Input image
Buckling elongation ecr = 6 mm
Threshold 151, e = 13 mm
Threshold 148, e = 17 mm
Threshold 144, e = 20 mm
Binary images of dark woven twill weave sample (warp yarn density 32 cm–1, weft yarn density 19 cm–1)
Threshold 46, e = 0 mm
Threshold 50, e = 5 mm
Threshold 43, e = 10 mm
Threshold 36, e = 15 mm
Figure 7. Image processing by threshold procedure to commit moment when stretched specimen buckles
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where S is the standard deviation of gray scale intensity and I is the average value of gray scale intensities: PP I ¼ i¼1 I i ; ð2Þ P
336
where Ii is the i value of gray scale intensity, P is the total number of pixels in the analysed zone/line. The accuracy of chosen criterions was checked using the predescribed shape models clarified in Figure 1. It was defined that dependencies between surface roughness (ratio wave’s width am/wave’s depth hm) and variation of gray scale (parameter CV) can be described by exponential function y ¼ a þ bx c (Figure 8). In the case of concave surface, the accuracy of approximation is higher (coefficient of correlation r 2 ¼ 0.95) therefore in the case of convex surface the values of correlation coefficient are lower (r ¼ 0.81) because convex surface in digital image is observed with lower contrast of gray scale. Otherwise, steep wave of concave surface in digital image is fixed as a dark shadow with sharp contrast. Comparing the profile curves obtained from buckled specimen centre line and centre zone was concluded to use profile curve of stretched fabric specimen centre line (1 pixel width) due to sharper range (Figure 9). Method to calculate gray scale intensity variation in centre zone of specimen is more complicated because the zone of buckling 1.0 CV = –0.10 + 0.28 y–0.44 R2 = 0.95
0.8
CV
0.7 0.6 0.4
Figure 8. The dependence between ratio y (wave width/depth) and variation CV in the case of concave wave model
0.2 0 0
2
4
6
y = am /hm
Gray scale variation CV
Figure 9. The variation of parameter CV in sample F1 measured in a centre line and certain zone of deformed specimen at every step of elongation
fixed blurred shadow
0.100 0.075 Centre line of specimen
0.050 0.025
Centre zone of specimen
0 0
2
4
6
8
Specimen elongation e (%)
wave has to be adjusted to every step of specimen elongation furthermore the flat part of buckled specimen determines lower range of parameter CV and does not present any reasonable information about buckling wave. 7. Comparative analysis of buckling behaviour Different behaviour of woven fabrics (Table II) during bias tension was evaluated on the background of gray scale intensity variation the graphs of which are shown in Figure 10. The onset of buckling wave was evaluated using threshold procedures and the critical buckling parameters (critical buckling load, critical buckling elongation) were estimated (Table III). The increase of parameter CV for sample F2 obtained before specimen buckling. During tension fabric yarns are deformed: the density of specimen is changed due
Number of yarns per unit length (cm2 1) Warp Weft
Fabric code
Content
F1 F2
100% cotton 100% glass
48 12
30 11
Linear density (tex) Warp Weft 22.70 34.09
Area density (g/m2)
Thickness (mm)
171 120
0.30 0.14
14.40 33.67
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Table II. The specification of tested fabrics
0.20 0.18 Gray scale variation CV
0.16 0.14 0.12
Sample F1 (cotton)
0.10 0.08
Sample F2 (glass)
0.06 0.04 Buckling points
0.02 0 0
Fabric code F1 F2
10
20 30 Specimen elongation e (%)
40
50
Critical load (Pcr) (N/mm)
Critical elongation (1cr) (%)
Critical shear angle (gcr) (8)
18.0 1.6
6.0 13.0
6 47
Figure 10. The variation of parameter CV in samples F1 and F2
Table III. The critical buckling conditions for 458 stretched fabric samples
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to shearing and sliding and zones of uniform deformations can be separated in early stages of glass fabric elongation. Figure 10 shows sharp increase of parameter CV and the peak of curve is obtained at elongation of 18 percent. Further increase of elongation raises the decrease of specimen F2 surface waviness because the depth of buckling wave decreases as in the case of cotton sample F1 continues increase of surface roughness is recorded. The yarn nature and properties are the main reason of higher friction at yarns crossover points and worse formability properties of cotton fabric (Bekampiene˙ et al., 2008) when onset of buckling is earlier then in the case of glass sample. 8. Conclusions Digital image analysis technique as simple method for measuring changes of limp textile deformed surface is proposed in this paper. On the basis of predescribed shape models image analysis methodic and conditions of specimen illumination and filtering procedures are chosen to describe woven specimen buckling during bias tension. It is proposed to convert acquired images to binary to record the onset of buckling and to estimate critical buckling parameters of stretched woven sample. The threshold value is determined as mean value of approximated histogram of stretched specimen centre line. It is defined that profile curve and gray scale disperse presented by parameter CV can be used to obtain additional information and to compare behaviour of different samples during bias tension. Proposed image analysis technique allows to detect the onset of buckling wave formation and to evaluate surface waviness changes during woven samples different in colour and weave type tension. It is important to notice that described technique does not give reliable results for fabric samples with sharp multicoloured and complicated patterns. References Abouelela, A., Abbas, H.M., Eldeeb, H., Wahdan, A.A. and Nassar, S.M. (2005), “Automated vision system for localizing structural defects in textile fabrics”, Pattern Recognition Letters, Vol. 26, pp. 1435-43. Abril, H.C., Millan, M.S. and Valencia, E. (2008), “Influence of the wrinkle perception with distance in the objective evaluation of fabric smoothness”, Journal of Optics A: Pure and Applied Optics, Vol. 10, pp. 1-10. Alamdar-Yazdi, A. and Amirbayat, J. (2000), “Evaluation of the basic low stress mechanical properties (bending, shearing and tensile)”, International Journal of Clothing Science & Technology, Vol. 12 No. 5, pp. 311-32. Behera, B.K. (2004), “Image-processing in textiles – a critical appreciation of recent developments”, Textile Progress, Nos 2-4. Bekampiene˙, P. and Domskiene˙, J. (2009), “Analysis of fabric specimen aspect ratio and deformation mechanism during bias tension”, Materials Science¼Medzˇiagotyra, Vol. 15 No. 2, pp. 167-72. Bekampiene˙, P., Diliu¯nas, S., Domskiene˙, J. and Strazdiene˙, E. (2008), “Analysis of woven element deformation in fabric forming process”, Mechanika 2008: Proceedings of 13th International Conference, April 3-4, Technologija, Kaunas Lithuania, Kaunas, pp. 57-61. Boisse, P., Zouari, B. and Gasser, A. (2005), “A mesoscopic approach for the simulation of woven fibre composite forming”, Composite Science and Technology, Vol. 65, pp. 429-36.
Cavallaro, P.V., Sadegh, A.M. and Quigley, C.J. (2007), “Decrimping behavior of uncoated plain-woven fabrics subjected to combined biaxial tension and shear stresses”, Textile Research Journal, Vol. 77 No. 6, pp. 403-16. Dolatabadi, M.K. and Kovarˇ, R. (2009a), “Geometry of plain weave fabric under shear deformation. Part II: 3D model of plain weave fabric before deformation”, Journal of the Textile Institute, Vol. 100 No. 5, pp. 381-6. Dolatabadi, M.K. and Kovarˇ, R. (2009b), “Geometry of plain weave fabric under shear deformation. Part III: 3D model of plain weave fabric before deformation”, Journal of the Textile Institute, Vol. 100 No. 5, pp. 387-99. Domskiene, J. and Strazdiene, E. (2005), “Investigation of fabric shear behaviour”, Fibers and Textile in Eastern Europe, Vol. 13, pp. 26-30. Jeong, Y.J. and Jang, J. (2005), “Applying image analysis to automatic inspection of fabric density for woven fabrics”, Fibers and Polymers, Vol. 6 No. 2, pp. 156-61. Juciene˙, M. and Dobilaite˙, V. (2008), “Seam pucker indicators and their dependence upon the parameters of a sewing machine”, International Journal of Clothing Science & Technology, Vol. 20 No. 4, pp. 231-9. Kim, S.C., Kang, T.J., Hong, K.H. and Xu, B. (2005), “Image analysis for quantifying marquisette damage in home laundering”, Textile Research Journal, Vol. 75 No. 6, pp. 474-9. Lebrun, G., Bureau, M.N. and Denault, J. (2003), “Evaluation of bias-extension and picture-frame test methods for the measurement if intraply shear properties of PP/glass commingled fabrics”, Composite Structures, Vol. 61, pp. 341-52. Lien, H.-C. and Liu, C.-H. (2006), “A method of inspecting non-woven basis weight using the exponential law of absorption and image processing”, Textile Research Journal, Vol. 76 No. 7, pp. 547-58. Lin, H. and Stylios, G.K. (2009), “Prediction of post-buckling deformation in fabric drape”, Journal of the Textile Institute, Vol. 100 No. 1, pp. 35-43. Militky´, J. and Mazal, M. (2007), “Image analysis method of surface roughness evaluation”, International Journal of Clothing Science & Technology, Vol. 19 Nos 3/4, pp. 186-93. Pavlinic, D.Z. and Gersˇak, J. (2003), “Investigations of the relation between fabric mechanical properties and behaviour”, International Journal of Clothing Science & Technology, Vol. 15 Nos 3/4, pp. 231-40. Peng, X.Q., Cao, J., Chen, J., Xue, P., Lussier, D.S. and Liu, L. (2004), “Experimental and numerical analysis on normalization of picture frame test for composite materials”, Composite Science and Technology, Vol. 64, pp. 11-21. Potluri, P., Perez Ciurezu, D.A. and Ramgulam, R.B (2006), “Measurements of meso-scale shear deformations for modelling textile composites”, Composite: Part A, Vol. 37, pp. 303-14. Ruı´z, M.J.G. and Gonza´lez, L.Y.S. (2006), “Comparison of hyperelastic material models in the analysis of fabrics”, International Journal of Clothing Science & Technology, Vol. 18 No. 5, pp. 314-25. Stylios, G. and Sotomi, J.O. (1993), “A new instrument for routine objective assessment of seam deformations in limp materials”, Laser Metrology and Machine Performance, Lamdamap 93, Computational Mechanics Publications, Blackshaw, pp. 233-8. Tehran, M.S., Pourdeyhimi, B. and Merati, A.A. (2006), “Grading of yarn appearance using image analysis and artificial intelligence technique”, Textile Research Journal, Vol. 76 No. 3, pp. 187-96. Willems, A., Lomov, S.V., Verpoest, I. and Vandepitte, D. (2009), “Drape-ability characterization of textile composite reinforcements using digital image correlation”, Optics and Lasers in Engineering, Vol. 47, pp. 343-51.
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Xin, B., Hu, J. and Baciu, G. (2010), “Visualization of textile surface roughness based on silhouette image analysis”, Textile Research Journal, Vol. 80 No. 2, pp. 166-76. Xin, B., Hu, J. and Yan, H. (2002), “Objective evaluation of fabric pilling using image analysis techniques”, Textile Research Journal, Vol. 72 No. 12, pp. 1057-64. Xue, P., Cao, J. and Chen, J. (2005), “Integrated micro/macro-mechanical model of woven fabric composite under large deformation”, Composite Structures, Vol. 70, pp. 69-80. Xue, P., Peng, X.Q. and Cao, J. (2002), “A non-orthogonal constitutive model for characterizing woven composites”, Composite: Part A, Vol. 34 No. 2, pp. 183-93. Zhu, B., Yu, T.X. and Tao, X.M. (2007), “An experimental study of in-plain large shear deformation of woven fabric composite”, Composite Science and Technology, Vol. 67 No. 2, pp. 252-61. Zhu, B., Yu, T.X. and Teng, J. (2009), “Theoretical modelling of large shear deformation and wrinkling of plain woven composite”, Journal of Composite Material, Vol. 43 No. 2, pp. 125-38. Further reading Dolatabadi, M.K., Kovarˇ, R. and Linka, A. (2009a), “Geometry of plain weave fabric under shear deformation. Part I: measurement of exterior positions of yarns”, Journal of the Textile Institute, Vol. 100 No. 4, pp. 368-80. Corresponding author Jurgita Domskiene˙ can be contacted at:
[email protected]
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Blouse sizing using self-reported body dimensions
Blouse sizing
Hein A.M. Daanen Department of Human Performance, Security and Safety, TNO Defence, Soesterberg, The Netherlands, and
Michel B. Byvoet Bivolino, Hasselt, Belgium
341 Received 14 August 2010 Revised 17 March 2011 Accepted 17 March 2011
Abstract Purpose – The challenge for companies selling clothing over the internet is to combine a minimal requested effort of the visitor in entering (body) information with low-percentage no-fit returns. The purpose of this paper is to present a method that converts self-reported information to individual adjustments of a female blouse. Design/methodology/approach – In total, 48 Belgian females participated in the study. Age, height, weight and bra size were the inputs for blouse sizing as well as the subjective assessment of hip and waist size and arm length. All subjects were accurately measured and the relationship between eight essential body dimensions for blouse design (neck, bust, waist, hip and wrist circumference, arm and back length and shoulder length) and the simple inputs was determined. All subjects fitted a blouse, the size of which was determined by bust circumference, and the necessary alterations to optimize fit were recorded. Findings – The subjective information provided for hip and waist shape was related to the measured hip and waist circumference (r ¼ 0.68 and r ¼ 0.79, respectively). The relationship for arm length measurements was less (r ¼ 0.38). The self-reported values enabled a fairly good prediction of the essential body dimensions (r ranged from 0.65 to 0.97). The suggested alterations during the fit test were well related to the difference between the essential body dimensions and sizing chart data. The fit of the resized blouse was judged positively by all but one subject. Originality/value – The authors are not aware of similar studies reporting a statistical method to establish a stepwise link between self-reported data and blouse dimensions. The method may be helpful to improve fit of garments sold over the internet. Keywords Body dimensions, Anthropometry, Garment fit, Clothing fit, Measurements, Electronic commerce, Garment industry Paper type Research paper
Introduction Clothing sales over the internet is rapidly increasing in volume. In 2006 about 3 percent of the clothing was sold over the internet in the UK, which is low compared to 10 percent for overall retail sales (http://econsultancy.com/blog/774-online-clothingsales-break-1bn-barrier). In Korea, the country with the highest internet density, the sales of clothing over the internet increased from 5 percent in 2001 to 15.3 percent in 2006. In both countries the sales of clothing over the internet exceeded e1 billion. The authors acknowledge: Arno Krul of TNO for the statistical processing of the data, Aicha Baza and Gaby Ratajczak of Bivolino for the technical recommendations in the research project and Joe Layden for the critical review of the manuscript. The work was funded by the EU FP7 project “Open Garments” (www.opengarments.eu).
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In order to supply the correct size to the customer, the user has to enter a size or body dimensions to the web site of the retailer. Entering a clothing size is problematic, since not all subjects know their size and moreover, sizing is not standardized. Vanity sizing increases the difference between clothing dimensions and body dimensions, in particular for females. Therefore, entering body dimensions seems most appropriate. However, taking body measurements at home is time consuming and error prone since the user needs specific measurement equipment and correct instructions on how to take the measurement. Hip circumference, for instance, has been shown to be underestimated by over 4.5 cm when consumer measure their own circumference as compared to an anthropometric specialist (Yoon and Radwin, 1994). There is a trend in the clothing industry to use 3D whole body scans for clothing size determination (Bye et al., 2006; Daanen and Van de Water, 1998). However, these systems are not yet available for customer use at home. The new Kinect scanner, attached to the XBOX 360 video game platform, may be one of the first 3D body scanning systems for the consumer market that may transfer body scans for clothing sizing (http://en.wikipedia.org/wiki/Kinect). An alternative approach is to ask the user what they know about their body and use this as input for sizing. For men’s shirts, the Belgian company Bivolino uses age, height, weight and neck circumference as inputs for shirt sizing. These four dimensions are well known by most men and provide enough information to provide 95 percent of the population with fitting shirts. Less than 5 percent of sales are returned due to improper fit. The company Bivolino wanted to extend the service to female blouses. Again, the intention was to minimize the number of inputs for the subjects. Pilot investigations showed that stature, weight and age were again important parameters. Collar size is not very important for females; instead a blouse should fit correctly at the bust level. Ashdown and DeLong (1995) showed that subjects can perceive differences in circumference of pants waist bands about 0.5 cm, and it is not unlikely that similar values may apply to blouse chest circumferences. Although most females do not know their bust circumference they do know the bra size, which is related to bust size. Therefore, we asked the females to supply stature, weight, age and bra size (underbust circumference and cup size). Other important parameters for a blouse are waist shape, hip shape and arm length. Those parameters were judged by the subjects subjectively. The first goal of the study was to investigate if this combination of objective and subjective information supplied by the subjects accurately predicted the real body dimensions as measured by a trained measurer. The second goal of the study was to investigate if the estimated body dimensions were appropriate enough to allow for a proper individual resize of a blouse. Therefore, the subjects fitted a series of standard sized blouses. The size of the best fitting blouse was recorded as well as adjustments to optimize fit. The adjustments were modeled and the model was used to generate the dimensions of an individually sized blouse. The resized blouses were refitted and the subjects gave their judgment on fit. We hypothesized that the relevant body dimensions could be predicted from the limited set of parameters (stature, weight, age, bra size and estimation of waist, hip and arm size) with sufficient accuracy to allow a female blouse to be made with satisfying fit for most subjects.
Methods Subjects A total of 48 female Belgian subjects were measured in this study. The subjects were 42 (SD ^ 13) year old (range 22-69), 66 (SD ^ 14) kg in weight (range 44-100), 166 (SD ^ 7) cm tall (range 154-185) and had a mean bust circumference of 96 (SD ^ 12) cm. Garments All subjects tried on a fitted long sleeve blouse. The sizes ranged from 34 to 52. Body dimensions The following body dimensions were determined according to ISO 8559: body mass (ISO Code 3.1.2), stature (2.2.1), neck circumference (2.1.3), shoulder length (2.1.4), arm length (2.2.23), back length (2.2.10), front length (2.2.14), front length (2.2.16), bust circumference (2.1.8), underbust circumference (2.1.10), waist circumference (2.1.11), wrist circumference (2.1.15) and hip circumference (2.1.12). The age and bra size were recorded as well. All subjects gave an indication of their waist and hip size on a five-point scale (1 – small, 3 – normal, 5 – wide) and arm length on a three-point scale (1 – short, 2 – normal, 3 – long). The correlation was calculated between the subjective and objective parameters (waist, hip and arm). The relation between reported bra size and bust circumference was also investigated. Thereafter, the dimensions bust, waist, hip, wrist and neck circumference and arm, back and shoulder length were estimated using multiple linear regression (StatSoft, 2008). Independent parameters were stature, weight, age, bra size and estimation of waist, hip and arm size. The resulting formulae are called the body dimension estimators (BDE). Fit testing The criterion for size selection of the blouse was the chest circumference at the bust level (bust circumference). When the bust circumference was , ¼ 83 cm, size 34 was issued. Size 36 was issued when the bust circumference was 83-87 cm, size 38 for bust circumference 87-91 cm and so on. The largest size was 52. The size corresponding to bust circumference was recorded and issued to the subjects. The subjects fitted the blouse and the following adjustments were recorded: . Hip. How much should be added to the horizontal circumference at hip level? . Waist. How much should be added to the horizontal circumference at waist level? . Wrist. How much should be added to get a good fit at the wrist? . Sleeve length. How much longer the sleeve should be? . Length-back. How much longer the blouse should be at the back? . Shoulder length. How much should be added to the distance between neck-shoulder point and acromion to get a proper fit? Figure 1 shows an example on how sleeve length modifications were determined. Adjustments and refit The recorded adjustments of the blouse were compared to the difference between the estimated body dimensions based on self-reported values (DBE-results) and the body
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Figure 1. Determination of the necessary change in sleeve length
Notes: The diference between the end of the sleeve and the midlocation of the styloids was recorded in cm
dimensions according to the blouse sizing table. The relations were determined using linear regression (StatSoft, 2008) and are called the blouse adjustment (BA) formulae. The blouse sizing table is a matrix with size on the horizontal axis and corresponding body dimensions on the vertical axis. For example, size 40 corresponded to bust circumference of 92 cm, neck circumference 36.6 cm, waist circumference 74 cm, hip circumference 98 cm, shoulder length 12.4 cm, arm length 62.1 cm, wrist circumference 16.2 cm and back length of 41.5 cm. If, for instance, the DBE formula estimated a hip circumference of 104 cm for a subject with blouse size 40, this subject had relatively wide hips (6 cm more than 98 cm of the sizing table). According to the BA formula for the blouse at the hip, the adjustment of blouse should be 1.1 cm. The changes were made for each blouse and 45 subjects came back for a refit of the adjusted blouse. The satisfaction of the subjects concerning blouse fit was recorded. Results Relation between subjective and objective data There is a good relation between the subjectively estimated waist size and the measured waist circumference (Figure 2, r ¼ 0.79). This is also true for the hip (Figure 3, r ¼ 0.68). For arm length, the relationship is less accurate (Figure 4, r ¼ 0.38). Individual body dimensions Each measured individual body dimension was estimated based on stature, weight, age, bra size and the answers on the three questions (hip shape, waist shape and arm length). For example, the result of the multiple regression for bust circumference is shown in Figure 5. The correlation of this BDE is 0.97 and the mean absolute difference was 2.5 cm. Similarly, the waist, hip, wrist and neck circumference were estimated
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120
Waist circumference (cm)
110 100
345
90 80 70 60 50
Small 0
1
Normal 2
3
Wide 4
5
6
Waist shape (subjective)
Figure 2. Relation between subjectively reported hip shape on a five-point scale (small to wide) and hip circumference in cm. The regression line is shown
135 130
Hip circumference (cm)
125 120 115 110 105 100 95 90 Small 85
0
Wide
Normal 1
2
3
4
5
6
Hip shape (subjective)
as well as shoulder, arm and back length. The results of the regression analysis are presented in Table I. Blouse dimensions The fitted blouse size was selected based on bust circumference. The corresponding body dimensions for the fitted blouse size were selected from the blouse-sizing table. The BDE values were subtracted from these dimensions in the sizing table. The difference shows how a particular subject deviates from the average. In Figure 6,
Figure 3. Relation between subjectively reported waist shape on a five-point scale (small to wide) and waist circumference in cm. The regression line is shown
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Figure 4. Relation between subjectively reported arm length on a three-point scale (short to long) and arm length (from acromion to stylion) in cm. The regression line is shown
Arm length (cm)
74 70 66 62 58 54 Short 50
0
1
Normal
Long
2
3
4
Arm length (subjective)
Predicted bust circumference (cm)
130
Figure 5. Relation between measured and predicted bust circumference in cm. The regression line is shown
120
110
100
90
80
70 70
80
90 100 110 Measured bust circumference (cm)
120
130
Notes: Regression was based on age, height, weight, bra size and subjective assessment of hip and waist shape and arm length
the difference between predicted individual hip circumference and the hip circumference according to the sizing table is shown on the horizontal axis. The uppermost right point refers to a subject that had a hip circumference that was 20 cm more than what would have been expected for the blouse size she was fitting. This subject thus has a wide hip in respect to the bust circumference (the basis of the blouse size selection). Therefore, adjustments have to be made for her blouse pattern.
Age 0.14 0.26 20.02 0.01 0.02 0.03 0.02 0.06
Intercept 51.26 55.87 108.72 1.64 29.54 10.66 37.07 12.83 20.09 2 0.23 2 0.31 0.06 0.21 20.01 20.02 0.09
Height 0.61 0.74 0.85 0.03 0.17 0.08 0.15 0.04
Weight 0.11 0.02 2 0.11 2 0.02 2 0.19 0.02 2 0.08 0.08
Bra-underbust 1.17 0.08 20.04 20.12 0.46 20.05 0.12 20.19
Bra-cup 1.12 1.94 20.76 20.08 0.26 2 0.58 1.21 20.94
Waist shape 2 0.41 2 0.93 0.79 0.19 2 0.44 0.17 2 0.93 0.29
Hip shape
Correlation 0.97 0.97 0.97 0.68 0.82 0.87 0.81 0.65
Arm length 2 0.67 2 0.03 1.13 2 0.10 0.78 2 0.05 0.19 1.02
Notes: The bra-cup was coded as: aa ¼ 1, a ¼ 2, b ¼ 3, c ¼ 4, d ¼ 5, e ¼ 6, f ¼ 7, g ¼ 8, h ¼ 9; italic values indicate significant contributions; the correlation is the multiple regression coefficient
Bust circumference (cm) Waist circumference (cm) Hip circumference (cm) Shoulder length (cm) Arm length (cm) Wrist circumference (cm) Neck circumference (cm) Back length (cm)
Estimated body dimension
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Table I. Results of the multiple linear regression analysis to estimate individual body dimensions based on age, height, weight, bra size and three questions: waist shape, hip shape and estimated arm length
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12 necessary adaptation of hip circumference (cm)
348
14
10 8 6 4 2 0 –2 –4 –6 –8 –6 –4 –2 0 2 4 6 8 10 12 14 16 18 20 22 difference between predicted individual hip circumference and hip circumference according to the sizing table (in cm)
During the fit test, the clothing expert noted that this subject needed 13 cm extra (Figure 6, upper right point). There was a good relation between the difference and registered adaptation (r ¼ 0.85). This regression line is the BA formula for BA at the hip. Similar to the hip, the other blouse dimensions were adjusted. Table II shows the results. Bust circumference is not included since this parameter was used to select the blouse size. Also, neck circumference is not determined since most ladies never close the collar and thus this parameter is not critical. Refit Only three subjects out of 48 could not participate in the refit. Of the remaining 45 females, 39 were satisfied with the fit. The six subjects that reported fit problems are all analyzed in more detail. Two females were pregnant. For them, the blouse was adjusted around the belly. This resulted in proper fit. Four subjects were not satisfied. One subject was dissatisfied about the sleeve length that was considered too long, but the rest of the fit was satisfactory. Two subjects observed that the blouse was too wide. One of them lost 8 kg between fit and refit. Table II. Results of the linear regression analysis that relate individual adaptations to the difference between estimated individual body dimensions and values according to the sizing chart for the specific blouse
Adaptation Waist circumference (cm) Hip circumference (cm) Shoulder height (cm) Arm length (cm) Wrist circumference (cm) Back length (cm)
Intercept
Slope
n
r
2 2.14 2 2.87 0.25 2 0.13 2 1.80 2 0.22
0.58 0.67 1.00 0.73 0.65 0.25
35 42 44 40 46 40
0.90 0.85 0.91 0.95 0.70 0.35
Notes: n – number of registered adaptations; r – Pearson regression coefficient; italic values indicate significant contributions
Finally, one female erroneously reported the bra dimensions of her daughter, which resulted in a size mismatch. In conclusion, two out of 45 subjects (4 percent) can be identified as misfits without a clear cause. Discussion The study describes a method that uses self-reported body dimensions that can be easily transferred over the internet for individual adjustment of ladies blouses. Krul et al. (2010) observed that subjects are generally well aware of their weight and stature, although gender and location specific over- or underestimation may occur. These deviations can be corrected using a correction formula based on age, country and gender so that the final estimation of height and weight is more reliable. The subjective assessment of hip and waist shape seemed to be well related to the measured hip and waist circumference (Figure 2 and 3). Thus, without measuring, a fair impression can be achieved by asking for the hip and waist shape. Some companies use pictograms on the internet to have an easier interface for the user (www.myshape.com/ shop/body-shape) as an input for sizing, but in this case the information on waist and hip is difficult to separate. For correct sizing, knowledge about the individual body dimensions of the client is essential. Table I shows that assessment of the essential body dimensions for blouse sizing is fairly reliable. However, it is good to realize that for a close and tight fit, the real body dimensions will be necessary. For a loose fit, the allowable error is larger than for tight fit. For female blouses the fit at bust level is considered to be most important and this parameter is also used to select the blouse size. Every blouse is individually adjusted based on the results of a fitting test. In the fitting test, the necessary adaptations to get a better fit are recorded. These adaptations seem to match well with the difference between the estimated body dimensions and the results from the sizing table (Figure 6, Table II). Each garment item should have a sizing table in which the corresponding body dimensions for each garment size are outlined. In a separate table the allowance should be specified, e.g. 4 cm at the hip level. This allowance table establishes the link between body dimensions and garment dimensions. In practice, there is often confusion between body dimensions and garment dimensions; for instance many sizing tables consider sleeve length as a body measurement. A proper statistical analysis of fit is only possible when unambiguous sizing tables are used. The adjusted patterns for the ladies blouses were manufactured and supplied to the female subjects. The fit was much better than the initial standard sized blouses. It is good to realize that the presented results are specific for the particular blouse design and investigated population. The described methodology should therefore be applied for every garment and intended user group. The selected subjects for fit testing should be representative for the total user group and the selection should be large enough to yield sufficient statistical power. Conclusions In conclusion, a limited set of self-reported body dimensions can be used to estimate the real body dimensions of females. These body dimensions can be matched with sizing tables to make individual corrections to a garment and improve garment fit.
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References Ashdown, S.P. and DeLong, M. (1995), “Perception testing of apparel ease variation”, Applied Ergonomics, Vol. 26, pp. 47-54. Bye, E., LaBat, K.L. and DeLong, M.R. (2006), “Analysis of body measurement systems for apparel”, Clothing and Textiles Research Journal, Vol. 24, pp. 66-79. Daanen, H.A.M. and Van de Water, G.J. (1998), “Whole body scanners”, Displays, Vol. 19, pp. 111-20. Krul, A.J., Daanen, H.A.M. and Choi, H. (2010), “Self-reported and measured weight, height and body mass index (BMI) in Italy, The Netherlands and North America”, European Journal of Public Health, Vol. 21 No. 4, pp. 414-19. StatSoft (2008), STATISTICA (data analysis software system): version 8.0, available at: www. statsoft.com Yoon, J.C. and Radwin, R.G. (1994), “The accuracy of consumer-made body measurements for women’s mail-order clothing”, Human Factors, Vol. 36, pp. 557-68. Corresponding author Hein A.M. Daanen can be contacted at:
[email protected]
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Breast volume and bra size
Breast volume and bra size
Deirdre E. McGhee and Julie R. Steele Biomechanics Research Laboratory, University of Wollongong, Wollongong, Australia
351 Abstract Purpose – The purpose of this paper is to measure the breast volume of a large sample of women and their corresponding correctly fitted bra size, in order to demonstrate the range of volumes within each size and the variation amongst different bra sizes. Design/methodology/approach – Breast volume of 104 women was measured via water displacement and was compared to their professionally fitted bra size, in the one style and brand of bra. Findings – The mean breast volume of the left and right breast was 642 and 643 ml, ranging from 125 (size 10A) to 1,900 ml (size 24DD). The average professionally fitted bra band size was 12 (range size 10-24; Australian sizing) and cup size was DD (range A-G). A range of breast volumes was found to correspond to the same bra size and the volume of any one cup size was not homogenous amongst different band sizes. Practical implications – Appreciating the range of breast volumes that correspond to each bra size is important in terms of both bra structure and design in order to provide adequate breast support. The large variation in cup volumes associated with different band sizes suggests women should not consider themselves to be an isolated cup size, but rather a combination of a band and cup size. Originality/value – This is the first study to publish normative breast volume data, and the corresponding correctly fitted bra sizes, for a large sample of women. This is important information for bra design and to assist women achieve correct bra fit and support.
Received 23 October 2010 Accepted 16 March 2011
Keywords Women, Breasts, Water displacement, Bra fit, Bra design, Anthropometric measurement, Biomechanics, Garment industry Paper type Research paper
1. Introduction Sports bras are designed to provide external support to the anatomical support structures of the breast, which include the skin overlying the breasts and fine hair-like ligaments within the breasts called Coopers’ ligaments (Eichelberger, 1981; Gehlsen and Stoner, 1987; Haycock, 1988; Lorentzen and Lawson, 1987; Mason et al., 1999). Inadequate breast support, particularly during physical activity, can contribute to a variety of musculoskeletal symptoms such as head, neck, back and upper limb pain which, in severe cases, can force women to seek a reduction mammaplasty (Kaye, 1972). The larger a women’s breasts and the greater her age and level of physical activity, the greater the need for the bra to provide support (McGhee et al., 2010). In order for a bra to provide adequate support and be comfortable, it must fit properly (Page and Steele, 1999). However, up to 100 per cent of females have been found to be wearing ill-fitting bras (Greenbaum et al., 2003; McGhee and Steele, 2006; Pechter, 1998). The authors thank Steve Cooper from the Science Workshop, University of Wollongong, for constructing the breast volume measurement system. This research was funded by a University of Wollongong Early Research Career Grant and the New South Wales Sporting Injuries Committee. Author disclosure statement: no competing financial interests exist for either Deirdre E. McGhee or Julie R. Steele.
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This finding implies that many women do not know their true breast size and shape (Lee et al., 2004), such that they are unable to accurately match their breast volume to the correct bra cup size and, in turn, risk inadequate breast support. Previous research has found that the negative health outcomes associated with poorly supported large breasts can be relieved by up to 85 per cent by providing women with a correctly fitted, supportive bra (Greenbaum et al., 2003; Maha, 2000; Wilson and Sellwood, 1976). Therefore, it is imperative that strategies to ensure women can select a bra that fits them correctly are developed. Correct bra fit, where the breast is fully encased within the cup, requires that the volume of the bra cup should equate to the volume of the breast within it (Lee et al., 2004). An understanding by women and bra manufacturers of the magnitude of breast volume in relation to bra size is, therefore, vital to ensure correct bra fit, as well as to appreciate the level of support that a bra is required to provide. That is, the structure and design of a bra must suit the magnitude of the breast volume it is to support. Despite this, only two studies have previously been published that have investigated the relationship between breast volume and bra size (Sigurdson and Kirkland, 2006; Smith et al., 1986). Unfortunately, both of these studies compared breast volume data to “subject reported” bra sizes, with neither study confirming that these “subject reported” bra sizes fitted correctly, despite the high incidence of females reported to be wearing the wrong size bra (Greenbaum et al., 2003). Furthermore, both studies were limited by low subject numbers and did not standardise the style and brand of the “subject reported” bra size. Consequently, it was not possible to compare the breast volume of different bra sizes, as bra sizes are not standardised amongst different bra manufacturers (Caruso et al., 2006; Sigurdson and Kirkland, 2006; Smith et al., 1986; Westreich, 1997). The diverse physiognomy of the breast makes accurate and reproducible measurement of breast volume difficult (Westreich, 1997). The various methods used to quantify breast volume can result in widely varying breast volume measurements (Bulstrode et al., 2001; Kovacs et al., 2006; Losken et al., 2005), and no one method is universally accepted as the gold standard (Nahabedian and Galdino, 2003). Three separate categories of breast volume measurement methods are available; computer-analysed indirect visualisation techniques (Caruso et al., 2006), anthropometric measurements, and water displacement techniques. The computer-analysed breast volume measurement methods include mammograms (Bulstrode et al., 2001; Kalbhen et al., 1999), magnetic resonance imaging techniques (Bulstrode et al., 2001; Kovacs et al., 2007), biostereometric analysis (Loughry et al., 1987) and three-dimensional digital photography and scanning (Kovacs et al., 2007; Lee et al., 2004; Nahabedian and Galdino, 2003). These methods involve either radiographic or light projection onto the breast and use mathematical algorithms to calculate breast volume (Bulstrode et al., 2001; Sigurdson and Kirkland, 2006). Mammograms and three-dimensional scanning measurements have been validated by direct measurement of mastectomy specimens with high correlations (Bulstrode et al., 2001; Losken et al., 2005; Sigurdson and Kirkland, 2006). Although the computer-based methods to determine breast volume have been found to be reliable and valid (Bulstrode et al., 2001; Kalbhen et al., 1999; Kovacs et al., 2007), they are expensive, require specialised technical expertise, and can involve radiation exposure (Nahabedian and Galdino, 2003). The techniques are also limited by difficulties in delineating the outline of the breast (Kovacs et al., 2007; Lee et al., 2004; Losken et al., 2005) and the breast/chest wall interface (Losken et al., 2005; Loughry et al., 1987; Nahabedian and Galdino, 2003), as well
as in measuring ptotic breasts, where the lower aspect of the breast is in contact with the anterior chest wall (Kovacs et al., 2006, 2007; Lee et al., 2004; Losken et al., 2005; Nahabedian and Galdino, 2003). Anthropometric breast volume measurement methods use mathematical equations to calculate breast volume based on various measurements of the torso and breasts. Although anthropometric measurements are quick, inexpensive and ideal for clinical and bra fitting settings (Qiao et al., 1997; Sigurdson and Kirkland, 2006; Zheng et al., 2007), the complex and varying morphology of the breast makes no one parameter or mathematical equation standard for all breast sizes and shapes (Bulstrode et al., 2001; Westreich, 1997). Water displacement breast volume measurement methods involve either casting (Campaigne et al., 1979; Edsander-Nord et al., 1996; Smith et al., 1986) or custom-designed calibrated devices (Bouman, 1970; Bulstrode et al., 2001; Grossman and Roudner, 1980; Kirianoff, 1974; Kovacs et al., 2007; Tegtmeier, 1978; Tezel and Numanoglu, 2000). Casting creates a negative three-dimensional form of the breast, which is filled with water or sand to measure breast volume. Inaccuracies in breast volume arise, however, as the breast/chest wall interface is measured as a flat surface rather than its characteristic circular form. Calibrated devices (Bouman, 1970; Bulstrode et al., 2001; Grossman and Roudner, 1980; Kirianoff, 1974; Kovacs et al., 2007; Tegtmeier, 1978; Tezel and Numanoglu, 2000) include either adjustable geometric cones that are placed over the breast (Grossman and Roudner, 1980; Tegtmeier, 1978) or other calibrated devices (Bouman, 1970; Kirianoff, 1974; Tezel and Numanoglu, 2000) that the breast is lowered into, in order to measure the water that is displaced by a given breast. Breast volume is then equated to the displaced volume of water. Although these water displacement methods are relatively quick and easy to use, they have been reported to have limitations in the breast size (volume) they can measure (Bulstrode et al., 2001; Sigurdson and Kirkland, 2006) and in being difficult for subjects to use (Bulstrode et al., 2001). Despite the importance of breast volume to bra fit and design, no published study was found that reported normative breast volume data or the relationship between breast volume and a correctly-fitted bra size, in the one style and brand of bra. Therefore, the aim of this study was to measure the breast volume of a large sample of women and to show how this breast volume data varied with bra size in the one style and make of bra. We hypothesised that a range of breast volumes would correspond to any one bra size. 2. Methodology 2.1 Participants A total of 104 women representing a wide range of ages (mean 43.5 years, range 19-67 years) and body shapes (average height 165.2 cm, range: 147-182 cm; average mass 71 kg, range: 46-123 kg) were recruited as participants. As hormone levels can influence connective tissue within the breasts, participants were not currently breast feeding or pregnant and had no history of breast surgery. Having had children was not an exclusion criterion, whereby the participants reported having 0-5 children (mean ¼ 1.5), with 35 participants having not had any children. All recruiting and testing procedures were approved by the University of Wollongong Human Research Ethics Committee (HE05/83) and all participants gave written informed consent to participate in the study.
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2.2 Breast volume Breast volume was measured using a custom-designed water displacement device, which could cater for the wide range of breast sizes and breast shapes (pert, broad and ptotic breasts) displayed by the participants. Water displacement has previously been found to be a cost effective, reliable and valid method to measure breast volume (Bulstrode et al., 2001; Caruso et al., 2006; Grossman and Roudner, 1980; Tezel and Numanoglu, 2000). The device consisted of a four-litre graduated beaker supported within a frame and connected via tubing to a two-litre graduated cylinder (Figure 1). Participants leant forward on the frame, keeping their trunk horizontal in order to utilise gravity to hang the breast away from the chest wall (Loughry et al., 1987). The participants then placed their infra-mammary fold and sternum on the rim of the beaker, ensuring good contact (Bulstrode et al., 2001) so that each breast was individually placed into the beaker. The volume of water displaced by each breast (capacity 2000 ml) was measured in the cylinder to the nearest 25 ml. The device overcame previous limitations associated with water displacement devices in terms of a restricted breast size capacity that could be measured and subject difficulty in performing the measurement (Bulstrode et al., 2001; Sigurdson and Kirkland, 2006). Each breast was measured three times by the same assessor [DEM] (ICC r ¼ 0.968), ensuring that the position of the subject’s feet, torso, sternum and arms were standardised, as pilot testing revealed that variations in participant positioning affected breast volume measurement. 2.3 Bra size Professional bra fitting criteria (Choice Magazine, 2005; McGhee et al., 2010) (Table I) were used to qualitatively determine each participant’s correct bra size in the one style and make of bra (New Legend sports bra, Berlei, Pacific Brands, Victoria, Australia).
Figure 1. The custom-designed water displacement device used to measure breast volume
Band
A Too tight. Flesh bulging over top of band, subjective discomfort “feels too tight” A Too loose: Band lifts when arms are moved above head, posterior band not level with inframammary fold Cup A Too big. Wrinkles in cup fabric A Too small. Breast tissue bulging above, below or at the sides Under wire A Incorrect shape. underwire sitting on breast tissue laterally (under armpit) or anterior midline, subjective complaint of discomfort Straps A Too tight. Digging in, subjective complaint of discomfort, carrying too much of the weight of the breasts A Too loose. Sliding down off shoulder with no ability to adjust the length Front band A Not all in contact with the sternum Rating of bra fit A Pass. No errors or if hooks or straps can be adjusted to allow correct fit A Fail. Any other ticks
This size included both a cup size and a band size, using Australian sizes (McGhee and Steele, 2006). A qualitative method was used rather than a quantitative one through the use of bra size measurements, as previous studies have found these to be inaccurate in determining correct bra fit (McGhee and Steele, 2006, 2010; Pechter, 1998). This over came limitations of the two previous studies investigating breast volume and bra size (Sigurdson and Kirkland, 2006), as it ensured that the bra size matched to each breast volume fitted correctly and both the style and brand of bra was standardised (Westreich, 1997). Validity of the professional bra fitting criteria has previously been established (Choice Magazine, 2005), with an intra-rater reliability of r ¼ 0.92. 2.4 Statistics Descriptive statistics (means and ranges) were used to characterise the participants’ breast volumes. All statistical analyses were conducted using Prism software (Prism 11.5 for Windows). 3. Results/discussion 3.1 Breast volume and bra size The mean breast volume for the left and right breast of the participants was 642 (range 100-1,825 ml) and 643 ml (range 125-1,900 ml), respectively, (Table II). This range corresponded to bra sizes of 10A (150ml) to 2,000ml (24DD). The average professionally fitted bra band size was 12 (range size 10-24; Australian sizing) and cup size was DD (range A-G). A range of breast volumes were found to correspond to the same bra size (Table II) and the volume of any one cup size was not homogenous amongst different band sizes (Figure 2). The range of breast volumes of the participants was consistent with previous studies (Loughry et al., 1987; Nahabedian and Galdino, 2003; Sigurdson and Kirkland, 2006; Smith et al., 1986), as was the fact that a range of breast volumes was found to correspond to the same cup size in different band sizes (Sigurdson and Kirkland, 2006). That is, a 10D cup had a different volume to a 16D cup. This result supports the previous notion that cup size is not homogeneous in different band sizes and that band size and cup size are interdependent (Kanhai and Hage, 1999; Ramselaar, 1988; Regnault et al., 1972; Smith et al., 1986; Wise, 1956). It also suggests that females should
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Table II. Range of breast volumes and the corresponding professionally-fitted bra sizes for the participants
Breast volume range (ml)
Bra sizes (Australian)a
Number of participants
150-249 250-299 300-349 350-399 400-499 500-599 600-699 700-799 800-999 1000-1099 1100-1499 1500-2000 þ
8 10 5 6 19 18 7 3 10 8 6 4
10B/A 10B/C, 12B/C 10C, 12C/D, 14C 10D, 12D, 12D, 12B 10E, 12D/DD, 12D 10E, 12D/DD/E, 14C/D, 16C 10DD/E, 12D/DD/E, 14C 12F, 14DD, 16D/DD/E 12F, 14E/F, 16D 10G, 12F, 14E/F, 18D/E 12G, 16E, 18DD/F/G 14H, 16G, 24DD/H
Notes: n ¼ 104; aA table summarizing international bra sizing conversions can be found in McGhee and Steele (2006)
2,000 Volume left breast (ml)
Band 10
Figure 2. Left breast volume and professionally-fitted bra cup size, grouped according to bra band size
1,600
Band 12 Band 14
1,200
Band 16 Band 18
800
Band 20 400
Band 22
0 0
A
B
C
D
DD E Cup size
F
G
H
I
J
Note: Breast volume for the same bra cup size was not homogenous amongst different bra band sizes
not consider themselves to be an isolated cup size, but rather a combination of a band and a cup size, as their cup size will be different in a different band size. For example, a 12D cup is approximately 350 ml while a 16D corresponds to 1,100 ml (Table II). The wide range of breast volumes that corresponded to the same correctly-fitted bra size (band and cup combined) was consistent with previous research (Smith et al., 1986). This result can be attributed to between participant variability in breast shape (Bulstrode et al., 2001; Kovacs et al., 2006; McGhee and Steele, 2006; Nahabedian and Galdino, 2003), as well as breast volume measurement considerations, such as the level of breast immersion (Bulstrode et al., 2001; Caruso et al., 2006) and the accuracy of the breast volume measuring device (within 25 ml). Three breast shapes were observed in this study; pert, broad and ptotic breasts, whereby variations in breast shape affected
breast volume measurement. The broad and smallest breasts did not hang away from the chest wall as well as the ptotic breasts, making it difficult to completely immerse them in the water displacement beaker. Consequently, breast volumes for broad and small breasts tended to be underestimated. Variation in breast shape has previously been described (Bulstrode et al., 2001; Kovacs et al., 2006; McGhee and Steele, 2006; Nahabedian and Galdino, 2003) and suggested to affect bra fit comfort (Lee et al., 2004). The effect of breast shape on breast volume measurement found in the present study suggests that breast shape may be as important as breast volume in bra cup design (Lee and Hong, 2007; Lee et al., 2004). Therefore, for bra cup design purposes, a breast volume measurement method that simultaneously measures breast shape, such as scanning technology, is recommended. This study is the first to present the magnitude of breast volumes that correspond to a wide range of correctly fitted, standardised bra sizes, allowing comparison of breast volume amongst a large range of bra sizes. This information is important for both bra consumers and manufacturers as it highlights the range of breast volumes, and therefore breast masses (mass ¼ volume £ density), that bras are required to support. That is, the structure and design of a bra supporting a size 14F breast (1500 ml) should be different to that supporting a size 10B breast (, 250 ml). Therefore, manufacturers designing bras for volumes of this wide range must modify designs accordingly so that the bra design is appropriate for the corresponding breast volume, particularly for the large breast sizes, so that adequate breast support is achieved. Furthermore, women with larger breast volumes, and in turn a larger breast mass, will require greater breast support, to decrease the risk of any negative health outcomes secondary to their breasts, compared to women with small breast volumes. 4. Conclusion This study is the first to present the magnitude of breast volumes that correspond to a wide range of correctly fitted, standardised bra sizes. This information is important for bra manufacturers to ensure that bra structure and design suit the corresponding breast volume, particularly for the large breast sizes, so that adequate breast support is achieved. It is also important for bra consumers to appreciate the magnitude of their breast volume, particularly women with large breast volumes, to optimise their breast support and bra fit and, in turn, decrease their risk of negative heath outcomes secondary to their breasts. Furthermore, as cup size is not homogeneous in different band sizes and band size and cup size were found to be interdependent, it is recommended that women should not consider themselves to be an isolated cup size, but rather a combination of a band and cup size, as their cup size will be different in a different band size. References Bouman, F.G. (1970), “Volumetric measurement of the breast before and during mammaplasty”, British Journal of Plastic Surgery, Vol. 23 No. 3, pp. 263-4. Bulstrode, N., Bellamy, E. and Shrotria, S. (2001), “Breast volume assessment: comparing five different techniques”, The Breast Journal, Vol. 10, pp. 117-23. Campaigne, B.N., Katch, V.L., Freedson, P., Sady, S. and Katch, F.I. (1979), “Measurement of breast volume in females: description of a reliable method”, Annals of Human Biology, Vol. 6 No. 4, pp. 363-7.
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Caruso, M.K., Guillot, T.S., Nguyen, T. and Greenway, F.L. (2006), “The cost effectiveness of three different measures of breast volume”, Aesthetic Plastic Surgery, Vol. 30 No. 1, pp. 16-20. Choice Magazine (2005), “Shadow shop: bra fitting services. Fit for what?”, Choice Magazine, pp. 15-19. Edsander-Nord, A., Wickman, M. and Jurell, G. (1996), “Measurement of breast volume with thermoplastic casts”, Scandinavian Journal of Plastic & Reconstructive Surgery & Hand Surgery, Vol. 30 No. 2, pp. 129-32. Eichelberger, M.R. (1981), “Torso injuries in athletes”, Physician and Sportsmedicine, Vol. 9 No. 3, pp. 87-92. Gehlsen, G. and Stoner, L.J. (1987), “The female breast in sports and exercise”, in Adrian, Me (Ed.), Medicine and Sport Science, Karger, Basel. Greenbaum, A.R., Heslop, T., Morris, J. and Dunn, K.W. (2003), “An investigation of the suitability of bra fit in women referred for reduction mammaplasty”, British Journal of Plastic Surgery, Vol. 56 No. 3, pp. 230-6. Grossman, A.J. and Roudner, L.A. (1980), “A simple means for accurate breast volume determination”, Plastic & Reconstructive Surgery, pp. 851-2. Haycock, C.E. (1988), “The breast”, in Shangold, M. and Mirkin, G. (Eds), Women and Exercise: Physiology and Sports Medicine, F.A. Davis, Philadelphia, PA, pp. 181-5. Kalbhen, C.L., McGill, J.J., Fendley, P.M., Corrigan, K.W. and Angelats, J. (1999), “Mammographic determination of breast volume: comparing different methods”, American Journal of Roentgenology, Vol. 173 No. 6, pp. 1643-9. Kanhai, R.C. and Hage, J.J. (1999), “Bra cup size depends on band size”, Plastic and Reconstructive Surgery, Vol. 104 No. 1, p. 300. Kaye, B.L. (1972), “Neurologic changes with excessively large breasts”, Southern Medical Journal, Vol. 65 No. 2, pp. 177-80. Kirianoff, T.G. (1974), “Volume measures of unequal breasts”, Plastic and Reconstructive Surgery, Vol. 54, p. 616. Kovacs, L., Eder, M., Hollweck, R., Zimmermann, A., Settles, M., Schneider, A., Udosic, K., Schwenzer-Zimmerer, K., Papadopulos, N.A. and Biemer, E. (2006), “New aspects of breast volume measurement using 3-dimensional surface imaging”, Annals of Plastic Surgery, Vol. 57 No. 6, pp. 602-10. Kovacs, L., Eder, M., Hollweck, R., Zimmermann, A., Settles, M., Schneider, A., Endlich, M., Mueller, A., Schwenzer-Zimmerer, K., Papadopulos, N.A. and Biemer, E. (2007), “Comparison between breast volume measurement using 3D surface imaging and classical techniques”, The Breast Journal, Vol. 16 No. 2, pp. 137-45. Lee, H.Y. and Hong, K. (2007), “Optimal brassiere wire based on 3D anthropometric measurements of the under breast curve”, Applied Ergonomics, Vol. 38, pp. 377-84. Lee, H.Y., Hong, K. and Kim, E.A. (2004), “Measurement protocol of women’s nude breasts using a 3d scanning technique”, Applied Ergonomics, Vol. 35 No. 4, pp. 353-9. Lorentzen, D. and Lawson, L. (1987), “Selected sports bras: a biomechanical analysis of breast motion while jogging”, Physician and Sportsmedicine, Vol. 15 No. 5, pp. 128-39. Losken, A., Seify, H., Denson, D.D., Paredes, A.A. Jr and Carlson, G.W. (2005), “Validating three-dimensional imaging of the breast”, Annals of Plastic Surgery, Vol. 54 No. 5, pp. 471-8. Loughry, C.W., Sheffer, D.B. and Price, T.E. (1987), “Breast volume measurement of 248 women using biosterometric analysis”, Plastic Reconstructive Surgery, Vol. 80, p. 553.
Maha, S.A.A.H. (2000), “Sports brassiere: is it a solution for mastalgia?”, The Breast Journal, Vol. 6 No. 6, pp. 407-9. Mason, B.R., Page, K.A. and Fallon, K. (1999), “An analysis of movement and discomfort of the female breast during exercise and the effects of breast support in three cases”, Journal of Science and Medicine in Sport, Vol. 2 No. 2, pp. 134-44. McGhee, D.E. and Steele, J.R. (2006), “How do respiratory state and measurement method affect bra size calculations?”, British Journal of Sports Medicine, Vol. 40, pp. 970-4. McGhee, D.E. and Steele, J.R. (2010), “Optimising breast support in female patients through correct bra fit. A cross-sectional study”, Journal of Science and Medicine in Sport, Vol. 13 No. 6, available at: http://dx.doi.org/10.1016/j.jsams.2010.03.003 McGhee, D.E., Steele, J.R. and Munro, B.J. (2010), “Breast support education improves bra knowledge and bra wearing behaviour in young female athletes: a randomised controlled trial”, Journal of Physiotherapy, Vol. 56 No. 1, pp. 19-24. Nahabedian, M.Y. and Galdino, G. (2003), “Symmetrical breast reconstruction: is there a role for three-dimensional digital photography?”, Plastic and Reconstructive Surgery, Vol. 112, pp. 1582-90. Page, K.A. and Steele, J.R. (1999), “Breast motion and sports brassiere design. Implications for future research”, Sports Medicine, Vol. 27 No. 4, pp. 205-11. Pechter, E.A. (1998), “A new method for determining bra size and predicting postaugmentation breast size”, Plastic & Reconstructive Surgery, Vol. 102 No. 4, pp. 1259-65. Qiao, Q., Zhou, G. and Ling, Y. (1997), “Breast volume measurement in young Chinese women and clinical applications”, Aesthetic Plastic Surgery, Vol. 21 No. 5, pp. 362-8. Ramselaar, J.M. (1988), “Precision in breast reduction”, Plastic and Reconstructive Surgery, Vol. 82 No. 4, pp. 631-41. Regnault, P., Baker, T.J., Gleason, M.C., Gordon, H.L., Grossman, A.R., Lewis, J.R., Waters, W.R. and Williams, J.E. (1972), “Clinical trial and evaluation of a proposed new inflatable mammary prosthesis”, Plastic and Reconstructive Surgery, Vol. 50, pp. 220-6. Sigurdson, L.J. and Kirkland, S.A. (2006), “Breast volume determination in breast hypertrophy: an accurate method using two anthropomorphic measurements”, Plastic and Reconstructive Surgery, Vol. 118 No. 2, pp. 313-20. Smith, D.J. Jr, Palin, W.E. Jr, Katch, V.L. and Bennett, J.E. (1986), “Breast volume and anthropomorphic measurements: normal values”, Plastic and Reconstructive Surgery, Vol. 78 No. 3, pp. 331-5. Tegtmeier, R.E. (1978), “A quick, accurate mammometer”, Annals of Plastic Surgery, Vol. 1 No. 6, pp. 625-6. Tezel, E. and Numanoglu, A. (2000), “Practical do-it-yourself device for accurate volume measurement of breast”, Plastic & Reconstructive Surgery, Vol. 105 No. 3, pp. 1019-23. Westreich, M. (1997), “Anthropomorphic breast measurement: protocol and results in 50 women with aesthetically perfect breasts and clinical application”, Plastic and Reconstructive Surgery, Vol. 100 No. 2, pp. 468-79. Wilson, M.C. and Sellwood, R.A. (1976), “Therapeutic value of a supportive brassiere in mastodynia”, British Medical Journal, Vol. 2, p. 90. Wise, R.J. (1956), “A preliminary report on a method of planning the mammaplasty”, Plastic and Reconstructive Surgery, Vol. 17 No. 5, pp. 367-75. Zheng, R., Yu, W. and Fan, J.T. (2007), “Development of a new chinese bra sizing system based on breast anthropometric measurements”, International Journal of Industrial Ergonomics, Vol. 37 No. 8, pp. 697-705.
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About the authors Deirdre E. McGhee is an APA Accredited Sports Physiotherapist and Researcher at the Biomechanics Research Laboratory, University of Wollongong. She completed her PhD on sports bra design and bra fit and has incorporated breast support and bra fit education in treatment of associated musculoskeletal pathologies, postural education and in the promotion of physical activity in her female patients for the past 20 years. She has run workshops on bra fit and breast support for clinicians, athletes and the general public and co-authored, Sport Bra Fitness, an educational booklet on breast support and bra fit. Deirdre E. McGhee is the corresponding author can be contacted at:
[email protected] Julie R. Steele, PhD, is Director of the Biomechanics Research Laboratory and Head of the School of Health Sciences at the University of Wollongong. Her research over the past 28 plus years has focused on the biomechanics of injury prevention with a specific interest in mechanisms of lower extremity dysfunction. Her current research interests also include breast movement and brassiere design and human biomonitoring applications of intelligent fabrics. A Fellow of the Australian Federation of Sports Medicine, Professor Steele is currently President of the International Society of Biomechanics. She co-authored, Sport Bra Fitness, an educational booklet on breast support and bra fit.
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A new transient approach for testing water vapor diffusion of fabrics and fibers Wenfang Song and Weidong Yu Textile Materials and Technology Laboratory, Donghua University, Shanghai, China
Testing water vapor diffusion
361 Received 3 June 2010 Revised 28 September 2010 Accepted 28 September 2010
Abstract Purpose – The purpose of this paper is to describe a new transient approach for testing water vapor diffusivity of fabrics and fibrous assemblies. Design/methodology/approach – An apparatus was designed and built in order to investigate the transient water vapor diffusivity of fabrics and fibrous assemblies, and the apparatus is validated by applying a theoretical model and comparing the result obtained by the desiccant cup method. Findings – The transient water vapor diffusion test method permits rapid testing of small quantities of fabrics in a short amount of time. The method has an excellent correlation and agreement with the desiccant cup method. The variation of the new method is much smaller than the desiccant method. It also provided a way to study water vapor transfer through fibrous assemblies. Originality/value – The paper introduces a new approach for testing water vapor diffusivity of fabrics and fibrous assemblies. Keywords Diffusivity measurement, Transient mass transfer, Water vapor, Fabrics, Fibrous assembly, Human biology, Garment industry Paper type Research paper
Introduction Heat generated in a human body, due to metabolism, is released by four different ways including heat convection, heat radiation, respiration and sweat, where sweat is considered to be the most important one because it has the function of adjusting torso skin temperature to suit various surroundings. However, there is no denying that the sweat sometimes causes discomforts due to the wet microenvironment sandwiched between torso skin and clothes. Thus, it is highly desired that the clothes, as a medium between the skin and atmosphere, should allow sweat to pass through easily, i.e. has a high mass diffusivity of vapor. In order to achieve this object, researchers have been investigating several influence factors to the water vapor transfer performance of clothes, such as geometrical structures of fiber composite, physical and chemical properties of fiber material and ambient environment (Li, 1999; Berger, 2000; Lotens and Havenith, 1995). Besides, water vapor transfer performance studies, various test methods for measuring the mass diffusivity of fiber assemblies have also been developed during the last several decades. Among the cup methods, the upright cup method (ASTM, 1999) is designed for evaluating water vapor transmission rate of materials with high vapor transport resistance, but it is not very suitable for thin textiles with relative small vapor transport resistance because the existence of air layer between textiles and water will enlarge the vapor transport resistance and induce measurement errors. For solving the air layer problem, the inverted cup method is developed, however, it is only limited to waterproof textiles, because the tested materials must contact water directly.
International Journal of Clothing Science and Technology Vol. 23 No. 5, 2011 pp. 361-372 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111166293
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Meanwhile, both the upright cup and inverted cup methods have a common drawback that they take a long time to finish each experiment. Thereafter, in order to reduce testing time, the desiccant inverted cup method was developed ( JSA, 1999), where the testing time is reduced to 15 min. The desiccant inverted cup method is not suitable for low density fabrics, such as battings, because the fabric is easily compressed by the upper desiccant cup, leading to the change of their water vapor transfer ability. Compared to the cup methods, the sweating guarded hot plate method models (Farnworth, 1986; Boyer et al., 1991; Fan and Chen, 2002) the entire moisture transfer process from the body surface to the environment through the clothing system, which is more closely resembled what the reality is. However, in the sweating guarded hot plate, both the climate-controlled chamber and the data acquisition system are expensive, what is more, it may take more than 60 min for testing the material with high thermal capacity. In the aforementioned approaches, all fabrics are tested in fixed surroundings. Actually, in practical applications, the boundary conditions of clothing are always changing, e.g. a sudden sweat after severe exercise or a rapid moisture variation of the ambient environment, so it is important to test the mass diffusivity of water vapor in clothing in transient process (Mecheels et al., 1966; McCullough et al., 1989; Yasuda et al., 1992). Gibson et al. (1995) developed a dynamic moisture permeation cell to measure the transient water vapor diffusion resistance of fabrics. Later, Huang (Huang and Qian, 2007) constructed a similar but simplified one. Meanwhile, in the interest of fully model the actual wear situation of textiles, a sweating hot plate and a thermal manikin were fabricated to measure the dynamic response of heat and vapor transfer performance of clothing (Fan, 2002). But for this very reason, the system is so complex and expensive. In this paper, we will introduce a new transient approach to test the vapor transfer property of fabrics. By applying a theoretical model and comparing the result obtained by the desiccant cup method, the effectiveness and accuracy of this new method is validated. Furthermore, we studied the influence of compression on the water vapor diffusivity of fibrous assemblies to illustrate the application of the proposed method. Testing methods and apparatus Figure 1 is the main frame of the testing apparatus. On the left, the chamber shown is divided into three parts: (1) The upper chamber. (2) The sample chamber. (3) The lower chamber. The upper chamber is open to the atmosphere, so the air pressure in these three chambers keeps constant during the testing process, which is monitored by the air pressure sensors (7) and (8) placed at the upper and lower chamber, separately. The sample (14) is placed at the bottom of the sample chamber, and the sample density can be changed by compression through moving the upper chamber just like the function of syringe. The pressure applied on the sample is measured by the pressure sensor (6). On the right, after forced into the water vessel (9) by the air pump (11) and humidified by the water, the moist air enters into the upper chamber through a pipe (15). The water level is monitored by the differential transformer (10), so that the mount of the water evaporated will be supplied instantly by a small syringe. Owing to the partial pressure difference between the upper and lower chamber, the water vapor in the moist air
Testing water vapor diffusion
6 8 10
1
363 15
12 11 4 9
2 14 5 13 3
16 7
Notes: (1) the upper chamber; (2) the sample chamber; (3) the lower chamber; (4) the porous bottom plate of the upper chamber; (5) the porous bottom plate of the sample chamber; (6) the pressure transducer; (7) and (8) the air pressure probe; (9) the water vessel; (10) the differential transformer; (11) the air pump; (12) and (13) the humidity sensors; (14) the testing sample; (15) the pipe; (16) climate-controlled unit
penetrates the porous plate (4), passes the testing sample (13) and finally reaches the lower chamber through the porous plate (5). Two moisture sensors (11) and (12) placed at the upper and lower chamber are detecting the change of relative humidity with time. The whole testing system is located in a climate-controlled unit. The principle of the testing method is shown in Figure 2. The air pump blows with a fixed speed and constant humidity is maintained and distributed evenly in the upper chamber quickly. It is possible to detect transient moisture transferred because of the small dimension of the upper and lower chambers, the length and diameter of which are 8 £ 3 cm and 5 £ 3 cm, separately. Water vapor diffusion resistance is the most important parameter describing the moisture transfer ability of a material and is determined by the following process: Water vapor concentration in the lower chamber by experiment is calculated using equation (1): fP sw cexp ¼ ð1Þ RT where Psw, the saturated water vapor pressure of a certain temperature (Pa); T, the temperature (8C); cexp, the experimental water vapor concentration (mol m2 3); F, the relative humidity (%); and R, the gas coefficient 8.315 J mol2 1 K.
Figure 1. The new dynamic water vapor diffusivity tester
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h
Figure 2. The sketch of the transport picture of water vapor
d
c
Saturation vapor pressure (Psw) as a function of temperature is correlated with table values (Perry et al., 1984) by equation (2): T 2 273:15 P sw ¼ 614:3 exp 17:06 ð2Þ T 2 40:25 Water vapor penetration through fiber assemblies obeys Fick law, discussed by many researchers (Morton and Hearle, 1993; Sachdeva, 1996; Kothari, 2000). We use the law for calculation here. The initial conditions for the equation include co, the constant moisture concentration in the upper chamber (mol m2 3) and cstart, the moisture concentration of the lower chamber at t ¼ 0 (mol m2 3): dm dC ¼ 2DA ð3Þ dt dx where m, the water vapor flux through fiber assemblies (g); t, the time (s); D, the diffusing coefficient (m2 s2 1); A, the cross area of the fiber assembly 7.065 £ 102 4 m2; and C, the water vapor concentration (g m2 3). Water vapor flux through fiber assemblies (m) accumulates in the lower chamber and is calculated by equation (4): ð4Þ m ¼ ctheo M w V 0 £ 1026 where Mw, the molecular weight of water vapor, 18 g mol2 1; V0, the volume of the lower chamber (cm3); and cexp, the theoretical water vapor concentration (mol m2 3). The relation between C and cexp is determined by equation (5): C ¼ ctheo M w
ð5Þ
The theoretical water vapor concentration of the lower chamber can be derived from the equations (3)-(5), shown in equation (6): 6
ctheo ¼ c0 2 ðc0 2 cstart Þe ð2DA£10 =dV 0 tÞ
ð6Þ
where d is the distance between the upper and lower chambers, shown in Figure 2. By assuming different values for D, and bring them into equation (6), we can calculate the theoretical value for c. The diffusing coefficient (D) is determined as the D value, which yields a difference smaller than a given error allowance between the experimental and theoretical values for c. Then, the total water vapor diffusion resistance is calculated using equation (7). The intrinsic diffusion resistance of the sample is determined by subtracting the resistance of both the upper and lower porous plates, shown in Figure 2: d Rt ¼ ð7Þ D Ra ¼
d2h Da
365
ð8Þ
Rf ¼ Rt 2 Ra Rf ¼
Testing water vapor diffusion
ð9Þ
h Df
ð10Þ
where Rt, the total water vapor diffusion resistance (s m2 1). Df and Rf, the intrinsic diffusion constant and resistance of fabrics, respectively. h, the thickness of fiber assemblies (m). Da and Ra, the diffusion constant and resistance porous plates, respectively, which can be obtained by performing a test without a sample. Testing procedure and calibration of the method A variety of fabrics were selected for the samples, including high, medium and lower water vapor permeability ones. The specifications of these samples are listed in Table I. Fabric thickness was measured in accordance with GB/T 3820-1997. The air flow rate was measured by a digital air flow tester (YG461D) and all fabrics were measured with the same pressure difference of 100 Pa and fabric area of 20 cm2. The air temperature and relative humidity of the climate-controlled unit were adjusted to 17 ^ 0.58C and 62 ^ 2 per cent, respectively, during one test run. A circular specimen with the diameter of 4 cm was carefully mounted on the porous bottom plate of the sample chamber, the diameter of which is 3 cm. The specimen and the porous plate
Sample code A B C D
Fabric description Polyester fabrics coated with resin Cotton fabrics Silk fabrics Viscose fabrics
Air flow Weight Thickness Porosity Warp Weft rate (gcm2 2) (mm) (%) (/10 cm) (/10 cm) (mm s2 1) 0.0087
0.16
60.58
1,670
650
361.3
0.016 0.00796 0.0063
0.31 0.21 0.18
66.5 71.9 76.6
490 1,110 400
330 640 385
143.6 2,148.7 4,359.6
Table I. Parameters of fabrics selected
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was held tightly by the sample chamber, so that fabrics can exhibit flat state on the plate, eliminating the possibility of fabric crimp, at the same time, preventing the leakage of water vapor to the air. Open the switch, and wait until the upper chamber reach a stable moisture concentration state, then put the chamber above the sample. The relative humidity in both the upper and lower chambers was collected by the computer every 3 s. Normally, one testing is within 5 min.Totally, six replications were conducted for each sample. The final results were taken by averaging the six replications. In order to test the new measuring apparatus, comparison measurements were carried out between the new method and the desiccant cup test method (GB1037-88). The test procedure of the desiccant method is described as follows: the specimen was placed on an aluminum cup filled with desiccant with the height of 10 mm, covered with a gasket and then clamped into position (Figure 3). The distance between the desiccant and the fabric is 3 mm. The cup was placed in a test chamber with the air temperature of 178C and relative humidity of 90 per cent. The air velocity in the wind tunnel was controlled at 1 m s2 1. The cup was weighed to the nearest 0.001 g before being placed into the test chamber, then subsequent weightings were made at 16, 24, 48 and 96 h after placement in the chamber. Water vapor transmission rate of the fabric was determined by equation (11). Six replications were conducted for each sample to get the average result: G=t ð11Þ WVTR ¼ A where WVTR is the rate of water vapor transmission (g h2 1 m2 2), G is the weight change (g), t is the time during which G occurred (h) and A is the test area (m2). Results and discussion Water vapor through the empty sample chamber with the height of 3 cm was tested, shown in Figure 4. The upper chamber showed a slight decrease of its moisture concentration, because larger water vapor concentration gradient developed between the inside of the upper chamber and the surrounding air, as soon as the upper chamber was placed into the sample chamber. Water vapor transferred into the lower chamber from the upper one until it reached a stable state, when the water vapor concentration in the water vessel, the upper chamber and the lower chamber reached the same value. Fabric
Rings
Air layer
Desiccant
Figure 3. The desiccant cup method
Testing water vapor diffusion
Moisture Concentration (Mol/m3)
0.72
0.67
367 0.62
0.57
0.52 0
20
40
60
80
Time (s) The upper chamber (Exp)
The lower chamber (Exp)
The lower chamber (Theo)
Figure 4. Moisture concentration change with time in the lower chamber
The diffusion coefficient through air was calculated to be 2.5 £ 102 5 m2 s2 1, very close to that of water vapor under the atmosphere of 1 atm and 178C, 2.43 £ 102 5 m2 s2 1 studied by previous researchers ( Jost, 1960). This indicates that is no convective water vapor transfer occurs during the test. The test result of the samples is shown in Figures 5 and 6. It can be seen that the theoretical and experimental results are in good accordance with each other.
Moisture Concentration (Mol/m3)
0.524
0.5225
0.521
0.5195
0.518 0
50
100
150
200
Time (s) Sample A (Exp)
Sample A (Theo)
Sample B (Exp)
Sample B (Theo)
250
Figure 5. Moisture concentration change with time in the lower chamber of samples A and B
IJCST 23,5 Moisture Concentration (Mol/m3)
0.63
368
0.6
0.57
0.54
0.51
Figure 6. Moisture concentration change with time in the lower chamber of samples C and D
0
30
60 Time (s)
90
120
Sample C (Exp)
Sample C (Theo)
Sample D (Exp)
Sample D (Theo)
The parameters are shown in Table II. The relation of water vapor diffusion resistance and air flow rate is shown in Figure 7 and it is found that the two properties are well correlated as the correlation coefficient is 0.83, which is in accordance with previous studies (Yoon and Buckley, 1984). The intrinsic diffusion constant is linearly correlated to fiber assembly porosity and the correlation coefficient can reach up to 0.87, which is the explanation for the order of intrinsic diffusion constant (Df) of the samples: D . C . B . A. However, the intrinsic diffusion resistance (Rf) follows the order of B . A . C . D. The phenomenon is mainly explained from the aspect of fiber assembly thickness according to equation (9). Sample B is almost two times the thickness of the rest samples, leading to its worst water vapor transfer ability. The intrinsic water vapor diffusion resistance values from the new method were plotted against the water vapor transfer rate from the desiccant cup method. As shown in Figure 8, good correlation was obtained between two types of test methods for the materials tested. The coefficient of determination was 0.98. Although the two test methods are conducted at temperatures differing by 68C, the correlation between the two methods is excellent. Moreover, the new method showed smaller variation than the cup method. This also indicts the accuracy of the new method.
Sample code Table II. Test results of the two methods
A B C D
D (m s
2 21
)
1.64 £ 102 7 1.32 £ 102 7 1.43 £ 102 6 1.45 £ 102 5
Test methods New tester Variation Rf Df (%) (s m2 1) (m2 s2 1) 1.1 0.8 1.2 1.6
181,800 225,800 19,779 871.8
8.8 £ 102 10 1.4 £ 102 9 1.1 £ 102 8 2.2 £ 102 7
The desiccant cup method WVTR (g m2 2 h2 1) Variation (%) 13.8 13.5 14.9 15.4
4.1 4.5 3.8 4.8
Testing water vapor diffusion
Water Vapor Diffusion Resistance (104s/m)
23
16 R2 = 0.8305
369 9
2
–5
0
9
18
27
36
45
Air Flow Rate (102 mm/s)
Figure 7. Relation between water vapor diffusion resistance and air flow rate
Resistance from the new method (104s/m)
30 R2 = 0.9849 20
10
0
–10 13
13.5
14
14.5
15
15.5
Water vapor transmission rate from E96-BW (g/m2/h)
Measuring water vapor transfer property of fibrous assemblies under compression Another application of the apparatus is to study compression influence on water vapor transfer property of fibrous assemblies. It is known that fibrous assemblies such as goose down, polyester, cashmere are often used as filling materials of winter apparatus, quilts, pillows, car-seat upholstery, even building insulator, because of their excellent insulating property, especially thermal and water vapor transfer property. While in the practical use, these fibrous assemblies are easily distorted and compressed because of their low material density and using conditions, inducing the alteration of their thermal and water vapor transfer properties. So, it is significant to study compression influence on the two properties.
Figure 8. Correlation between water vapor transmission rate from the desiccant cup method and the water vapor diffusion resistance from the new method
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Three types of fibers were selected for the experiment listed in Table III. Figure 9 shows the water vapor transfer property of wool fiber assembly compressed from the density of 0.0071 g/cm3 to 0.035 g/cm3. The water vapor diffusion resistance data were plotted against the material density of the three types of fiber assemblies, shown in Figure 10. Water vapor diffusion resistance of wool and polyester decreased with the increase of material density, while the parameter of cashmere decreased first and then increased. The result is determined by both the material thickness and density. The method provides us a way to find an optimum structure with the best water vapor transfer property. It can also be seen that cashmere exhibits the worst water vapor transfer ability in the density range studied. There are several reasons for this. First, cashmere owns the lowest fiber fineness, so it has more and worse connected pores in the assembly, preventing the water vapor transfer. Second, the fiber is hygroscopic and has the biggest fiber surface area, benefiting the absorption of water vapor. All the above reasons lead to the worse water vapor transfer property of cashmere than the other two types of fiber assemblies. Polyester owns better water vapor transfer property than wool because of its crude fiber fineness and hydrophobic property. Fibers
Table III. Information of the materials
Average fineness (mm)
Curl density (unit/cm)
21 15.6 35
4.68 3.5 2.5
Wool Cashmere Polyester
Moisture Concentration (Mol/m³)
1.3
1.2
1.1
1
0.9
0
50
100
150
200
250
Time (s)
Figure 9. Moisture concentration of the lower chamber of wool under compression
The upper chamber (Exp) 0.0071 g/cm³ (Theo) 0.0213 g/cm³ (Theo) 0.035 g/cm³ (Theo)
0.0071 g/cm³ (Exp) 0.0213 g/cm³ (Exp) 0.035 g/cm³ (Exp)
Testing water vapor diffusion
Water Vapor Diffusion Resistance (s/m)
6,000
4,500
371
3,000
1,500
0 0
0.008
0.016
0.024
0.032
0.04
Density (g/cm3) Wool
Cashmere
Polyester
Conclusion The transient water vapor diffusion test method permits rapid testing of small quantities of fabrics in a short amount of time. The method allows one to examine a material’s transport behavior under transient condition and provided a new way to get the diffusion constant. The method has an excellent correlation and agreement with the desiccant cup method. Compared to the desiccant cup method, the result variation of the new method is much smaller, the measuring time is much shortened and the sample is in small quantities. Furthmore, the new method provides a way measuring water vapor transfer property of fibrous assemblies, which is not discussed in previous literatures. The method also provides a way to study water vapor transfer through fibrous assemblies under compression. The optimum structure with best water vapor transfer ability of fibrous assemblies was got by this method. References ASTM (1999), Annual Book of ASTM Standards – Part 3.01, American Society for Testing and Materials, Conshohocken, PA. Berger, X. (2000), “A new dynamic clothing model, part I: heat and mass transfer”, International Journal of Thermal Science, Vol. 39, pp. 673-83. Boyer, R.A., Bide, M., Dember, M.O., Francisco, A., Hindle, M.C., Ordonez, M.T. and Reardon, M.K. (1991), “An alternative method for testing moisture vapor transmission through textile fabrics”, Textile Chemists and Colorists, Vol. 23, pp. 17-20. Fan, J. (2002), “Measurement of clothing thermal insulation and moisture vapor permeability using a novel perspiring fabric thermal manikin”, Measurement Science and Technology, Vol. 13, pp. 115-23. Fan, J. and Chen, Y.S. (2002), “Measurement of clothing thermal insulation and moisture vapour resistance”, Measurement Science and Technology, Vol. 13, pp. 1115-23.
Figure 10. Water vapor diffusion resistance of different fibers in compression
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Farnworth, B. (1986), “A numerical model of the combined diffusion of heat and water vapor through clothing”, Textile Research Journal, Vol. 56, pp. 653-65. Gibson, P., Kendrick, C., Rivin, D., Sicuranza, L. and Charmchi, M. (1995), “An automated water vapor diffusion test method for fabrics, laminates, and films”, Journal of Industrial Textiles, Vol. 24, pp. 322-44. Huang, J. and Qian, X. (2007), “A new test method for measuring the water vapor permeability of fabrics”, Measurement Science and Technology, Vol. 18, pp. 3043-7. Jost, W. (1960), Diffusion in Solids, Liquids, Gases, Academic Press, New York, NY. JSA (1999), Japanese Industrial Standard: JISL 1099 Testing Methods for Water Vapor Permeability of Clothes, Japanese Standards Association, Tokyo. Kothari, V.K. (2000), Quality Control: Fabric Comfort, Indian Institute of Technology, New Delhi. Li, Y. (1999), “Fabric wetting factors”, Textile Asia, Vol. 6, pp. 39-41. Lotens, W.A. and Havenith, G. (1995), “Effects of moisture absorption in clothing on the human heat balance”, Ergonomics, Vol. 38, pp. 1092-113. McCullough, E.A., Jones, B.W. and Tamura, T. (1989), “A data base for determining the evaporative resistance of clothing”, ASHRAE Transactions, Vol. 95, pp. 316-28. Mecheels, J.H., Demeler, R.M. and Kachel, E. (1966), “Moisture transfer through chemically treated cotton fabrics”, Textile Research Journal, Vol. 36, pp. 375-84. Morton, W.E. and Hearle, J.W.S. (1993), Physical Properties of Textile Fibers, Wiley, New York, NY. Perry, R.H., Green, D.W. and Maloney, J.O. (1984), Perry’s Chemical Engineering Handbook, McGraw-Hill, New York, NY. Sachdeva, R.C. (1996), Fundamentals of Engineering Heat and Mass Transfer, New Age International, New Delhi. Yasuda, T., Miyama, M. and Yasuda, H. (1992), “Dynamic water vapor and heat transport through layered fabrics. Part II. Effect of the chemical nature of fibers”, Textile Research Journal, Vol. 62, pp. 227-35. Yoon, H.N. and Buckley, A. (1984), “Improved comfort polyester. Part I: transport properties and thermal comfort of polyester/cotton blend fabrics”, Textile Research Journal, Vol. 54, pp. 289-98. Further reading Lomax, G.R. (1985), “The design of waterproof, water vapor-permeable fabrics”, Journal of Industrial Textiles, Vol. 15, pp. 40-9. Corresponding author Weidong Yu can be contacted at:
[email protected]
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On the performance of a mitt heating multilayer: a numerical study Sandra Couto and Joao B.L.M. Campos Departamento de Engenharia Quı´mica, Transport Phenomena Research Centre, Faculdade de Engenharia da Universidade do Porto, Porto, Portugal, and
A mitt heating multilayer
373 Received 2 February 2011 Revised 12 April 2011 Accepted 12 April 2011
Tiago S. Mayor Centre for Nanotechnology and Smart Materials, Vila Nova de Famalica˜o, Portugal Abstract Purpose – The purpose of this paper is to investigate the heat transfer on an alpine-climbing mitt featuring an electrical heating multilayer, in order to provide information for the optimization of its thermal performance. Design/methodology/approach – A numerical model was developed to simulate the heat transfer across an electrical-heated alpine mitt. The model was used to study the heat losses as a function of the environmental conditions, to optimise the positioning of the heating elements, to determine the optimal power input to the heating system, to estimate the battery capacity requirements and to assess the effect of low-emissivity surfaces. Findings – The results show that: the heating elements assure approximately constant temperatures across the skin provided they are not more than 6-7 mm apart; the use of low-emissivity surfaces facing the skin can reduce the total heat loss by 8-36 per cent (for air layer thicknesses in the range 102 3 to 102 2 m) and to increase the skin temperature during the transient operation of the heating multilayer; the heat losses from the mitt are practically independent of the chosen heating power; and a battery capacity of 4 A h assures active temperature regulation for more than 18-23 h. Practical implications – By enhancing the thermal performance of an electrical heating mitt, the use of low-emissivity surfaces (facing the skin) can favour the thermal comfort perception of its user. Originality/value – The influence of several parameters on the thermal performance of an electrical-heated mitt is analysed and discussed. The findings are relevant for improving the performance of existing electrical heating garments. Keywords Heat transfer, Electrical heating layer, Low-emissivity, Metallization, Alpine mitt, Radiation, Convection Paper type Research paper
Nomenclature
G ¼ solar irradiance (1,373 W m2 2) x, y, z ¼ coordinates (m) P ¼ heating power (W m2 2) Q ¼ source term (W m2 3) T ¼ temperature (8C) t ¼ time (s) Subscripts avg ¼ average
min max Greek a 1 s
D
¼ minimum ¼ maximum symbols ¼ surface absorptivity ¼ surface emissivity ¼ Stefan-Boltzmann constant (5.67 £ 102 8 W m2 2 K4) ¼ difference
International Journal of Clothing Science and Technology Vol. 23 No. 5, 2011 pp. 373-387 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111166301
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1. Introduction The use of electrically heating elements in clothing/footwear products has been increasing in the last years as improvements in battery performances allow for longer effects (Holmer, 2005). Given that battery life is often strongly correlated with battery weight, this can be of paramount importance for activities involving strenuous efforts, such as in alpine climbing. In such activities, all unnecessary weight is severely questioned and, therefore, it is important in terms of products acceptance that any heating solution does not imply a marked increased in the weight to be carried. In that sense, it is crucial that the power requirements of such systems be thoroughly studied in order to allow for minimum battery weights. Low-emissivity surfaces are known to decrease the heat transfer by radiation (Cengel, 2002). They are used in very different applications such as building/construction, machinery, space technology, clothing apparel, etc. (Cengel, 2002; Holmer, 2005; Ma¨kinen, 2005). When used on clothing outer surfaces, they help to reduce the heat loss to surrounding colder mediums (e.g. a worker inside a cold chamber or an unlit astronaut outside the spacecraft) or diminish the thermal loads on the human body by reflecting partially the incident infrared radiation (e.g. a fire fighter near a ground fire or an astronaut exposed to solar radiation). When used facing the skin, they can contribute to the reduction of the radiant heat loss from the body (e.g. emergency care thermal blankets). However, the impact of low-emissivity surfaces in the reduction of the heat loss and gain from the human body depends on the relevancy of the radiant resistance when compared to the conductive (clothing) and convective resistances. For thinner clothes, for which the conductive resistance is small, the radiant resistances are more important. In these scenarios, changes in the emissivity of the surfaces may have a strong impact on the total heat exchange. The relevancy of this impact diminishes for clothes with increasing thickness (i.e. with higher conductive resistance) and for windier environmental conditions (where convective heat losses predominate over radiant ones (Holmer, 2005)). Thus, for every particular scenario, i.e. clothing ensemble and environmental conditions, it is necessary to evaluate the relative importance of the aforementioned resistances to assess the effect changes in clothing surface emissivity may have over the overall heat exchange to and from a human body. In order to address these questions, a thorough analysis was conducted focussing on the heat transfer across an alpine-climbing mitt featuring an electrical heating multilayer. The relevancy of conduction, convection and radiation heat transfer mechanisms was studied for different environmental conditions and heating powers in order to allow the optimization of the heating system performance and weight. The impact of surface metallization over the total heat exchange across the mitt and over the heating and cooling performance of the multilayer heating system was analysed. This provided valuable information for the development and optimization of the heating system. 2. Materials and methods 2.1 Physical situation under consideration This study aimed at the optimization of the thermal performance of a heating multilayer, developed for use with an alpine-climbing mitt, during extreme climbing activities (i.e. expeditions up to altitudes above 8,000 m). The heating multilayer (Figure 1) consists of a heating wire grid, knitted onto a fleece layer and covered by a thin lining. The whole heating multilayer
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Figure 1. Heating wire grid (infrared image)
(fleece þ heating wire grid þ lining) is intended for use in the interior of the glove, in contact with the skin. For the purpose of this study, four different environmental scenarios were considered (Table I), covering from harsh to mild conditions at the Everest Mountain. The air temperatures at this location are reported to vary between 2 368C in winter and 2 198C in summer whereas the wind is mentioned to reach 160 km h2 1 (Hambrey et al., 2008). However, according to alpinists (personal communication), it is not advisable to initiate expeditions when the wind is stronger than 60 km h2 1 (16.7 m s2 1), thus it was assumed that this is the maximum air velocity to which a climber may be exposed to. Table I summarises the air temperatures and velocities together with the corresponding heat transfer convective coefficients used in this study. The heat transfer coefficients were computed based on empirical correlations relating Nusselt, Reynolds and Prandtl numbers (Lienhard IV and Lienhard V, 2003). The scenarios shown in the table were chosen to address the conditions a climber might encounter during an expedition and to allow straightforward assessment of the relevancy of conduction, convection and radiation contributions in the total heat losses. 2.2 Heating multilayer The heating elements, electrically conductive yarns, are taken as perfect cylinders. The physical properties of the heating elements are assumed homogeneous (and equal to those of stainless steel, the main component: domain D in Table II). The heat production by Joule effect is taken constant throughout the yarn volume Scenarios I II III IV
Air temperature (8C)
Air velocity (m s2 1)
Heat transfer coefficienta ( J kg2 1 K2 1)
236 236 219 219
16.7 1 16.7 1
26.8 5.2 26.3 5.2
Note: aCalculated for a pressure of 0.33 atm (summit of Everest mountain, altitude of 8,850 m) Source: West (1996) and Mason and Barry (2007)
Table I. Environmental scenarios
Height z (m) 3.5 £ 102 2 2.5 £ 102 3 1.7 £ 102 4 1 £ 102 3
Width x (m)
3 £ 102 3 3 £ 102 3 3 £ 102 3 5 £ 102 4
A B C D
Table II. Dimensions and physical properties of the different model domains (Figure 2(c))
Domains 1 £ 102 3 1 £ 102 3 1 £ 102 3 1 £ 102 3
Thickness y (m) 0.046 0.045 0.043 44.5
Thermal conductivity k (W m2 1 K2 1)
116 68 358 7,850
Density r (kg m2 3)
350 210 370 475
Heat capacity Cp ( J kg2 1 K2 1)
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(consequence of constant electrical resistivity) and a function of the power supply and circuit association (serial/parallel). The operation mode (ON/OFF) of the heating multilayer depends on the temperature of the heating elements and on the evolution of their temperature over time. The system is ON and OFF mode when its temperature is lower or higher than Tmin and Tmax, respectively. When its temperature is in the range Tmin to Tmax, the system provides heating as long as the temperature is increasing over time. The lower temperature limit (Tmin) was set to 238C since the onset of cold-induced pain has been reported to occur between 148C and 238C during contact with cold surfaces (Havenith et al., 1992; cit. by: Brajkovic et al., 2001; Geng et al., 2006). The higher limit (Tmax) was set to 288C as this is mentioned as the threshold temperature for assuming comfort at the hands (Brajkovic et al., 2001).
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3. Simulation model The simulations were performed following a FEM approach, using a Core I7 2.80 GHz PC, with 20 Gb of RAM. The following sections provide details on the simulation model used in this study. 3.1 Geometry of simulation domain and material properties Figure 2(a) shows the glove plus the heating multilayer (fleece þ heating wire þ lining) placed in its interior whereas Figure 2(b) shows a section cut perpendicular to the arm axis (along plane xz, in Figure 2(a)). Owing to the existence of several planes of symmetry (along and perpendicular to the wire axis and along the midpoint between wires), only a small portion of the entire heating multilayer has to be considered in the simulation (Figure 2(c)). The dimensions and physical properties of the simulation domains are shown in Table II. 3.2 Boundary conditions 3.2.1 At the external surface. Four different environmental scenarios were considered for defining the heat flux boundary conditions at the glove external surface. The imposed heat fluxes, different for each of the four scenario considered, were computed based on the corresponding air temperatures and heat transfer coefficients (as given in Table I). Radiant heat losses to the environment were considered at the glove external surface, based on a surface emissivity of 0.92 (measured with a calibrated infrared camera). In the calculation of the radiant heat loss at the glove external surface, no radiant sources other than the glove itself were considered. Thus, the effect of the heat a
b A
c a
Hand
y
b
z x
Heating Band
c
z (a)
(b)
Dy
B x
C (c)
Notes: A, insulation layer; B, fleece layer; C, lining layer; D, heating wire
x z
Figure 2. (a) Glove þ heating multilayer (positioned in the glove’s interior); (b) section cut (along plane xz) of the glove þ heating multilayer; (c) geometry of the simulation domain
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gains from the solar and atmospheric radiation was discarded in these analyses (see the Appendix for details on the extension of this effect). 3.2.2 At the internal surface. Different boundary conditions were used depending on the type of simulation (steady state versus transient). Although the operation of the described heating band is intrinsically transient, meaning that its temperature varies over time in a transient way, it is obvious that this variation occurs within a given temperature range, dependent on the operation limits of the heating multilayer (in this case, 238C and 288C). Therefore, the steady-state analyses were based on a temperature boundary condition at the skin of 25.58C, i.e. midway between the mentioned limits (the consideration of average skin temperature in the steady-state analyses does not constitute a significant deviation from reality, particularly for increasing thickness of the internal air layer; see Section 4.3.2. for further information). In these analyses (Sections 4.2.2 and 4.2.3), no heat generation was considered at the heating wires. The exception was the analysis on the effect of the distance between heating wires (Section 4.2.1), for which preference was given to a heat flux boundary condition at the skin (similar to that used for transient simulations), in order to study the temperature profiles along the skin due to the local heat generation of the heating wires. A skin emissivity of 0.98 (Kurazumi et al., 2008) was used when considering radiant heat exchange between the skin and the lining. For the transient simulations, preference was given to a heat flux boundary condition at the skin in order to allow the evolution of its temperature over time as the natural outcome of the heating multilayer operation. In order to estimate the heat fluxes at the skin (hand), one could use complex thermal/comfort models (Fiala et al., 1999; Huizenga et al., 2001; Salloum et al., 2007) and perform whole-body simulations, in which the articulation of local and core temperatures should be implemented while taking into account the heat transfer between different body segments as well as heat losses at the skin level (dry versus evaporation heat losses). However, such approach would require estimates of a considerable amount of parameters (thermal properties of the main body tissues, heat transfer coefficients, blood perfusion rates, etc.), describing the thermal contributions of each body segment/portion. Such a holistic description of the thermal balance of the human body would be outside the scope of this work, thus, an alternative approach was followed for estimating the heat flux at the skin (hand). This parameter was based on the local basal metabolic rate of the hand, despite the associated clear under-prediction. This simpler approach was considered reasonable since it implies an over-prediction of the average heating requirements of the heating system which, ultimately, assures the resulting system is able to provide all the heating an alpinist may ever need. Different figures were found in the literature for the basal metabolic rate at the hands, namely 0.14, 0.188 and 0.25 W (Raman and Vanhuyse, 1975; Tanabe et al., 2002; Salloum et al., 2007), respectively. Using the medium value (0.188 W) and the hand surface area, one obtained the estimate of the heat flux at the skin (4.1 W m2 2) that was used as boundary condition in the transient simulations. 3.2.3 At the heating wires. The effect of the heating wires was introduced in the transient simulations through the use of a source term (Q in W m2 3, where m3 refers to the volume of heating wire) in the heat balance equation, whose value depends on the operation of the heating system (Q is 0 when the heating system if OFF and equal to the heating power, when the system is ON). The source term was computed based on the heating power of the multilayer (in W m2 2, where m2 refers to the surface area
of the portion of skin considered in the simulation domain), the cross-sectional area of its heating elements taken as perfect cylinders and the length and number of the heating elements existing in the simulation domain. 3.3 Simulation approach Steady state and transient analyses were developed in this study. Steady-state analyses were performed in order to highlight the relevancy of each transfer mechanism in the total heat loss as well as to allow a straightforward analysis of the influence of infrared reflective surfaces on the overall performance of the system under consideration (e.g. at the glove outer surface or at the skin-facing lining surface). Transient analyses were performed to study the effect over time of the heating multilayer power, to establish the energy requirements of the corresponding battery and to allow a thorough analysis of the effect of internal infrared reflective surfaces during the heating and cooling cycles.
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4. Results and discussion The following sections describe the main results obtained for the steady state and transient analyses performed. 4.1 Convergence, grid testing and computational requirements For all simulations geometries, grid tests were performed in order to define the grid characteristics which guarantee grid-independent results. Depending on the geometry in question, grids of 4.3 £ 104 to 3.8 £ 105 elements were used, which resulted in a maximum error of 0.2 per cent in the average normalized temperature of each simulation domain (Table III; grid 3). Similar approaches were developed to determine the time-step adequate for running the transient simulations. A compromise was found between accuracy and computational power requirements with a time-step of 0.1 s (resulting in a negligible error (8 £ 102 2 per cent) in the duration of an entire heating-cooling cycle). Depending on the type and characteristics of the simulations (transient/steady state, geometry of the simulation domain, with or without radiant heat exchange), up to 16GB of RAM were needed during the simulations. 4.2 Steady-state results 4.2.1 Distance between heating wires. In order to determine the ideal distance between the heating wires, several simulations were conducted with varying number of wires for the same total power (70 W m2 2, where the m2 refers to surface area of the portion of skin considered in the simulation domain, in this case 0.02 m £ 0.001 m; the total
Domains Grids
Nodes
A
B
C
D
1 2 3 4
892 24,538 43,021 68,765
0.9993 1.0000 1.0000 1.0000
1.0189 1.0004 1.0002 1.0000
1.0000 1.0000 1.0000 1.0000
0.8329 0.9967 0.9983 1.0000
Note: Data normalized by the temperatures obtained with the denser grid
Table III. Average normalized temperature of each simulation domain (Figure 2(c)), for grids with increasing density
45
30 25 20 15 0
0.005
0.01
0.015
0.025
∆T
20 DT (°C)
T (°C)
35
0.020
∆x
15
0.015
10
0.010
5
0.005
0.000 0 1 Wire 2 Wires 3 Wires 4 Wires
0.02
x (m) (a)
(b)
120
10 Conductive Flux Convective Flux Radiative Flux Glove outer Temperature
100 80
0 –10
60 –20
40
–30
20
–40
0 I
II
III (a)
IV
T (°C)
Figure 4. (a) Heat fluxes through the glove þ heating multilayer and temperature of the glove outer surface; (b) thermal resistances (conductive resistance and convection þ radiation equivalent resistance), for the four environmental scenarios studied (Table I) and constant skin temperature (25.58C)
25
1 Wire 2 Wires 3 Wires 4 Wires
40
Heat Flux (W•m–2)
Figure 3. (a) Temperature profile along x coordinate for different number of wires (for the same total power; 70 W m2 2); (b) maximum temperature difference at the lining (DT) and distance between wires (Dx), for different number of wires
Dx (m)
380
heating power from the wires (70 W m2 2) was chosen so that, together with the heat flux boundary condition at the skin (4.1 W m2 2), one obtains at the skin an average temperature of 25.58C). The environmental conditions of scenario I were considered for this purpose (air temperature of 2 368C, air velocity of 16.7 m s2 1). As can be seen in Figure 3, the temperature profile flattens (i.e. the heating becomes more homogeneous) as the number of wires increases. For the conditions considered here (total power: 70 W m2 2), it was found that the heating wires should dist approximately 6-7 mm to assure that the temperature along the lining does not vary more than 38C. Although smaller distances would assure flatter temperature profiles, that was considered unpractical from the manufacture point of view. The width of the simulation domain mentioned in Table II (3 mm) was defined based on these results (i.e. separation between wires of 6-7 mm). 4.2.2 Heat losses for several climatic conditions. The heat fluxes through the glove plus the heating multilayer, for each of the environmental scenarios of Table I, are shown in Figure 4(a), whereas the corresponding thermal resistances are shown in Figure 4(b). These analyses were done considering a constant skin temperature of 25.58C and no heat generation at the heating wires (see Section 3.2.2 for details). Owing to the steady-state nature of the simulations, the conductive flow through the glove equals the convective plus the radiant flows at the glove outer
Thermal Resistance (°C•m–2•W–1)
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Equivalent (Conv. + radiat.)
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0.6 0.4 0.2
4%
13%
4%
13%
0 I
II
III (b)
IV
surface (the convective and radiant resistances are parallel but in series with the conductive resistance). Moreover, depending on the environmental scenario, the conductive resistance accounts for 87-96 per cent of the total existing resistance (0.81-0.90 K m2 W2 1). This is why a 17-fold decrease in the air velocity (e.g. scenarios I and II or III and IV) results in less than 10 per cent decrease in the total heat loss from the glove. Owing to different convective losses, the temperature of the gloves external surface is higher for the less windy scenarios (II and IV), which accounts for the higher radiant heat losses observed (when compared to the similar but more windy scenarios, i.e. I and III, respectively). Nevertheless, the convective heat losses are 1.5-9.5-fold higher than the radiant heat losses observed. 4.2.3 Influence of surface emissivity. Metallisation surface treatments are known to offer different materials infrared reflective capacity and low radiant heat losses. In order to evaluate the relevancy of such treatments in the system under study, a series of parametric simulations were performed, in which the emissivity of the surfaces in question (either the glove outer surface or the skin-facing lining) was changed gradually from 0.95 to 0.05 (approaching the emissivity of aluminium foil). These simulations where conducted considering a constant skin temperature of 25.58C and no radiant sources other than the glove itself (so the effect of the heat gains from the sun was discarded in these analyses). Figure 5(a) and (b) shows the results of the mentioned simulations for environmental scenarios I and IV, regarding changes in the emissivity of the glove outer surface. There is a decrease in the radiant heat loss and (accordingly) an increase in the temperature of the glove external surface as the emissivity decreases. The escalation of the glove external temperature is accompanied by the corresponding increase of the convective heat loss, although to a lesser extent than the change in the radiant component. This produces an overall decrease in the total heat loss from the glove, reaching, however, no more than 7 per cent. These results indicate that, in the absence of any other radiant sources than the alpinist himself (i.e. in the absence of solar and atmospheric radiation), it is advantageous to use a low-emissivity cover over the gloves (or other body region) as this will reduce slightly the total heat loss. Such an advantage can be particularly relevant during the night when the effective sky temperature decreases sharply (increasing the relevancy of the effect of the radiant heat loss (Cengel, 2002)). However, during a daylight mountain activity, there is enough solar and atmospheric radiation to clearly overcome
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–33.3
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A mitt heating multilayer
Figure 5. Heat fluxes and temperature of the glove outer surface versus emissivity of the glove outer surface for (a) scenario I (2368C, 16.7 m s2 1) and (b) scenario IV (2198C, 1 m s2 1);
80 60
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Heat Flux (W•m–2)
Figure 6. Heat fluxes (across the air layer between skin and lining) and lining temperature versus emissivity of the skin-facing lining surface for scenario IV (2 198C, 1 m s2 1), considering air layer thickness of (a) 102 3 m and (b) 102 2 m
T (°C)
382
the aforementioned effect, which, ultimately, advises against the use of low-emissivity coverings in such conditions (see the Appendix for details). The effect of metallisation of the skin-facing lining was also studied as there is an increasing trend towards the use of such solutions in apparel industry. This was done for the environmental conditions of scenario IV (for which the radiant flux is more important in relative terms) and considering conductive and radiant heat exchange between the skin (1 ¼ 0.98) and the lining, for air layers thicknesses of 102 3 and 102 2 m. For these simulations, radiant heat loss was also considered at the glove outer surface based on an emissivity of 0.92. In these analyses, the emissivity of the lining was gradually changed from 0.95 to 0.05, while registering the corresponding heat fluxes for every particular emissivity. The obtained results are shown in Figure 6. When the emissivity of the lining decreases (thus increasing its reflectivity), there is a decrease in both the net radiant heat flux and the lining temperature. There is however an increase in the conductive flux across the air layer. This is obviously related to the decrease in the lining temperature (which augments the temperature gradient between the skin and the lining). The opposing variation of the radiant and conductive fluxes, for decreasing lining emissivity, results in an overall slight decrease in the total flux across the glove. The extent of this effect escalates with increasing air layer thickness since it is obviously related to the augmentation of the temperature difference between the opposing surfaces (e.g. when the lining emissivity decreased from 0.95 to 0.05, the total heat flux across the glove decreased by 8 per cent for an air layer thickness of 102 3 m and by 36 per cent for an air layer thickness of 102 2 m, respectively). These results highlight the clear benefit associated to the inclusion of low-emissivity (infrared reflective) internal surfaces in the clothing apparel. However, it should be stressed that this effect is only relevant if air layers/gaps between skin and the reflective surfaces do exist. Furthermore, the results highlight the shift between conduction and radiation heat transfer occurring when the emissivity of the surfaces exchanging heat is altered. For that reason, further studies were developed in transient mode in order to fully understand the influence of changes in surface emissivity over the performance of the heating multilayer, during the cooling and heating phases. These analyses are described in Section 4.3.2.
Heat Flux (W•m–2)
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4.3 Transient results 4.3.1 Temperature curves and battery duration. Several transient simulations were performed in order to determine the optimal power of the heating multilayer. The mostand least-demanding environmental conditions were considered (i.e. scenarios I and IV). Convective and radiant (1 ¼ 0.92) heat losses were considered at the glove outer surface. Constant heat flux (4.1 W m2 2) was imposed at the lining (perfect contact between skin and lining was assumed). Figure 7 shows the variation of the heating wire temperature over time for power supplies of 75, 250 and 500 W m2 2 (where the m2 refers to surface area of the portion of skin considered in the simulation domain, in this case 0.003 m £ 0.001 m). Not surprisingly, the temperature curves are strongly dependent on the external environmental conditions and on the power of the heating multilayer. The harsher the environmental conditions, the steeper the temperature variations (Figure 7(a) and (c)). Moreover, the higher the power, the more pronounced its temperature oscillation, during both the heating and the cooling phases (Figure 7(b)). The latter derives from the steeper temperature profiles existing across the multilayer, for increasing heating power. This indicates that this parameter should be as low as possible (in order to favour homogeneous heating across the multilayer rather than more or less evident hot spots around the heating wires). Although a heating power of 75 W m2 2 appears sufficient for the milder scenario (Figure 7(c)), it results in an almost asymptotic temperature escalation for the harsher conditions (Figure 7(a)). This advises the use of higher heating powers (to produce less unsymmetrical heating/cooling curves and, therefore, average skin temperature more stable over time). For both scenarios, the remaining heating powers (250 and 500 W m2 2) produce heating periods shorter than the cooling ones (about 61-90 per cent). Considering that the heat flux imposed at the lining is under-predicted (as it is based on the metabolic rate of the hands), the real heating and cooling periods will be even shorter and longer, respectively. For that reason, it is advisable to use heating powers lower than those mentioned before, arguably in the range 125-250 W m2 2. In order to determine the adequate battery capacity, the average heating powered (Pavg) was calculated. This parameter was obtained by Pavg ¼ P · tON/(tON þ tOFF), where P is the heating power delivered to the multilayer and tON and tOFF are the duration of the heating and cooling phases, respectively. It is interesting to notice that, for a given environmental condition, similar average heating powers are obtained regardless of the chosen heating power (75, 250 and 500 W m2 2; for high heating power, the multilayer is in ON mode for short periods of time, leading to full compensation). This indicates that the heat loss from the mitt and, thus, the temperature of its outer surface, are practically independent of the chosen heating power. This is obviously a consequence of the high-conductive insulation provided by the glove and the fixed limits (temperature wise) of operation of its heating multilayer. The fact that the average power consumption of the heating system does not depend on the chosen heating power is very convenient as it enables its design independently of energy-related restrictions. For the two scenarios analysed here (I and IV), the average heating power is 44.6 and 70.7 W m2 2 (the average heating powers for the scenarios II and III are within these values). The battery capacity required for powering the heating multilayer depends obviously on the expected effect duration. Mountain climbers mention the summit
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27 75 W m–2 250 W m–2 500 W m–2
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20 t (s)
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Figure 7. Heating wire temperature over time, for heating powers of 75, 250 and 500 W m2 2, for (a) scenario I (2 368C, 16.7 m s2 1), time span of 800 s; (b) scenario I (2368C, 16.7 m s2 1), time span of 50 s; (c) scenario IV (2198C, 1 m s2 1)
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t (s) 75 W m–2
250 W m–2
500 W m–2
Note: All simulations based on a constant skin heat flux of 4.1Wm–2
attack can last up to 12-24 h (personal communication). With this figure in mind, one concludes that, for the conditions studied here, a 4 A h battery can assure up to 18-23 h of operation of the described heating multilayer: charge duration ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi : P avg =Resistance As already mentioned, due to the under-prediction in the hand heat flux, the real effect duration should be even longer than the mentioned 18-23 h which, ultimately, indicates
28
28
27
27
26
26
T (°C)
T (°C)
that the system described here should comply with the duration requirements mentioned by climbers. 4.3.2 Influence of the internal surface emissivity. Transient simulations were conducted in order to study the influence of changes in the emissivity of the skin-facing lining surface, over the performance of the heating multilayer, during the cooling and heating phases. The simulations focussed on the environmental conditions of scenario IV (for which the radiant flux is more important in relative terms) for a heating power of 250 W m2 2. Convective and radiant heat (1 ¼ 0.92) losses were considered at the glove outer surface. Both conductive and radiant heat exchange were considered between the skin (1 ¼ 0.98) and the lining (1 ¼ 0.05 and 1 ¼ 0.95), for two distinct air layers thicknesses (1 £ 102 3 m and 5 £ 102 3 m). At the skin, a constant heat flux was imposed as boundary condition (4.1 W m2 2). Figure 8 shows the variation of the skin and heating wire temperatures over time, for lining emissivities of 0.05 and 0.95, for air layer thicknesses of 1 £ 102 3 m and 5 £ 102 3 m (Figure 8(a) and (b)), respectively. As expected, the thermal resistance and inertia of the air layers dampens and delays the temperature oscillations of the heating wires. This effect escalates obviously with increasing air layer thickness (distance between skin and lining). For the thinner air layer (1 £ 102 3 m; Figure 8(a)), the skin temperature is practically independent of the lining emissivity. Indeed, the temperature and the amplitude of its oscillation over time, obtained with the lining emissivity of 0.05 and 0.95, are almost identical. This indicates that, for such a thin air layer (1 £ 102 3 m in thickness), the lining emissivity does not have a significant effect over the thermal performance of the heating multilayer. However, if the air layer is allowed to be thicker, e.g. 5 £ 102 3 m, the skin temperatures obtained with the different lining emissivities, do differ (Figure 8(b)). The results show that, for the tested conditions, the skin temperature obtained with the lower emissivity (0.05) is between 0.38C and 0.58C higher than that obtained with the higher emissivity (0.95). Moreover, they show that the oscillation (over time) of the skin temperature is less pronounced with the lining featuring the lower emissivity (0.48C versus 0.68C). These results indicate that the use of low-emissivity surfaces facing the
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t (s)
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wire, ε(lining) = 0.05
skin, ε(lining) = 0.05
wire, ε(lining) = 0.95
skin, ε(lining) = 0.95
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Figure 8. Skin and heating wire temperatures over time for lining emissivity of 0.05 and 0.95, for air layer thicknesses of (a) 1 £ 102 3 m and (b) 5 £ 102 3 m; heating power of 250 W m2 2 and environmental conditions of scenario IV (2198C, 1 m s2 1); constant skin heat flux of 4.1 W m2 2
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skin is beneficial for the performance of the heating system, provided relatively thick air layer/gaps are allowed to exist between the skin and the heating multilayer. Furthermore, given that the use of such surfaces reduces the total heat loss from the body when no electrical heating system is considered/present (as discussed in Section 4.2.3), such solution seems to have interesting potential for clothing apparel applications (heated or not). However, due attention must be given to its effects over other parameters relevant for comfort perceptions (e.g. water vapour resistance, moisture management, tactile sensation, etc.). 5. Conclusion A series of steady state and transient simulations were implemented using a FEM approach in order to study and optimise the thermal performance of a heating multilayer, for use inside an alpine-climbing mitt. Several issues were addressed, namely, the heat losses as a function of environmental conditions, the positioning of the heating wires, the power input to the heating system, the battery capacity requirements and the effect of the use of low-emissivity surfaces. These are shown to reduce the total heat loss through the mitt and increase the skin temperature during the transient operation of the heating multilayer. References Brajkovic, D., Ducharme, M.B. and Frim, J. (2001), “Relationship between body heat content and finger temperature during cold exposure”, Journal of Applied Physiology, Vol. 90 No. 6, pp. 2445-52. Cengel, Y.A. (2002), Heat Transfer: A Practical Approach, McGraw-Hill, London. Fiala, D., Lomas, K.J. and Stohrer, M. (1999), “A computer model of human thermoregulation for a wide range of environmental conditions: the passive system”, Journal of Applied Physiology, Vol. 87 No. 5, pp. 1957-72. Geng, Q., Holmer, I., Hartog, D.E.A., Havenith, G., Jay, O., Malchaire, J., Piette, A., Rintamaki, H. and Rissanen, S. (2006), “Temperature limit values for touching cold surfaces with the fingertip”, Ann. Occup. Hyg., Vol. 50 No. 8, pp. 851-62. Hambrey, M.J., Quincey, D.J., Glasser, N.F., Reynolds, J.M., Richardson, S.J. and Clemmens, S. (2008), “Sedimentological, geomorphological and dynamic context of debris-mantled glaciers, Mount Everest (Sagarmatha) region, Nepal”, Quaternary Science Reviews, Vol. 27 Nos 25/26, pp. 2361-89. Havenith, G., van de Linde, E.J. and Heus, R. (1992), “Pain, thermal sensation and cooling rates of hands while touching cold materials”, European Journal of Applied Physiology and Occupational Physiology, Vol. 65, pp. 43-51. Holmer, I. (2005), “Textiles for protection against cold?”, in Scott, R.A. (Ed.), Textiles for Protection, Woodhead, Cambridge. Huizenga, C., Hui, Z. and Arens, E. (2001), “A model of human physiology and comfort for assessing complex thermal environments”, Building and Environment, Vol. 36 No. 6, pp. 691-9. Kurazumi, Y., Tsuchikawa, T., Ishii, J., Fukagawa, K., Yamato, Y. and Matsubara, N. (2008), “Radiative and convective heat transfer coefficients of the human body in natural convection”, Building and Environment, Vol. 43 No. 12, pp. 2142-53. Lienhard IV, J.H. and Lienhard V, J.H. (2003), A Heat Transfer Textbook, Phlogiston Press, Cambridge, MA.
Ma¨kinen, H. (2005), “Fire fighters protective clothing?”, in Scott, R.A. (Ed.), Textiles for Protection, Woodhead, Cambridge. Mason, N.P. and Barry, P.W. (2007), “Altitude-related cough”, Pulmonary Pharmacology & Therapeutics, Vol. 20 No. 4, pp. 388-95. Raman, E.R. and Vanhuyse, V.J. (1975), “Temperature dependence of the circulation pattern in the upper extremities”, Journal of Physiololgy, Vol. 249, pp. 197-210. Salloum, M., Ghaddar, N. and Ghali, K. (2007), “A new transient bioheat model of the human body and its integration to clothing models”, International Journal of Thermal Sciences, Vol. 46 No. 4, pp. 371-84. Tanabe, S.-I., Kobayashi, K., Nakano, J., Ozeki, Y. and Konishi, M. (2002), “Evaluation of thermal comfort using combined multi-node thermoregulation (65MN) and radiation models and computational fluid dynamics (CFD)”, Energy and Buildings, Vol. 34 No. 6, pp. 637-46. West, J.B. (1996), “Prediction of barometric pressures at high altitudes with the use of model atmospheres”, Journal of Applied Physiology, Vol. 81 No. 4, pp. 1850-4. Appendix The net radiant heat flux (qnet) to a surface exposed to solar and atmospheric radiation can be computed by the following energy balance (Cengel, 2002): q_ net ¼ asolar Gsolar þ 1s T 4sky 2 T 4 where asolar is the solar absorptivity, Gsolar is the total solar irradiance (1,373 W m2 2), 1 is the emissivity of the surface at room temperature, a is the Stefan-Boltzmann constant (5.67 £ 102 8 W m2 2 K4), Tsky is the effective sky temperature (230-285 K (Cengel, 2002)) and T is the temperature of the surface exchanging radiant heat (in K). For a mitt with a low-emissivity outer surface (1 ¼ 0.05 and asolar ¼ 0.15, taken equal to those of aluminium foil (Cengel, 2002)), the net radiant heat flux can be as high as 200-215 W m2 2 (depending on the temperature of the glove outer surface and the effective sky temperature). This value can be even higher, if considering a mitt with no low-emissivity outer surface.
Corresponding author Tiago S. Mayor can be contacted at:
[email protected]
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IJCST 23,5
388 Received 10 August 2010 Accepted 7 October 2010
A new electro-mechanical technique for measurement of stress relaxation of polyester blended fabric with constant torsional strain Emadaldin Hezavehi Department of Textile Engineering, Islamic Azad University, Arak, Iran
Saeed Shaikhzadeh Najar Department of Textile Engineering, Amirkabir University of Technology, Tehran, Iran, and
P. Zolgharnein and Hamed Yahya Department of Textile Engineering, Islamic Azad University, Arak, Iran Abstract Purpose – The purpose of this paper is to analyze the stress-relaxation behavior of different woven fabrics under constant torsional strain in a wrinkled state. For this purpose, a new method for determination of stress-relaxation behavior of the fabric was used while keeping the torsional strain constant. Design/methodology/approach – In this study, the behavior of stress relaxation of fabric is examined with modification of wrinkle force tester sophisticated electro-mechanical method and fabricating a device which uses a computer and micro controller, with constant torsional strain by a rotational level of 9.1 turn/m in 2808, and in 300 s. Findings – The results depict that stress-relaxation percentage in fabric in weft alignment is more than warp alignment and the fabrics which tolerate more torsional force, possess less stress-relaxation percentages. In this way, with increasing polyester percentage in fabric the scale of stress-relaxation percentage decreases. Also, adoption of data derived from experiments with Maxwell model shows that the interlaced model is a suitable model for explaining the stress relaxation decline in fabric. Correlation coefficient of fabrics in weft alignment with Maxwell model is more than warp alignment. Practical implications – This study has practical implications in the clothing as well as in technical textiles areas. Originality/value – Knowing visco-elastic properties is very important. However, there is no information available to study the stress relaxation of woven fabrics under the combined influences of compression and constant torsional strains. Keywords Stress relaxation, Torsional strain, Rotational level, Woven fabric, Measurement, Polyesters, Fabric testing Paper type Research paper
International Journal of Clothing Science and Technology Vol. 23 No. 5, 2011 pp. 388-398 q Emerald Group Publishing Limited 0955-6222 DOI 10.1108/09556221111166310
1. Introduction In a stress-relaxation experiment, we can study the behavior of stress relaxation with constant strain, applied to material by time progress. When a stress is inserted (Morton and Hearl, 1962) on visco-elastic compound it shows time dependent change. When stress is omitted from the compound its does not return completely to initial form.
International Journal of Clothing Science and Technology
ISSN 0955-6222 Volume 23 Number 6 2011
International textile and clothing research register Editor-in-Chief George K. Stylios
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CONTENTS
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EDITORIAL ADVISORY BOARD Professor Jaffar Amirbayat Amirkabir University of Technology, Tehran, Iran Professor H.J. Barndt Philadelphia College of Textiles & Science, Philadelphia, USA Professor Mario De Araujo Minho University, Portugal Professor Dexiu Fan China Textile University, Shanghai, China Professor Jintu Fan Hong Kong Polytechnic University, Hong Kong Professor P. Grosberg Shankar College of Textile Technology and Fashion, Israel Professor Carl A. Lawrence University of Leeds, UK
Professor Trevor J. Little North Carolina State University, USA Professor David Lloyd University of Bradford, UK Professor Masako Niwa Nara Women’s University, Japan
Editorial advisory board
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Professor Isaac Porat School of Textiles, University of Manchester, UK Professor Ron Postle The University of New South Wales, Australia Professor Rosham Shishoo Swedish Institute for Fibre and Polymer Research, Mo¨lndal, Sweden Professor Paul Taylor University of Newcastle, Newcastle upon Tyne, UK
Professor Gerald A.V. Leaf Heriot-Watt University (Hon), UK
International Journal of Clothing Science and Technology Vol. 23 No. 6, 2011 p. 3 # Emerald Group Publishing Limited 0955-6222
IJCST 23,6
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International Journal of Clothing Science and Technology Vol. 23 No. 6, 2011 pp. 4-5 q Emerald Group Publishing Limited 0955-6222
Editorial Research Excellence Framework 2014 British Universities and Colleges are preparing themselves for Ref 2014; Research Excellence Framework 2014. Institutions will be invited to make submission in 36 units of assessment (UOA), which are broadly speaking subject areas, through a precisely prescribed process, judged by experts, one for each UOA working under the guidelines of four main panels. Panels have prepared draft statements of theirs assessment criteria as we will see later, and members of these panels have already been appointed but it is said that additional assessors will also be appointed to extend the depth and breadth of expertise. The government organisations that overlook this process are hefce; the Higher Education Funding Council for England, the Scottish Funding Council for Scotland and the Higher Education Funding Council for Wales, the process is identical for the UK as a whole. Ref will make its judgments using three weighted criteria: (1) the quality of research outputs (65 per cent); (2) the much discussed research impact (20 per cent); and (3) the research environment (15 per cent). Hefce will fund four-star; world-leading research, but is unlikely to fund two-star; internationally recognised research and are yet to confirm whether or not they will fund three-star; internationally excellent research, as we will be discussing later. Ref 2014 is the seventh series of exercises conducted nationally to assess UK’s research quality in order to selectively distribute public funds for research by the four UK higher educational funding bodies. Ref is a new system for assessing research and it replaces the RAE; Research Assessment Exercise as previously called. Hefce have provides a statement which states that it aims to make “a major contribution to economic prosperity, national well being”, etc. This translates to most of us that research has to have direct relationship with money making, which has met with dissenting voices from eminent scientists and academics. Short-term research does not warrant excellence and certainly not new discovery, creation and fundamental breakthroughs. Further on hefce tries in a rather weak statement to explain its support for a selective funding system “that allocates our grant primarily by reference to robust assessment of research excellence”, how will a researcher without any track record in a non-funded institution pursue a new field of enquiry? It will be very difficult if not impossible. Another problem that this culture has been promoting, over the last few years, is that with the ever increasing funding cuts, line managers seek by implication short term external funding of research with obvious outputs and less risk. These compliance tools are excellent in distributing limited money and in sustaining research at best but not creating breakthroughs. The method of assessment is another huge problem which has to have quantitative and qualitative examination by “experts” of every submission, so that they are given a scoring mark “consisting of stars”. This star collecting process with three stars meaning national and four stars international standing is very important and it is allocated to
individual researchers by the experts. Paper publication in refereed journals with high impact factor is skewing quality within disciplines and benchmarking between disciplines. The best of four papers are usually the maximum submission assessed (along with explanations, narrative documentation of impact) for every academic. Many institutions are hiring experts to make these proposals as best as possible, under the criteria; there are a number of synergisms to strengthen these submissions and much tactical selection of academics and collaborations amongst academics creating critical mass of otherwise fragmented research topics. The big problem of course is the qualitative assessment in which there are very few experts that are capable of truly assessing the research. Experienced experts with depth and breadth are hard to come by and the funding councils have only a limited number of experts. Many stories have been told over the years of research project proposals being assessed as successful, but due to lack of funding invited to resubmit the following year and under a different panel of experts being rejected outright; I remember such an embarrassing case a few years ago by the Arts and Design Council. League tables by institution and subject with statistics and different interpretations are thriving again, and will be used to attract more funding and most importantly new students. Although the merit of assessment is a welcome proposition, research is difficult and we have to try to move away from mechanistic, superficial and quantitative comparisons and to try to allow the mind to be free and creative for important endeavours. Our subject area textile and clothing can belong to at least three UOA; materials, general engineering and arts and design. It can of course be submitted to all of them but institutions have to choose again how best to submit their research to secure funding. IJCST has recognised the need for promoting the diverse and important research in textiles and clothing and has been producing annually this Research Register to fulfil research assessment. It is not because in the last research assessment government has used our publication, but it provides a platform to register our research, giving due credit to those researchers that nevertheless are pioneering in original thinking, even if huge funding is not the case. This publication is also a collection of internationally based research in our subject area which is hard to come by in a single publication. I thank all registrars for your input and I look forward to seeing the production of another proud Research Register issue for 2011, promoting the importance of our discipline in the international research arena. In this last issue of 2011 our thanks go to our readers, to our authors, to our publisher, to IJCST’s Editorial Board and to many reviewers that help in the ever increasing demands of refereeing papers. To this end IJCST is now on line hoping to reduce waiting and queuing times and increasing of real time communication of information of paper status to our authors. George K. Stylios Editor-in-Chief
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Heriot-Watt University, EPS – Physics, Heriot-Watt University, Riccarton, Edinburgh, Scotland, UK, EH14 4AS. Tel: +00 44 131 451 3034; Fax: +00 44 131 451 3473; E-mail:
[email protected];
[email protected] Principal investigator(s): Professor J.I.B. Wilson and Dr R.R. Mather Research staff: Ms. A.H.N. Lind and Mr Adel Diyaf
Solar cells on textiles Other Partners: Academic
Industrial
None More being sought Project start date: 2001 Project end date: Ongoing Project budget: N/A Source of support: SMART:SCOTLAND Award to Power Textiles Limited Keywords: Thin-film silicon, Solar energy, Photovoltaics, Textile fabrics We are continuing to develop thin-film silicon solar cells on low cost textile substrates, using chemical vapour deposition (CVD) technology, based on previous thin-film diamond expertise. The CVD technology employs a proprietary microwave plasma system (developed at Heriot-Watt University) with silane/hydrogen/dopant gas mixtures, to produce the sequence of layers that forms the active part of these cells. We have shown that relatively low deposition temperatures of 200 C and the active plasma conditions of the process do not affect our textile substrates, whether of woven or non-woven construction. In addition, solutions have been determined to the problem of reliable electrical contacts over fibrous, flexible substrates, together with a conventional transparent conducting oxide as the top contact in the cell “sandwich” structure. Effective “first barrier” encapsulation may also use our deposition technology.
Aims and objectives Flexible solar cells for a variety of applications:, e.g. building facades, use in remote areas, emergency use in disaster relief, camping/leisure industry, portable chargers.
Deliverables Working prototype. Publications and outputs “Textiles make solar cells that are flexible and lightweight”, Technical Textiles International, December 2002, pp. 5-6.
“Solar textiles: production and distribution of electricity coming from solar radiation. Applications.” in Intelligent Textiles and Clothing, H. Mattila (Ed.), Woodhead Publishing Limited, Cambridge, 2006, pp. 202-17. “Microwave plasma deposited thin-film silicon for flexible devices on polyester”, paper presented at the 16th International Colloquium on Plasma Processes, Toulouse, June 2007. “Silicon deposition on polyester substrate”, poster at the 5th Technological Plasma Workshop, Belfast, December 2007. “Development of flexible solar cells on textiles”, paper presented at the Conference on Photovoltaics beyond Conventional Silicon, Dresden, April 2009. “Solar textiles”, in Polymer Electronics – A Flexible Technology, F. Gardiner and E. Carter (Eds), iSmithers, Shawbury, Shropshire, UK, 2009, pp. 87-94. “Solar textiles – the challenges”, paper presented at the Powering Technical Textiles Event, organised by the Materials KTN, Edinburgh, April 2010. “Solar textiles: the challenges”, paper presented at the Textile Institute Centenary Conference, Manchester, November 2010. “Raman spectroscopy of thin-film silicon on woven polyester”, submitted to Phys. Status Solidi A, July 2011.
Galashiels, Scotland, UK Heriot-Watt University, RIFleX, School of Textiles and Design, Netherdale, Galashiels TD1 3HF, UK. Tel: +44 1896 89 2135; Fax: +44 1896 75 8965; E-mail:
[email protected] Principal investigator(s): Prof. George K. Stylios Research staff: Liang Luo
Interactive wireless and smart fabrics for textiles and clothing Other Partners: Academic
Industrial
None None Project start date: September 2002 Project end date: December 2011 Project budget: £80,000 Source of support: Industry Keywords: Smart, Interactive, Textiles, Garment, Clothing, Sensors, Wireless The last few years have witnessed an increased interest in wearable technologies, smart fabrics and interactive garments. This has come about by certain technological innovations n the areas of sensor-based fabrics, micro devices, wire and wireless networks. In terms of textiles, most of current developments are towards the fashion markets and have resulted in glorifying garments as gimmicky gadgets. However, some efforts are also being directed in using the technology for improving the quality of life, or even for life saving purposes. Examples of such uses can be found in the military, healthcare, fire fighting, etc. This research project investigates new interdisciplinary
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technologies in fabrics, sensors and wireless computing, for the development of a prototype interactive garment for monitoring various functions of the wearer.
Aims and objectives
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The general aim of the project is to develop technologies for use in interactive garments, which can provide monitoring functions for various applications such as the clinical or healthcare sector. More specifically, objectives are: .
Develop suitable wireless sensors for various measurements, including ECG, temperature, breathing, skin conductivity, mobility and movement, humidity, positioning, etc.
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Develop a Personal Area Network and a Wireless Communication Centre.
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Optimise suitable wireless technologies such as Bluetooth to enable communication between sensors and a central processing unit. Conceptualise a smart multilayer fabric.
. .
Integrate technologies.
Deliverables .
wireless sensors for physiological and other measurements;
.
wireless communication centre for relaying information between sensors, wearers, central processing unit and Internet; and
.
conceptual multilayer fabric suitable for interactive garments.
Publications and outputs Stylios, G.K., Luo, L., “Investigating an interactive wireless textile system for SMART clothing”, paper presented at 1st International Textile Design and Engineering Conference (INTEDEC 2003), Fibrous Assemblies at the Design and Engineering Interface, Edinburgh, UK, September 22-24, 2003. Stylios, G.K., Luo, L., “The concept of interactive, wireless, smart fabrics for textiles and clothing”, paper presented at 4th International Conference, Innovation and Modelling of Clothing Engineering Processes – IMCEP 2003, Maribor, Slovenia, October 9-11, 2003. Stylios, G.K, Luo, L., “A SMART wireless vest system for patient rehabilitation”, paper presented at Wearable Electronic and Smart Textiles Seminar, Leeds, UK, June 11, 2004. Stylios, G.K., Luo, L., Chan, Y.Y.F., Lam Po Tang, S., “The concept of smart textiles at the design/technology interface”, paper presented at 5th International Istanbul Textile Conference, Recent Advances and Innovations in Textile and Clothing, Istanbul, Turkey, May 19-21, 2005.
Maribor, Slovenia University of Maribor, Faculty of Mechanical Engineering, Smetanova ulica 17, 2000 Maribor. Tel: +386 2 220-7500; Fax: +386 2 220-7990; E-mail:
[email protected] Principal investigator(s): Alenka Majcen Le Marechal Research staff: Tina Jericˇ, Darko Golob, Ernest Sˇimon, Nina Novak, Julija Valh Volmajer, Simona Vajnhandl
Water in industry, fit-for-use, sustainable water use in chemical, paper, textile and food industry Other Partners: Academic University of Madrid
Industrial Tekstina, Svilanit, Inotex, Enea, Vermicon, Voltea, Veolia, TNO Project end date: 31 May 2012
Project start date: 1 June 2008 Project budget: 14.8 Me Source of support: EC funding Keywords: Industrial Water, Fit-for use, Paper, Food, Chemistry, Textiles, Water treatment, Modelling, Water quality, Water quality definition
Sustainable water use in industry is the goal of AquaFit4Use, by a cross-sectorial, integrated approach. The overall objectives are: the development and implementation of new, reliable, cost-effective technologies, tools and methods for sustainable water supply, use and discharge in the main water consuming industries in order to significantly reduce water use, mitigate environmental impact and produce and apply water qualities in accordance with industrial own specifications (fit-for-use) from all possible sources, and contributing to a fargoing closure of the water cycle in a economical, sustainable and safe way while improving their product quality and process stability. The 4 pillars of the project are Industrial Water Fit-for-use, Integrated water resource management, Strong industrial participation and Cross-sectorial technologies and approach. Water fit-for-use is the basis for sustainable water use; the integrated approach a must. Tools will be developed to define and control water quality. The heart of AquaFit4Use however is the development of new cross-sectorial technologies, with a focus at biofouling and scaling prevention, the treatment of saline streams, disinfection and the removal of specific substances. By intensive co-operation between the industries, the knowledge and the technologies developed in this project will be broadly transferred and implemented. This AquaFit4Use project is based on the work of the Working group “Water in Industry” of the EU Water Platform WSSTP; 40% of the project partners of AquaFit4Use were involved in this working group. The expected impacts of AquaFit4Use are: A substantial reduction of fresh water needs (20 to 60%) and effluent discharge of industries; Integrating process technologies for further closing the water cycles; Improved process stability and product quality in the different sectors and strengthening the competitiveness of the European Water Industry.
Aims and objectives The overall objectives of the project are development of new, reliable, cost-effective technologies, tools and methods for sustainable water supply, use and discharge in the main European water consuming industries, in order to: . reduce fresh water needs (>30%); .
.
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mitigate environmental impact (5% less CO2 emissions and 20-40% less sludge disposal); produce and apply water qualities in accordance with industrial own specifications (fit-for-use) from all possible sources (5% increased productivity); and
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.
contribute to a far-going closure of the water cycle in an economical, sustainable and safe way (over 10% energy saving).
Aims: (1) water quality definition for processes, utilities and environment; (2) integrated modeling and control of industrial water systems; (3) practicable innovation in water treatment technologies; and (4) integration and validation of solutions.
Deliverables For public reports see: www.aquafit4use.eu Publications and outputs Majcen Le Marechal, Alenka, Vajnhandl, Simona, GOLOB, Darko. FP7 EU Project AquaFit4Use – Synergy of 4 Industrial Sectors with the Goal of Waste Water Recycling. AUTEX Res. J. (Print Ed.), September 2009, Vol. 9, No. 3, str. 99-103. Vajnhandl, Simona, Volmajer Valh, Julija. Kako resˇiti problematiko obarvanih tekstilnih odpadnih vod?. Kemija v sˇoli in druzˇbi, Mar. 2009, letn. 21, sˇt. 1, str. 24-29. Majcen Le Marechal, Alenka, Golob, Darko, Vajnhandl, Simona. Projekt sedmega okvirnega evropskega programa AquaFit4Use – sinergija sˇtirih industrijskih sektorjev za recikliranje odpadne vode ¼ FP7 EU project AquaFit4Use – synergy of 4 industrial sectors with the goal of waste water recycling. Tekstilec, 2009, Vol. 52, No. 4/6, str. 110-114, 2009, Vol. 52, No. 4/6, str. 115-119. Vajnhandl, Simona, Volmajer Valh, Julija. Predstavitev evropskega projekta AquaFit4use. Gospodarjenje z okoljem, Dec. 2010, Letn. 19, Sˇt. 76, str. 7-10. Vajnhandl, Simona, Majcen Le Marechal, Alenka, Jericˇ, Tina, Marcˇec, Monika. Advanced oxidation processes as decolouration and disinfection method. V: 10th Autex Conference, June 21-23, 2010, Vilnius, Lithuania. Proceedings of Autex 2010. Kaunas: Kaunas University of Technology, Faculty od Design and Technologies, Department of Textile Technology, 2010, 4f. Jericˇ, Tina, Mattioli, Davide, Grilli, Selene, Krapsˇ, Maja, Vajnhandl, Simona, Majcen Le Marechal, Alenka, Golob, Darko, Kobal, Lucija. Reuse of treated textile waste waters for dyeing process. V: 10th Autex Conference, June 21-23, 2010, Vilnius, Lithuania. Proceedings of Autex 2010. Kaunas: Kaunas University of Technology, Faculty OD Design and Technologies, Department of Textile Technology, 2010, 4 f. Jericˇ, Tina, Mattioli, Davide, Grilli, Selene, Krapsˇ, Maja, Vajnhandl, Simona, Majcen Le Marechal, Alenka, Golob, Darko, Kobal, Lucija. Ponovna uporaba obdelanih tekstilnih odpadnih vod za proces barvanja ¼ Reuse of treated textile wastewaters for dyeing process. V: Slovenski kemijski dnevi 2010, Maribor, 23. in 24. September 2010. (Maribor): FKKT, (2010), 9 str. Vajnhandl, Simona, Majcen Le Marechal, Alenka, Fakin, Darinka. Dyeing with treated wastewater. V: Adolphe, Dominique C. (ur.). 11th World Textile Conference AUTEX 2011, 8-10 June 2011, Mulhouse, France. Book of Proceedings: 150 Years of Research and Innovation in Textile Science. Mulhouse: Ecole Nationale Supe´rieure d’Inge´nieurs Sud-Alsace, 2011, Vol. 1, str. 162-165. Majcen Le Marechal, Alenka, Vajnhandl, Simona, Castagnet, S., Jossent, J. “The effect of ultrasound treatment on bacteria survival: V”, International Conference on Fibrous Products in Medical and Health Care, FiberMed11, June 28-30, 2011, Tampere Hall, Finland. “Fibrous products in medical and health care: papers and poster abstracts”, Tampere: University of Technology, 2011, 7 str. Volmajer Valh, Julija, Vajnhandl, Simona, Novak, Nina, Majcen Le Marechal, Alenka, “Primeri vkljucˇevanja slovenske tekstilne industrije v evropske projekte: V”, Simoncˇicˇ, Barbara (ur.), ForteTavcˇer, Petra (ur.). Raziskovalne prioritete Slovenske in Evropske tekstilne tehnolosˇke platforme v povezavi s 7. okvirnim programom EU: zbornik prispevkov. Ljubljana: Naravoslovnotehnisˇka fakulteta, Oddelek za tekstilstvo, 2008, str. 60-65.
Golob, Darko, Majcen Le Marechal, Alenka, Vajnhandl, Simona. “Water use reduction in textile industry – EU projetcs[!]: V”, Valant, Matjazˇ (ur.), Pirnat, Ursˇa (ur.). Slovenska konferenca o materialih in tehnologijah za trajnostni razvoj, Ajdovsˇcˇina, 11.-12. maj 2009. Knjiga povzetkov. Zbornik. V Novi Gorici: Zalozˇba Univerze, 2009, str. 78-83. Majcen Le Marechal, Alenka, Vajnhandl, Simona, Novak, Nina, “AquaFit4Use – cost and energy effective water treatment issues in textile sector: V”, 9th Autex Conference, May 26-28, 2009, Izmir, Turkey. Proceedings of the 9th Autex Conference. Izmir: Ege University, Engineering Faculty, Department of Textile Engineering, 2009, str. 892-894. Vajnhandl, Simona, Majcen Le Marechal, Alenka, “Predstavitev EU projekta 7.OP-AquaFit4Use: V”, Slovenski kemijski dnevi 2009, Maribor, 24. in 25. September 2009 (Maribor): FKKT, (2009), 3 str. Jericˇ, Tina, Mattioli, Davide, Grilli, Selene, Krapsˇ, Maja, Vajnhandl, Simona, Majcen Le Marechal, Alenka, Golob, Darko, Kobal, Lucija, Kolar, Matjazˇ. “Laboratory scale experiments for waste water reuse in textile processes: V”, VII ANQUE International Congress, 13-16 June 2010, Oviedo, Spain. Integral Water Cycle: present and future: “a shared commitment”: abstracts book. Madrid: Asociacio´n Nacional de Quı´micos de Espan˜a (ANQUE), 2010, str. 24. Snaidr, J., Beimfohr, C., Vajnhandl, Simona, Kobal, Lucija, Zupin, Natasˇa, Majcen Le Marechal, Alenka, “New insights into the microbiology of water streams in the textile industry: V”, VII ANQUE International Congress, 13-16 June 2010, Oviedo, Spain. Integral Water Cycle: present and future: “a shared commitment”: abstracts book. Madrid: Asociacio´n Nacional de Quı´micos de Espan˜a (ANQUE), 2010, str. 26-27. Mattioli, Davide, Grilli, Selene, Majcen Le Marechal, Alenka, Vajnhandl, Simona, “Examples of treatment strategies for reuse purposes in textile finishing SMEs: V”, VII ANQUE International Congress, 13-16 June 2010, Oviedo, Spain. Integral Water Cycle: Present and Future: “A Shared Commitment”: abstracts book. Madrid: Asociacio´n Nacional de Quı´micos de Espan˜a (ANQUE), 2010, str. 47-48. Vajnhandl, Simona, Golob, Darko, “Presentation of FP7 EU project AQUAFIT-FOR-USE: synergy of 4 industrial sectors with the goal of waste water recycling: lecture”, paper presented at The 11th European Meeting on Environmental Chemistry – EMEC 11, Portorozˇ, Slovenia, December 8-11, 2010 (Round table EU projects – good practice examples). Portorozˇ, 2010. Vajnhandl, Simona. Tekstilni sektor in AquaFit4Use ¼ Textile sector within AquaFit4Use: predavanje na predstavitvi rezultatov projekta AquaFit4Use “Dissemination of results; tailor-made water treatment technologies in textile companies, Tekstina, Ajdovsˇcˇina, 30 March 2011. Ajdovsˇcˇina, 2011.”
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Lieva Van Langenhove Research staff: Dr Ir. Vincent Nierstrasz (
[email protected])
NO BUG: novel release system and bio-based utilities for insect repellent textiles and garments Other Partners: Academic
Industrial
None Project start date: 15 October 2009
None Project end date: 14 October 2013
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Project budget: 523827e Source of support: European Commission, FP7-NMP 2008-SME-2 Keywords: N/A In several applications of professional textiles and clothes, mosquito repellency is an important issue. Two major problems arise: (1) repellents currently in use are harmful, resistance to conventional repellents increases; and (2) the lifetime of release systems is too short. Solving these two problems are the main goals of the No Bug project. Novel biorepellents will be considered and evaluated as well as two release systems (multilayer coating and textile bioaggregates) in order to repel mosquitoes causing malaria or dengue. Novel release concepts are multilayer coatings and in situ release of the active compounds. Targeted prototypes are textiles for health workers and bed nets (mosquitoes). The project will study what are the best conditions of use of the biorepellents and how to integrate them in the textile products. Testing, exploitation and dissemination will be an active part of the work.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Lieva Van Langenhove Research staff: Dr Simona Vasile (
[email protected])
Multirapier – multirapier technology for woven 3-D fabrics Other Partners: Academic None Project start date: 1 October 2009 Project budget: 101925 Source of support: IWT, Tetra Keywords: N/A
Industrial None Project end date: 30 September 2011
Market demand for three-dimensional fabrics has recently shown considerable growth. Although many of the 3-D fabrics used are knits, nonwovens or braids, woven 3-D structures can be a superior alternative for certain applications. Multirapier weaving is not yet fully exploited in the construction of woven 3-D fabrics, as most woven 3-D fabrics are presently produced on either looms with single weft insertion or on three-dimensional orthogonal weaving (e.g. 3WEAVEw of 3TEX). Multirapier technology, as applied in face-to-face weaving is both technologically and economically a good alternative for producing 3-D woven structures. Face-to-face looms are simultaneously forming multiple sheds and inserting multiple wefts and enable production of fabrics of up to 5m width, which is a major advantage in many technical markets. The conversion of face-to-face looms into use as 3-D looms is a very important milestone in the development of woven 3-D fabrics. A relatively large capacity of this type of weaving is available in Flanders but the traditional markets, such as upholstery and carpets are steeply declining. This IWTTETRA research project aims at converting existing technology to the technical textiles market. Decorative and technical fabric production techniques, however, are very different and conversion from one to the other requires technical modifications. Aramids, glass or carbon are often used in technical textiles and the correct use of these yarns is a further technological challenge. Their stress-strain behaviour, abrasion on machine parts will certainly involve machine adaptations. As machine modifications are expected, due to the fabric construction and raw material used, the consortium of the “Multirapier” project includes a face-to-face loom manufacturer. The project will furher benefit of the expertise of three RTD partners: the Departments of Textiles of Ghent University and the University College of Ghent as well as the Institut fu¨rTextiltechnik (ITA), Aachen (DE) as partner in the ERA-SME project with the same topic. SMEs and large companies from Belgium and Germany interested in woven 3-D fabrics as supplier/buyer are further completing the project consortium.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Karen De Clerck Research staff: Ing. Lieve Van Landuyt
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BIOCOT II: innovative strategies and assays for bioengineered cotton fibres with improved processing and enduser properties (Bayer) Other Partners: Academic None Project start date: 1 November 2009 Project budget: 36,996,989 Source of support: IWT Keywords: N/A
Industrial None Project end date: 31 October 2012
Cotton is the most important natural fibre: it represents about one third of the total world fibre consumption. Despite the intensive and long-lasting use of cotton fibre for textile applications, several steps of the cotton fibre processing are still inefficient or require large amounts of harsh chemicals. Most of the progress in improving these processes and adding new end-user characteristics to the fibre results from new or modified chemical and enzymatic treatments. Little progress is being made by improving the cotton fibre itself. The development of traits in cotton through genetic engineering is a lengthy and costly process that requires a careful selection of the target traits and approaches to be tested. This project focuses on the first step in this process and determines, within a 2-years time scope, what modifications of the cotton fibre are required to achieve improved functionality in 3 fields: (3) reactivity and dyeing; (4) intrinsic wrinkle resistance; and (5) flame retardancy. It is also important to see whether the introduced modifications do not affect the basic properties of the cotton fibre in a negative way. Therefore, after imparting changes to the fibres, tests were performed with currently available standard cotton tests to get an idea about the general characteristics of the fibres. The tests that are currently available are designed to be performed on fabrics and require at least 100 g to several kilos of material. Therefore, one of the challenges of this project is to develop and optimize small-scale tests which are applicable to extremely low amounts of fibre material.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Karen De Clerck (
[email protected]) Research staff: N/A
Advanced characterization of fibre morphology Other Partners: Academic None Project start date: N/A Project budget: N/A Source of support: N/A Keywords: N/A
Industrial None Project end date: N/A
Many of the current and future projects within the Department of Textiles involve some means of characterization of the fibre morphology. The morphology of fibres is in general very different from that of bulk polymer materials due to the high degree of orientation in the fibres. Also fibres often require separate dedicated sampling techniques due to their specific structure both at macro and at micro level. Therefore, a considerable effort has been spent within the Department of Textiles to develop new or optimise existent techniques for the characterization of fibre morphology. The analytical tools used are diverse with the focus being on thermal analysis (thermomechanical analysis, differential scanning calorimetry and modulated differential scanning calorimetry), spectroscopy (Fourier transform infrared spectroscopy and microscopy, DRIFTS, ATR, Fourier transform Raman spectroscopy and UV-VIS-NIR spectroscopy) as well as on microscopy (confocal laser scanning microscopy).
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium.
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Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Dr Philippe Westbroek (
[email protected]) Prof. Dr Ir. Karen De Clerck (
[email protected]) Research staff: N/A
Bio-based functional materials from engineered selfassembling peptides (EU-STREP-FP6-2003-NMP-TI-3) Other Partners: Academic None Project start date: N/A Project budget: N/A Source of support: N/A Keywords: N/A
Industrial None Project end date: N/A
This project aims at advancing the science and technology of sustainable and functional materials. Specifically it targets innovative nano-coatings for plastics, metals and ceramic objects, exploiting the self-assembly capabilities of short (25) amino-acid sequences ( ¼ peptides) in industrially relevant applications. Selfassembly is a method of spontaneous organization of molecules into higher order structures and defined by a set of boundary conditions (e.g. pH, T, etc.). This addresses the need for water-based coating solutions beyond plastics and explores principles of nature for supramolecular structure formation at various surfaces. These ambitions require a work programme addressing the challenges facing peptide-based nanocoatings in terms of their bio-technological engineering at a cost of 300ekg1 and their functional performance validation in selected self-assembled nano-coatings. The contribution of the Department of Textiles is situated on the level of producing peptide-functionalized nano-dimensioned fibres. This results in opening new application possibilities and insight in the behaviour of electrospinning methods during the electrospinning of (bio)polymers and subsequent coating procedures. An indirect impact of this development is the availability of functionalized nano-fibres for the textile industry. Ghent University delivered proof-of-principle for some peptide combinations. However, peptides are short chain molecules and therefore difficult to electrospin.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Karen De Clerck (
[email protected]) Dr Philippe Westbroek (
[email protected]) Research staff: Ir. Sander De Vrieze (
[email protected])
Nanofibres for filter applications: PhD work Other Partners: Academic None Project start date: N/A Project budget: N/A Source of support: N/A Keywords: N/A
Industrial None Project end date: N/A
Electrospinning is a booming technique to produce nonwoven structures from a polymer solution. These nonwoven structures consist of nanofibres. Nanofibres are fibres having a diameter between 1 and 1000 nanometers. Nanofibre nonwovens are nonwovens with very specific properties. These properties can be optimised by a thorough study of the process and the process parameters. The most important parameters are flow rate, used polymer, used solvent, applied voltage, mass percentage of polymer, distance between collector and surface, etc. The obtained structures are applicable in both air and water filtration. According to the parameters, different filters with different cut-off values are obtained. The cut-off value of a filter is the maximum size of the particles going through the filter. This value is directly linked with the diameter of the nanofibres and the tortuosity of the nonwoven. Different polymers are investigated for their electrospinnability and the possible application as a filter. Polymers like cellulose acetate, polysulfone, poly(ethylene-covinyl acetate) are tested. Cellulose acetate nanofibres seem to be the most promising polymers for further research.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/
Research register
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Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Karen De Clerck (
[email protected]) Research staff: O¨zgu¨r Ceylan (
[email protected])
Study of cotton fibres modified and developed for high-value applications: PhD work Other Partners: Academic None Project start date: N/A Project budget: N/A Source of support: N/A Keywords: N/A
Industrial None Project end date: N/A
Today’s cotton fibres have developed over the last centuries, with the fibres being longer and stronger than a few centuries ago. Many of these improvements can be attributed to continuous research and advanced breeding projects. Although quite some work has been done to optimise the mechanical properties, a possible improvement of the intrinsic chemical properties has been lacking behind. In this PhD work, it is investigated what aspects of the chemical behaviour of the cotton fibres would benefit from intrinsic improvements. This is done by relating the fibre properties to demanding end-user applications. Therefore, various methods are to be established to allow the characterisation of the aimed traits on small-scale fibrous samples and moreover relate them to large-scale end-user tests. This PhD is performed within the programme of the BIOCOT project.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium.
Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Dr Ir. Philippe Westbroek Research staff: Ir. Bert De Schoenmaker (
[email protected])
Natural fibre composites with a matrix of a renewable resource: PhD work Other Partners: Academic None Project start date: N/A Project budget: N/A Source of support: N/A Keywords: N/A
Industrial None Project end date: N/A
Composites have many advantages compared to other materials like metals and ceramics. The main advantage of high performance composites consists of their high specific strength and modulus. In order for the transportation industry to diminish its fuel consumption, cars, planes, etc. need to be lightened. This can be done by substituting metals by composites. Nowadays, about 25 weight percent of the airbus A380 consists of composites. The Boeing 787 Dreamliner is pushing the envelope with a total composite fraction of 50% by weight. The main research work of this PhD is to study the possibilities of using resins of renewable resources in engineering composites. Currently, most composites are made out of glass, carbon or aramid fibre and a fossil-based resin. Production, usage and disposal of such composites still have a great impact on the environment. It is better to use green composites, which have a smaller or no impact on the environment. So-called bio-composites are very often CO2-neutral and biodegradable. In this research work, flax is chosen as reinforcement. Possible resins are PLA, PHAs, natural epoxies, polyfurans, etc.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium.
Research register
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Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Lieva Van Langenhove Research staff: Prof. Dr Ir. Lieva Van Langenhove
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LIDWINE – multifunctionalized medical textiles for wound (e.g. decubitus) prevention and improved wound healing (“Lidwine”) Other Partners: Academic
Industrial
None None Project start date: 1 September 2006 Project end date: 31 August 2010 Project budget: 543.752e Source of support: European Commission – FP6 – IP – SME, FP6 – Integrated Projects – SME Keywords: Decubitus, Electrotherapy, Nanotechnology Several techniques will be developed to prevent decubitus and to stimulate its healing. Examples are passive and active antibacterial action, materials with reduced surface friction, massage and electrotherapy. The latter is the specific task of UGent. The materials will be developed in textile structures. The technologies used will be nanoparticles, encapsulation, brush coatings.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://texti les.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Lieva Van Langenhove Research staff: Prof. Dr Ir. Lieva Van Langenhove
COMPAS – computer based evaluation of aspect change of carpets by wear
Other Partners: Academic
Industrial
None None Project start date: 1 September 2006 Project end date: 31 August 2009 Project budget: 415.790,32e Source of support: IWT, VIS Keywords: Carpet wear, Evaluation, Image processing The aim of the project is to develop an objective method to be able to quantitatively measure carpet wear in a univocal and accurate way. To this end, images recorded with a colour CCD camera are being processed. New algorithms developed and in development in the framework of other projects will be tested for the evaluation of carpet wear. A considerable obstacle in the research regarding automatic evaluation of carpets is the lack of an extensive basic library of images of good as well as bad samples, and for a large variety of qualities. Establishing such a library is part of the project as well.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://texti les.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Lieva Van Langenhove Research staff: Prof. Dr Ir. Lieva Van Langenhove
Systex: coordination action for enhancing the breakthrough of intelligent textile systems (e-textiles and wearable microsystems) Other Partners: Academic None Project start date: 1 May 2008 Project budget: 800.000e
Industrial None Project end date: 30 April 2011
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Source of support: European Commission, FP7 – IST – Coordination and Support Action Keywords: Smart textiles, E-textiles, Wearable micro systems, Wearable electronics The project aims at creating a framework for current and future research activities, technology transfer and education in the area of wearable textile systems and e-textiles. This results in enhancing the cooperation between various entities that contribute to the development and commercialization of the textiles of the future. Technical and non technical information on relevant projects is collected.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://texti les.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr P. Kiekens Research staff: Ir. Els Van der Burght
Mudra learning network Other Partners: Academic
Industrial
None None Project start date: 1 February 2008 Project end date: 30 September 2009 Project budget: 43.394,73e Source of support: Vlaamse Gemeenschap, Samenwerkingsprojecten Vlaanderen/ Centraal – EN OOST-EUROPA Keywords: Textiles, Networking, Innovation MUDRA Learning Network is a network project of Flemish business and educational partners with their Croatian and Slovenian counterparts. The mentorship methodology offers the framework to a large group of SMEs and entrepreneurs to exchange expertise and to professionalise their management. The know-how from the universities strengthens the technological capacity and helps these companies to innovate. The target group: Textile and design-related companies
Aims and objectives Not available.
Research register
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://texti les.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Karen De Clerck Research staff: Prof. Dr Ir. Karen De Clerck
Research into new “sensor materials”: pH-sensitive colorants in textile materials Other Partners: Academic
Industrial
None None Project start date: 1 January 2009 Project end date: 31 December 2012 Project budget: 172.000e Source of support: Universiteit Gent, Bijzonder Onderzoeksfonds 2008 Keywords: pH-Sensitive dyes, Textiles, Spectroscopy, Microscopy The aim of the project is to obtain a better understanding of the interactions between pH-sensitive dyes and textiles. Both a macroscopic spectral analysis and a general microscopic evaluation will be performed. The dye-fiber interactions, the local distribution, the impulse sensitivity and spectral variations as a function of time and place will be looked at.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://texti les.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium.
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Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr P. Kiekens Research staff: Prof. Dr Paul KIEKENS; Prof. Dr Ir. K De Clerck
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Front – flame retardant on textile Other Partners: Academic
Industrial
None None Project start date: 1 November 2008 Project end date: 31 October 2010 Project budget: 141.000e Source of support: European Commission, FP7 Keywords: Textiles, Flame retardants, Nanoclays The project aim is to introduce finishing products in the European textile market, to produce textile fabrics resistant to fire with high performance and quality, as requested from evolution of legislation and from customer attention. Moreover, flame retardant finishing on textiles would achieve a multifunctional textile composition having not only fire resistance properties, but also an additional functionality. The project proposed by SMEs engaged in the field of polymer processing will contribute to meet needs and to strengthen the competitiveness of the EU manufacturers.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Karen De Clerck Research staff: Prof. Dr Ir. Karen De Clerck
Tapijtfabriek ALFA: water absorbing capacity of hollow fibres for filling yarn in artificial turf
Other Partners: Academic
Industrial
None None Project start date: 1 March 2008 Project end date: 28 February 2009 Project budget: 28.050e Source of support: IWT, KMO-Innovatiestudie Type 3 Keywords: Hollow fibre-water absorption – PP This project was conducted together with ALPHA-carpets. The capacity of water absorption of hollow PP-fibres was examined and improved, in order to optimize the quality of actual products such as bath maths and towels, but also to be able to bring new products on the market in the future. In the framework of this project, new methods have been written to quantify the water absorption and the drying of hollow fibres. More understanding was gained in the effect of the extrusion parameters on the fibre diameter and the capacity of water absorption of hollow fibres.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr P. Kiekens Research staff: Johanna Louwagie; Johanna Louwagie
TRITex: transfer of research and innovations in textiles Other Partners: Academic None Project start date: 1 January 2009 Project budget: 490.948,42e Source of support: INTERREG IV, EFRO Keywords: Research, Innovation, Textiles
Industrial None Project end date: 31 December 2012
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Ensait and Ghent University – Department of textiles want to establish common and complementary actions in order to strengthen the cross border cooperation. 4 actions are foreseen: multilateral research programmes, development of modules for distance learning, valorisation of digital training modules at industrial partners, organisation of seminars
Aims and objectives
26
Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr P. Kiekens Research staff: Dr Ir. Vincent Nierstrasz
BIOTIC: biotechnical functionalization of (bio)polymeric textile surfaces Other Partners: Academic
Industrial
None None Project start date: 1 April 2008 Project end date: 31 March 2010 Project budget: 223.288,66e Source of support: European Commission, People Marie Curie Actions (Intra-European Fellowships (IEF)) Keywords: Biotechnology, Enzymes, Grafting, Functionalisation, Surface modification, Textiles, Biopolymer, Polymer, Nano-structuring The aim is to functionalise textile materials using biotechnology. The research will be based on a concerted multi-disciplinary approach, thereby creating the possibility to produce functionalised materials with unique properties and functionalities. The research will focus on enzymatic grafting of functional groups on textile fibres, and specific enzymatic surface modification to obtain functional nano-structured surfaces.
Aims and objectives Not available.
Deliverables Not available.
Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
Research register
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr P. Kiekens Research staff: Ir. Els Van der Burght
SNAP – production of imidised styrene-malein acid (SMI) nanoparticles and surface interactions with different types of substrates (TOPCHIM) Other Partners: Academic
Industrial
None None Project start date: 1 September 2008 Project end date: 31 August 2011 Project budget: 249.525e Source of support: IWT, Onderzoeksproject Keywords: SMI nanoparticles, Imidisation, Surface properties This project aims for a better understanding of the chemistry and physics at the nano level of SMI nanoparticles, which are created by imidisation of copolymer styrene-maleic anhydride (SMA). The main aspect is to broaden insight into the physical characteristics of the nanoparticles such as shape, size and uniformity. Interaction with minerals and substances from renewable sources is another focus.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected]
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Principal investigator(s): Prof. Dr Ir. Lieva Van Langenhove Research staff: Ing. Johanna Louwagie; Ing. Johanna Louwagie
Bexco: arctic ropes – research into the dynamic behaviour of synthetic ropes in extremely cold circumstances
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Other Partners: Academic
Industrial
None None Project start date: 1 July 2008 Project end date: 31 October 2009 Project budget: 21.499,46e Source of support: IWT, KMO-Innovatiestudie Type 3 Keywords: Dynamic behaviour, Synthetic ropes The purpose of the study is to obtain insight in the phenomena that occur in frozen ropes that are under cyclic load an in the effect of the phenomena on their mechanical properties, fatigue and life span of the rope. The influence of ice will be studied on the macro- and microscopic level on ropes after cyclic loading in frozen conditions.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Lieva Van Langenhove Research staff: Simona Vasile
NIRIS: new insertion rules for a new insertion system (Picanol) Other Partners: Academic
Industrial
None None Project start date: 1 December 2008 Project end date: 30 November 2011 Project budget: 840.8 13,28e Source of support: IWT, Onderzoeksproject
Keywords: Weft preparation system, Air jet loom, Speed increase The aim of this project is to ultimately bring a new weft preparation system on the market. This should allow to insert the weft yarn faster on an air jet loom. In concrete figures, a speed increase on the loom of 10 to 15% is set as goal.
Aims and objectives
29
Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Karen De Clerck Research staff: Dr Philippe Westbroek
Advanced water filtration with nanofibres (Hogeschool West-Vlaanderen) Other Partners: Academic
Research register
Industrial
None None Project start date: 1 October 2008 Project end date: 30 September 2010 Project budget: 103.000e Source of support: IWT, TETRA-fonds Keywords: Waterfiltration, Nanofibers, MBR The goal of the project is the evaluation of nanofiber nonwovens produced by electrospinning for usage in advanced waterfiltration. This project is a continuation of a previous project around nanofibers. The focus is put on the research in the MBR-technology.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
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Zwijnaarde (Gent), Belgium Ghent University, Department of Textiles, Technologiepark 907, B-9052 Zwijnaarde (Gent), Belgium. Tel: +32 9 264 57 35; Fax: +32 9 264 58 46; E-mail:
[email protected] Principal investigator(s): Prof. Dr Ir. Lieva Van langenhove; Prof. Vanfleteren, Prof. Leman Research staff: Hertleer Carla; Hertleer Carla
UGent mobile textiles: a travelling compact, attractive and interactive platform demonstrating the multidisciplinary research at Ghent University that contributes to the textiles of the future Other Partners: Academic
Industrial
None None Project start date: 1 January 2009 Project end date: 31 December 2011 Project budget: 95.100e Source of support: Universiteit Gent, Werkgroep Wetenschapscommunicatie En-Popularisering: Projecten Wetenschap en Maatschappij Keywords: Smart textiles, Demonstrators, Textile antennas, Music, Stretchable electronics Textiles of the future are smart. This emerging research area has a large economical potential and a huge social relevancy. Four departments of Ghent University join forces to develop demonstrators that exhibit research on smart textiles at UGent. In a mobile stand, the visitor is given the opportunity to acquaint with these new technologies.
Aims and objectives Not available.
Deliverables Not available. Publications and outputs See https://biblio.ugent.be/input?func ¼ search; http://textiles.ugent.be/docs/AnnualReports/2008.pdf
Sliven, Bulgaria College of Sliven (TU – Sofia), College of Sliven, 59 “Bourgasko chaussee”, 8800 Sliven. Tel: +00359 44 667710; Fax: +00359 44 667505; E-mail:
[email protected]
Principal investigator(s): Ivelin Rahnev Research staff: 4 university lecturers from TU-Sofia, College of Sliven
Research register
Technology optimization of sirospun cotton yarns Other Partners: Academic
Industrial
Department of Textile Materials and “E.Miroglio” AD – Sliven, Design at the University of Maribo, www.emiroglio.com Slovenia Project start date: 1 May 2010 Project end date: 28 February 2011 Project budget: None Source of support: Indirectly Sponsored by “E.Miroglio” AD – Sliven Keywords: Sirospun, Cotton, Yarns Manufacturing of Sirospun cotton yarns is relatively rare phenomenon in the spinning technology. Principal difficulty derives from the small length of the cotton fibers, which do not manage to support the particular “spinning triangle” of the Sirospun technics. Another reason for the little by volume manufacturing of Sirospun cotton yarns is the mean trend to prepare weaving warps from single cotton yarns, which be sized in consequence. In the cases when the final product requires a fabric with resistance to wear increased, twisted threads are irreplaceable and the Sirospun cotton yarns become indispensables. Subject of the present investigation is a single ring-spun yarn, from cotton fibers, produced by the Sirospun method. Project includes following stages: (1) preliminary computations concerning the fibrous composition and the torsion structure of the yarn; (2) study of the technology capacity of a carded spinning mill for cotton ring-spun yarn; (3) planning and carrying out an experiment to receive cotton Sirospun yarns; (4) tests of the samples and laboratory data treatment; and (5) determining of the optimum machine adjustments to produce cotton Sirospun yarns with properties desired. Fibrous composition of the threads designed – Tt 202, 100-Cotton, Sirospun; consists of middle-length cotton with fineness Tt 1.67 dtex and staple length – 34.0 mm. Machine equipment to carry out the experimental work is a carding line to process cotton and cotton-type fibrous materials. Single yarns are received on ring spinning frame “Marzoli NSF2”. Mean factors of the technology optimization are the machine adjustments of the distance between the roving spins in the drafting zone and the spinning twists. Purpose of the threads designed is the weaving warp, so, their inherent properties are described by the mechanical resistance at extension, the general irregularity and the stability of the peripheral layer. In order to determine these qualitative indicators, the samples will pass through dynamometric tests, structural analysis and microscopic visualization. After statistical treatment of the laboratory data and regressive analysis, the technic file of the technology prototype will be conceived.
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Aims and objectives Goal of the present work is the obtaining of cotton Sirospun yarn with linear density 202, 100-Cotton with optimum properties, destined to weaving warp threads. Attaining this aim passes the following tasks: .
methodology investigation (fibrous raw materials, equipment capacity and previous results);
.
experimental work; and receiving of the optimization model and drawing up of a technic file of the linear textile product: Tt 202, 100-Cotton, Sirospun.
.
Deliverables Academic results consist in the investigation of the rheology properties and the structure of the cotton Sirospun yarns. University results consist in the formulation of final diploma projects and doctoral thesis. Practical results consist in the technic file to reproduce the cotton Sirospun yarn and the patent application. Publications and outputs For our university team this is the beginning of a perspective investigation work. Results of this thorough research on the stages of the project will be described in 3 autonomous publications. A part of them will be reported to the annual conferences of AUTEX, the second part will be represented to the local university seminars and the third part will be offered to newspapers specialized of textile industry and clothing.
Hong Kong, China The Hong Kong Polytechnic University, QT719, Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong. Tel: +852-27666470; Fax: +852-29542521; E-mail:
[email protected] Principal investigator(s): Prof. Tao Xiaoming Research staff: Zhu Bo, Yi Weijing, Li Qiao, Wang Yanming, Wang Fei, Li Mingjian, Li Ying, etc.
In-situ multi-parameter evaluation system for smart protective apparel under high-speed impact Other Partners: Academic The Hong Kong Polytechnic University
Industrial Shenzhen NanHua Electronic Technology Corporation Ltd; Joint Sensor Instruments (Hong Kong) Ltd; TAL Apparel Ltd
Project start date: 2 August 2010 Project end date: 31 July 2012 Project budget: HK$8,628,795 Source of support: Hong Kong Innovation and Technology Fund Keywords: Textiles/Clothing The modern society has an increasing demand for smart protective apparel against impact from contact sports, traffic, and ballistic force, etc. However, so far there has been no measuring and sensing technology available for flexible textile materials with large deformation. Based on the previous achievements by the applicants, the present project is aimed to develop a built-in and in-situ multi-parameter evaluation system to be integrated with protective apparel. By real-time obtaining and analysis of spatial and temporal distributions of strain and pressure inside protective apparel during high-speed impact loading, the system can provide information and intelligence to help train sportsmen and reduce possible injuries to human body, to timely detect injury on human body and wirelessly transmit the situation to related surgeons, and to evaluate performances of protective textiles and apparel. On one hand, the project targets developing a platform technology of smart protective apparel with a reasonable cost and ensured performance quality. On the other hand, the technology will also fill a gap in the field of high-speed impact protection as well as corresponding product market.
Aims and objectives The aim is to develop a built-in and in-situ multi-parameter evaluation system for smart protective apparel to train sportsmen and reduce injuries to human body; to detect injury on human body and wirelessly transmit the information, thus to save time for preparation of surgery procedure; and to evaluate performance and optimize design of protective textiles for high-speed impact. The objectives are as follows: (1) to measure and confirm the dynamic response of the fabric strain and pressure sensors according to the requirement of high-speed impact applications; (2) to conduct mathematical modeling of the fabric sensors and the evaluation system according to the results of dynamic tests; (3) to explore and optimize the configuration, connection, and materials for the integration of the evaluation system with smart protective apparel; (4) to develop pilot fabrication technology and equipment for the evaluation system as well as smart protective apparel; (5) to establish testing protocols for the fabric sensors, the evaluation system, and the smart protective apparel; (6) to develop prototypes of the evaluation system, and make necessary modifications according to real impact test; (7) to design and construct prototypes of smart protective apparel with integrated evaluation system, and evaluate the related performances; and (8) to conduct data processing/analysis, and provide relevant information of impact, injury situation on human body, or technical specifications of protective apparel.
Deliverables Pilot fabrication technology and equipment for the smart protective apparel and the evaluation system:
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(1) Integration and packaging technology of the evaluation system for the smart protective apparel. (2) Testing protocol for the performances of the evaluation system and the smart protective apparel. (3) Application prototypes of smart protective apparel integrated with the evaluation system with acceptable performances and reasonable cost. (4) The methods of signal acquisition, storage, transmission and data analysis, as well as the evaluation methods of impact information, injury of human body, and performances of protective apparel. Publications and outputs Li, Q., Tao, X.M., Zhu, B., “Knitted stretchable interconnects for wearable electronics”. Proceedings of Fiber Society 2011 Spring Conference, Hong Kong, 23-25 May 2011. Yi, W.J., Wang, Y.Y., Wang, G.F., Tao, X.M., “Flexible and conductive silicone composites for pressure measurement”. Proceedings of Fiber Society 2011 Spring Conference, Hong Kong, 23-25 May 2011.
Lodz, Poland Technical University of Lodz, Faculty of Material Technologies and Textile Design, Zeromskiego Street 116 90-924 Lodz. Tel: +48 42 631 33 00 (02); Fax: +48 42 636 48 23; E-mail:
[email protected],
[email protected] Principal investigator(s): Ryszard Korycki, PhD, D.Sc – Coordinator, Prof. Izabella Krucin´ska, PhD, DSc, Prof. Krzysztof Gniotek, PhD, DSc, Prof. Iwona Frydrych, PhD, DSc, Prof. Krzysztof Kowalski, PhD, DSc Research staff: Dr inz˙. Włodzimierz Konecki, Dr inz˙. Sławomir Sztajnowski, Dr inz˙. Agnieszka Komisarczyk, Dr inz˙. Jacek Rutkowski, Dr inz˙. Jacek Les´nikowski, Dr inz˙. Michał Frydrysiak, Dr inz˙. Agnieszka Cichocka, Dr inz˙. Renata Krasowska, Dr inz˙. Bogdan Włodarczyk, Dr inz˙. Jolanta Ledwon´, Mgr inz˙. Łukasz Te˘siorowski, Mgr inz˙. Grzegorz Bednarski
Investment project: development of research infrastructure of innovative techniques and technologies of textile-clothing industry “CLO-2IN-TEX” Other Partners: Academic
Industrial
None None Project start date: 1 September 2009 Project end date: 31 March 2012 Project budget: 20 488 527,18 PLN (5 316 281,46 EUR) Source of support: 85% European funding, 15% National funding Keywords: Research infrastructure, Laboratory, Textile, Clothing technology, Modelling The project is realized by Technical university of Lodz, Faculty of Material Technologies and Textile Design by the following Departments: Department of Clothing Technology,
Department of Automation of Textile Processes, Department of Technology and Structure od Knitted Products, Department of Fibre Physics and Textile Metrology. The followin laboratories and workrooms will be equipped with new research devices: (1) technological workroom I; (2) technological workroom II; (3) workroom of clothing design; (4) workroom of testing clothes usability; (5) laboratory of knitting machines; (6) laboratory of sewing machines; (7) research laboratory; (8) laboratory of ballistic research; (9) laboratory A of Advanced Technologies Centre PRO HUMANO TEX: . . . . .
workroom of nanotechnology of textiles; workroom of surface engineering of textile materials; workroom of textronics; workroom of fibrous micro and nano structure analysis; workroom of specialized microscopy;
workroom of structural research; and workroom of surface engineering of textile materials. (10) laboratory of textile metrology: . workroom of chemical research; . .
.
workroom of mechanical research; and
workroom of electrical properties of textiles. The following laboratories and workrooms will be created: .
. . .
thermal processing workroom; workroom of adhesive connections; laboratory od numerically controlled flat knitting machines; and
workroom of analysis of comfort created by clothes. The rooms where the machines will be situated will first be modernized. Laboratory of textile metrology will undergo accreditation procedure. .
Aims and objectives The main (strategic) aim of the project is development of research infrastructure of the Faculty of Material Technoogies and Textile Design of Technical University of Lodz, which is an institution of high research potential. The infrastructure purchased during the project will enable carrying out advanced research for the textile-clothing companies and will improve the competitiveness of polish science. The realization of the project will also strengthen cooperation between the research institutions, and enterprises and improve the position of the polish textile-clothing companies functioning in the conditions of Single European Market. The project will also improve the position of the research sector in the economy, especially in the areas regarded as prior for the social and economic development.
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Deliverables .
modernized laboratories – 1;
.
newly created laboratories – 6;
.
new, specialized workplaces connected with the new research infrastructure – 1;
.
purchased research equipment – 147;
.
modernized area – 1408,42m2;
.
newly created workrooms – 3;
.
modernized workrooms – 14;
.
articles published in newspapers with impact factor – 18;
.
companies benefiting from the offer of the modernized laboratories – 16;
.
obtained accreditations – 1;
.
research and targeted projects realized on the basis of the new infrastructure – 8;
.
international projects realized on the basis of the new infrastructure – 5;
.
research institutes benefiting from the offer of the new infrastructure – 7;
.
agreements for providing services on the basis of the new infrastructure – 23;
.
staff members participating in trainings concerning operating the new infrastructure – 20;
.
scientists employed to operate the newly bought research infrastructure – 17;
.
technical staff members employed to operate the new research infrastructure – 7;
.
scientists using the new research infrastructure – 36; and
.
students using the new research infrastructure – 40.
Publications and outputs Korycki Ryszard, Wie˘zowska Anna, “Modelling of the temperature field within knitted fur fabrics”. Fibres and Textiles in Eastern Europe 2011, Vol. 19 Nr 1(84) pp. 55-9. Korycki Ryszard, Krasowska Renata, “Lockstitch tightening model with mechanical and thermal loads”. Fibres and Textiles in Eastern Europe 2011, Vol. 19 Nr 2(85), pp. 47-53. Korycki Ryszard, “Modeling of transient heat transfer within bounded seams”. Przyje˘ty do druku, po recenzjach, Fibres and Textiles in Eastern Europe, 2011 Vol. 19(87) Nr 4. Frydrych I., Jurczak K., Bartkowiak G., Cichocka A., “Comparison of physiological comfort of T-shirts with and without PCM content”, Fibres & Textiles in Eastern Europe (submitted in May 2011). Te˘siorowski, Ł., Frydrysiak, M., Zie˘ba, J., “Wireless transmission of breath rhythm in textronic system”, paper presented at 7th International Conference Texsci 2010, Liberec, Czech Republik Te˘siorowski, Ł., Gniotek, K., Frydrysiak, M., Zie˘ba J., “Wireless system of monitoring human’s temperature”, paper presented at 7th International Conference Texsci 2010, Liberec, Czech Republic. Te˘siorowski, Ł., Les´nikowski, J., Frydrysiak, M., Zie˘ba, J., Tokarska, M., “Inductive coupling for transmission of energy and measurement data”, paper presented at 17th International Conference Structure and Structural Mechanics of Textiles, Liberec 2010, Czech Republik. Gniotek, K., Frydrysiak, M., Zie˘ba, J., Tokarska, M., “Innovative textile electrodes for electrostimulation of muscles, medical measurement and applications”, paper presented at MeMeA 2011 Conference, Italy.
Frydrysiak, M., Ziegler, S., Gniotek, K., Zie˘ba, J., “The modelling of textile layers in textronic clothing”, paper presented at 5th International textile, Clothing & Design Conference – Magic World of Textiles, Dubrovnik, Croatia. Zie˘ba, J., Frydrysiak, M., “Textronic sensors of respiratory rhythm frequency”, paper presented at 5th International textile, Clothing & Design Conference – Magic World of Textiles, Dubrovnik, Croatia. Tokarska, M., Zie˘ba, J., Frydrysiak, M., Gniotek, K., “The concept of the forearm’s phantom to the research of textile electrodes”, paper presented at 17th International Conference Structure and Structural Mechanics of Textiles, Liberec 2010, Czech Republik. Zie˘ba, J., Frydrysiak, M., Tokarska, M., “The initial research of textile electrode to electrostimulation”, paper presented at 7th International Conference Texsci 2010, Liberec, Czech Republic. Zie˘ba, J., Frydrysiak, M., “The method of human frequency breathing measurement by textronic sensors”, paper presented at 7th International Conference Texsci 2010, Liberec, Czech Republic. Zie˘ba, J., Frydrysiak, M., Gniotek, K., “Textronic contact junction”, paper presented at 7th International Conference Texsci 2010, Liberec, Czech Republic. Korycki Ryszard, “Modeling of coupled heat and mass transfer during drying”, Proceedings of Autex 2010, 10th World Textile Conference, 21-23 June 2010 Vilnius, Lithuania, publication on the optical disc (CD-ROM). Korycki Ryszard and Krasowska Renata, “Modeling of dynamics of lockstitch tightening”, Proceedings of Autex 2010, 10th World Textile Conference, 21-23 June 2010 Vilnius, Lithuania, publication on the optical disc (CD-ROM). Korycki Ryszard, “Modeling of heat transfer within the wet diving suit: 1960-2010”, Faculty of Textile Engineering, Technical University of Liberec, Book of Selected Lectures. Texsci’10, 7th International Conference Textile Science 2010, September 6-8, 2010, Liberec, Czech Republic, pp. 153-60. Korycki Ryszard, “Shape optimization in mass diffusion within composite dressing: 1960-2010”, Faculty of Textile Engineering, Technical University of Liberec. Book of Selected Lectures, Texsci’10, 7th International Conference Textile Science 2010, September 6-8, 2010, Liberec, Czech Republic. Publication on the optical disc (CD-ROM). Korycki Ryszard, “Coupled mass and energy transfer within textronic structures: 1960-2010”, Faculty of Textile Engineering, Technical University of Liberec. Book of Selected Lectures, Texsci’10, 7th International Conference Textile Science 2010, September 6-8, 2010. Liberec, Czech Republic, Publication on the optical disc (CD-ROM). Korycki Ryszard, “Sensitivity oriented shape optimization and identification during opposite coupled diffusion within composites”, W: 19th International Conference on Computer Methods in Mechanics, 9-12 May, 2011, Warsaw, Poland. Korycki Ryszard and Szafranska Halina, “Modeling of heat transfer within clothing laminates”, Proceedings of Autex 2011, 11th World Textile Conference, 8-10 June 2011, Mulhouse, France. Korycki Ryszard, “Coupled heat and mass transfer within textronic structures”, Proceedings of Autex 2011, 11th World Textile Conference, 8-10 June 2011, Mulhouse, France.
Lodz, Poland Technical University of Lodz, Faculty of Material Technologies and Textile Design, Zeromskiego Street 116 90-924 Lodz. Tel: +48 42 631 33 17; Fax: +48 42 631 33 18; E-mail:
[email protected] Principal investigator(s): Prof. Izabella Krucin´ska, PhD, DSc Research staff: Prof. Krzysztof Dems, PhD, DSc, Prof. Krzysztof Kowalski, PhD, DSc, Włodzimierz Konecki, PhD, Piotr Szablewski, PhD, Jan Turant, PhD,
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Jolanta Ledwon´, PhD, Magdalena Kłonowska, PhD, Bogdan Włodarczyk, PhD, Andrzej Golczyk
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Development of a rapid configuration system for textile production machinery based on the physicel behaviour simulation of precision textile structures Other Partners: Academic
Industrial
Universitat Politecnica de Catalunya Spolsin, spol. s.r.o.; T.F.A. alfa, s.r.o.; (INTEXTER-UPC and KEMLG-UPC); Heimbach GmbH & CO KG; Gebr. Technical University of Liberec; Ro¨ders AG; Santoni Spa.; Deutsche Institute fu¨r Textil- und Informatica Textil S.L.; Faserforschung Denkendorf; Belgian Monitoring Systems, Bvba. Sa¨chsisches Textilforschungsinstitut e.V; Deutsche Institute fu¨r Textil- und Faserforschung Denkendorf Project start date: November 2008 Project end date: April 2012 Project budget: 237 318,00 EUR Source of support: 179 188,00 EUR Keywords: Rapid machine setting, Textile, Simulation, Physical behaviour of fabrics, Small batches, Online process control, Artificial intelligence, FEM models of textiles The textile industry faces important challenges regarding the production of new advanced textile products. It is not possible to define the characteristics and parameters of a given textile structure due to the difficulty of measuring them. This situation makes very difficult to configure the machines involved in the production of such textiles; the typical practices consists in manufacturing samples and through trial and error adjust the processing operations until the desired characteristics are achieved in the final product. With this procedure it is very expensive to match the designer’s idea with the final product. The production setup takes a long amount of time and efforts and increases the cost of the final product. This is especially critical when a company is trying to develop new technical textiles. The vast majority of the existing systems capable to simulate textile products are limited to the visual representation, without any kind of mechanical or physical evaluation of the properties of the textile structures. Of course, these tools do not take into account the configuration of the production machinery, so they are not capable of help in the setup of production machinery. Unlike these conventional design systems, the core of this proposal is to develop a virtual simulation system of the physical-mechanical properties of the textile structures oriented to the fast setup of the machines involved in the whole textile chain manufacturing process (yarns, woven fabrics, knit fabrics, needle-punch non-woven, hydro-tangled non-woven, and composite structures). This virtual construction system will allow the prediction of the multifunctional textile performance before the actual textile is manufactured allowing the settings of the production machines to be either an input or an output of the computation thus reducing dramatically the effortand cost to produce small batches or develop a new advanced technological textile.
Aims and objectives To overcome the described functionality limits of the currently available textile design systems, the objective of this proposal is to develop a simulation system for the physicalmechanical properties of the textile structures that enables the rapid manufacturing process configuration. The system will support the product development and production for all products in textile value-added chain (yarns, woven fabrics, knitware, and needle punch non-wovens). This virtual construction system will allow the performance prediction of multifunctional textiles before the starting to manufacture. Production machine settings will be both computations input an output. This will thus reduce dramatically the effort to produce small production lots and the process setting-up times (small or large lots). The project has therefore the following main objectives: .
Development of the simulation model of the physical properties of the basic structural units that compose the multifunctional textile structures. Mathematical models will be developed to simulate the behaviour of the 4 textile structures studied in this project (yarns, woven fabrics, knit fabrics and non-woven fabrics). Starting from their manufacturing parameters and machinery setup.
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Development of a finite elements simulation system to simulate the physical properties of the textile structures, based on the mathematical models developed for these textile structures.
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Development of an artificial-intelligence based simulation system for the physical properties of textile structures. This A.I. based simulation system will complement the results of the finite elements simulation system to fill in the gaps where the finite elements system cannot simulate. The composition of both systems will generate a very strong and robust composed system that will generate precise results.
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Implementation of the 2 simulation models (finite elements and A.I.) in one single composed simulation system that will be the core of the MODSIMtex software package which is the final milestone of the project.
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Integration of the simulation system results into the manufacturing process through the adequate interfaces, to produce real multifunctional textiles using the parameters established during the design process with the simulation software MODSIMtex. This way the design phase and the manufacturing phase are seamlessly integrated for the first time in the textile industry. This integrated software package MODSIMtex will be focused to the final user, and it will be the final deliverable of the project. The software will be divided in many modules oriented to each kind of machine inside the process, in order to be adapted specifically to it.
Deliverables Report about technical definitions and requirements of the simulation systems, including data formats for data exchange; programming languages, tools and destination platforms, enumeration of input parameters and output parameters for each process in focus:
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(1) Yarn simulation model for yarns used in technical applications (high module multifilament, high module chemical fibres, etc.). Range of yarn counts to be studied will depend on the applications of the designed yarns. (2) Validation report of the yarn simulation model. (3) Simulation model for the basic structural units in woven fabrics (basic structural units will be the plain repeat, “sage” repeat and satin repeat, composed of the same yarns foreseen for D2). (4) Simulation model for the basic structural units in knit fabrics (basic structural units will be the jersey and double jersey, composed of the same yarns foreseen for D2). (5) Simulation model for the basic structural units in non-woven fabrics (needlepunch non-woven). (6) Measurement system for the properties of the basic structural units in fabrics, elaborated with the same materials established in D2 and the manufacturing parameters established in D4-D6. (7) Innovation Level Assessment Report of the Development Phase: Comparison of the current development results with other research and development activities Recommendations for the Project Co-ordination Committee. (8) Innovation Level Assessment Report of the Implementation Phase: Implementation-centered comparison of the implementation results with other systems, especially focusing on product usability, its performance in practice and integration capabilities.Recommendations for the Project Co-ordination committee. (9) Validation report of the fabric simulation models. (10) Report about technical definition of the artificial intelligence system. (11) Experimental software package for A.I. system development. Must be available in a support ready to be installed, featuring development advanced interface; the target platform and O.S. will be decided inside the WP 1. (12) Simulation model for fabrics using finite element methods. (13) Experimental software package for finite element fabric simulation. Must be available in CDROM support, It will not include graphical design interface, because it will be imported from third party dedicated application; its interface will be focused to the system developer (not user friendly). (14) Analogy map between the models for yarn simulation (finite element and A.I.). (15) Analogy map between the models for woven fabrics simulation (finite element and A.I.). (16) Analogy map between the models for knit fabrics simulation (finite element and A.I.). (17) Analogy map between the models for non-woven fabrics simulation (finite element and A.I.). (18) Report about results of the A.I. system validation and training. (19) Experimental software package for composed simulation of fabrics (finite element, artificial intelligence). Support in CDROM.It will include a first approach to the graphical interface in both input and output. This interface will also be focused to the system developer (not user friendly). The target O.S. and programming language and tool will be decided inside the WP 1.
(20) Software package for the production of multifunctional precision yarns in a commercial spinning machine with pre-determined properties through the simulation system, targeted to final user. It must feature user-friendly graphical interface for both parameter input and results. Developing tool and O.S. will depend on the specifications of the WP1. (21) Software package for the production of precision multifunctional woven fabrics (priority for textiles developed for personal protection applications) in a commercial woven machine, with pre-determined properties through the simulation system, targeted to final user. Support: CDROM, featuring userfriendly graphical interface for both parameters input and results. The final running platform will be defined in the WP1. (22) Software package for the production of precision multifuncional knit fabrics (priority for high performance sport textiles applications) in a commercial knitting machine, with pre-determined properties through the simulation system, targeted to final user. Support: CDROM, featuring userfriendly graphical interface for both parameters input and results. The final running platform will be defined in the WP1. (23) Software package for the production of precision multifunctional non woven structures (priority for applications on barrier effects (acoustic, thermal and liquid), with pre-determined properties through the simulation system, targeted to final user. Support: CDROM, featuring user-friendly graphical interface for both parameters input and results. The final running platform will be defined in the WP1. (24) Software package for the production of precision non woven multifunctional non woven structure in a needle-punch machine for big applications (like paper machinery clothing), with pre-determined properties through the simulation system, targeted to final user. Support: CDROM, featuring userfriendly graphical interface for both parameters input and results. The final running platform will be defined in the WP1. (25) Software simulation module (plug-in) to be integrated in a textile CAD system, targeted to the final user (designer of multifunctional textile structures (smart textiles)). Must include an installation utility. Key features: Very user-friendly graphical interface (data input and results output). Optimized computation time (if needed). OS and platform will be defined in the WP1 and will depend onthe CAD application chosen (Linux or Windows). (26) Report about the validation of the whole simulation system. (27) Demonstration of the completed system. Publications and outputs Not available.
Lodz, Poland Technical University of Lodz, Polish Technology Platform of Textile Industry, Zeromskiego 116, 90-924 Lodz.
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Tel: +48 42 631 33 09; Fax: +48 42 631 33 09; E-mail:
[email protected] Principal investigator(s): Technical University of Lodz, Institute of Biopolymers and Chemical Fibres, Center of Molecular and Macromolecular Investigation of Polish Academy of Sciences Research staff: Prof. Izabella Krucinska, PhD, DSc, Prof. Barbara Lipp – Symonowicz, PhD, DSc, Prof. Roman Jantas, PhD, DSc, Prof. Stefan Polowinski, PhD, DSc, Ass. Prof. Marcin Struszczyk, PhD, DSc, Michal Chrzanowski, PhD, Jerzy Czekalski, PhD, Zbigniew Draczynski, PhD, Lucyna Herczynska, PhD, Agnieszka Komisarczyk, PhD, Malgorzata Koszewska, PhD, Monika Malinowska – Olszowy, PhD, Michal Puchaklski, PhD, Jacek Rutkowski, PhD, Dawid Stawski, PhD, Wiktor Strzembosz, PhD, Slawomir Sztajnowski, PhD, Joanna Szumilewicz, PhD, Wieslawa Urbaniak – Domagala, PhD, Jadwiga Bilska, MSc, Olga Mazalevska, MSc, Dorota Wojciechowska, MSc, Henryk Wrzosek, MSc, Stanislawa Kowalska, Eng.
Biodegeradable fibrous products Other Partners: Academic
Industrial
Technical University of Lodz, None Technical – Humanistic Academy Bielsko – Biala, Medical University of Wroclaw, Agricultural University in Karakow, Project start date: 17 November 2008 Project end date: 31 October 2013 Project budget: Qualified 35 579 999,82, total 35 918 089,57 Source of support: 85% European Funding of Region Development and 15% National fundings Keywords: Biodegradability, Polumers, Textiles, Non-fibrous products, Non-wovens The aim of the project is elaboration of biodegradable products for application as a filters, for agriculture (e.e.g. nonwovens for plant growing, pots or foils for hay) or medical (implants, wound dressings, hospital beds, hospital clothes) and hygienic (napkins, sanitary towel and others). Project bases on four polymers, which of one is commercially avaluable PLA, and three are elaborated in the frame of the project: modified Polypropylene, thermplastic cellulose and aliphatic copolyesters with extremly high biocompatibility for implantology). In the frame of the projects, products obtained by non-woven, knitting and spinning and spun-bonded technology are elaborated. Additionally, non-fibrous structures, like foils, membranes and foams are developed. All materials characterises biodegradability and properties required by their application. In the frame of the project, certified laboratory of biodegradability assessment was build. Also alaboratory stand for spun-bonded technology was designed and constructed.
Aims and objectives The aim of the project is elaboration and development of innovative technology necessary for national industry growing and improvement of position of polish industry on European market. Moreover, realisation of the project and potential incorporation of its products onto market will improver quality of life of Polish society in aspects of health care, hygienic, ecological agriculture and advanced, human friendly products. In the frame of the project following objectives are defined: (1) Elaboration of technology and modification of fibre-forming biodegradable polymers. (2) Elaboration of technology of fibre forming from biodegradable polymers. (3) Elaboration of technology of spun-bonded non-wovens from modified polypropylene and polylactide. (4) Elaboration of wide group of flat products and prototypes from biodegradable polymers for agriculture, medical and hygienic application and for technical (filtering) application. (5) Assessment of biodegradability of materials and products developed in the frame of the project. (6) Life-cycle assessment for selected products. Socio-economic objectives are also defined: (7) decreasing of environmental pressure by minimalisation of wastes; (8) increasing of supply of innovative technological solutions; (9) transformation of textile industry in industry bases on renewable raw materials; (10) increasing of competition of Polish industry on European market; and (11) increasing of cooperation between science and industry.
Deliverables In the project are defined numerous deliverables, which concerns elaboration and development of different products for: (1) agriculture; (2) hygienic; (3) medicine, including non-invasive products like hospital clothe and highly advanced products – implants, wound dressinfa and others; and (4) filtration – filters and half – masks. Publications and outputs A. Sroka-Bratnicka, W. Ciesielski, J. Libiszewski, A. Duda, M. Sochacki, M.J. Potrzebowski, “Complementarity of solvent-free MALDI tof and solid-state NMR spectroscopy in spectral analysis of polylactides”, Anal. Chem., 2010, Vol. 82, pp. 323-8. B. Z˙ywicka, E. Zaczyn´ska, A. Czarny, P. Dobrzyn´ski, M. Kowalczuk, “Cytotoxicity of new biodegradable fibrous copolymers with low-toxicity zirconium compounds for tissue repair and regenaration”, eCM True Open Access Journal, 2010. H. Schmidt, B. Witkowska, I. Kamin´ska, K. Twarowska-Schmidt, K. Wierus, D. Puchowicz, “Poro´wnanie szybkos´ci degradacji wło´kien polipropylenowych wywołanej s´wiatłem sztucznym i s´wiatłem słonecznym”, Polymer Degradation and Stability 2010. R. Jantas, S. Połowin´ski, D. Stawski, J. Szumilewicz, Modyfikacja Powierzchni Wło´kien Polilaktydowych Metode˘ Layer-By-Layer, Fibres & Textiles in Eastern Europe, 2010.
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B. Z˙ywickaiin., Cytotoxicity of the new biodegradable polylactide fibres for regenerative medicine, Inz˙ynieria Biomateriało´w, 2010. Presentations: B. Fryczkowska, R. Fryczkowski, J. Janicki, “Thermoplastic fibres in blends containing cellulose”, 6th Central European Conference 2010 Fibre-Grade Polymers, Chemical Fibres and Special Textiles, 2010 Bratysława. B. Fryczkowska, J. Janicki; R. Fryczkowski, “Conductive foils based on thermoplastic blends containing cellulose”, ICSM, 2010 Kyoto. R. Jantas, S. Połowin´ski, D. Stawski, J. Szumilewicz, L. Herczyn´ska, Z. Draczyn´Ski, “Modyfikacja powierzchni wło´kien polilaktydowych”, Meeting of the Polish Chem. Assoc., Gliwice 2010. K. Twarowska-Schmidt, M. Lichocik, K. Sulak, G. Maciejewski, “Degradacja termiczna pla w procesie przetwo´rstwa na wło´kna metode˘ stopowe˘”, Meeting of the Polish Chem. Assoc., Gliwice 2010. B. Witkowska, H. Schmidt, I. Kamin´ska, K. Wierus, D. Puchowicz, “Analysis of the photo-degradation of polypropylene yarns comparing the action of sunlight and artificial light”, Autex 20106. K. Twarowska-Schmidt, K. Sulak, M. Lichocik, G. Maciejewski, “Investigation in the manufacture of fibres from poly(lactic acid)”, 6th Central European Conference 2010 Fibre-Grade Polymers, Chemical Fibres and Special Textiles, 2010 Bratysława. S. Penczek, T. Biela, G. Lapienis, R. Szymanski, “Highly branched and star-shaped polyethers and polyesters (mainly polylactide)”, III Russian Conference “Current Treds in Petrochemistry” Zwiengorod (Russia), October 27-30, 2009. T. Biela, “Application of SEC chromatography for the actual molar mass determination and for analysis of polylactides of complex architecture”, 52 Zjazd PTCh i SITPChem, 2009. R. Jantas, S. Połowin´ski, D. Stawski, J. Szumilewicz, “Modyfikacja powierzchni wło´kien polilaktydowych metode˘ layer-by-layer”, Fibres & Textiles in Eastern Europe (in print). S. Penczek, T. Biela, G. Łapienis, R. Szyman´ski, “Branched polyethers and polysters”, 52 Zjazd PTChem i SITPChem, Ło´dz´ 20096. K. Twarowska-Schmidt, K. Sulak, M. Lichocik, G. Maciejewski, “Investigation in the manufacture of fibres from poly(lactic acid)”, 6th Central European Conference 2010 Fibre-Grade Polymers, Chemical Fibres and Special Textiles, 2010 Bratysława. B. Z˙ywickaiin, “Cytotoxicity of new biodegradable fibrous copolymers with low-toxicity zirconium compounds for tissue repair and regeneration”, Conference of Repair and Regeneration, Davos, June 2010.
Patent applications: “Obtining of thermoplastic composities containing pure celulose”. “Method of production of foam from biodegradable polymers”. “Methods of bioresorbable aliphatic polycarbons”.
Ło´dz´, Poland Technical University of Lodz, Department of Clothing Technology and Textronics, Zeromskiego 116, 90-924 Ło´dz´, Poland. Tel: +48 42 631 33 21; Fax: +48 42 631 33 20; E-mail:
[email protected] Principal investigator(s): Prof. Krzysztof Gniotek – Coordinator, Prof. Jan Błaszczyk – head of medical staff Research staff: Janusz Zie˘ba PhD, Michał Frydrysiak PhD,
Zbigniew Stempien´ PhD, DSc; Magdalena Tokarska PhD, Jacek Les´nikowski PhD, Tadeusz Nawarycz PhD, Łukasz Te˘siorowski, MSc
Research register
Textronic system for muscles electrostimulation Other Partners: Academic
Industrial
Medical University of Lodz None Project start date: 04 January 2010 Project end date: 30 November 2012 Project budget: 1 176 950 PLN (about 295 000e) Source of support: European Regional Development Fund and Polish Government The share of the European Union: 85% of project value Keywords: Textile electrodes, Textronics, Electrostimulation, Human muscles The object of the project is to produce and test the textronic system for electrostimulation current muscle. The system will be used for the electrical current of human muscles and in particular human limb muscles, for their excitation, for example, to enhance muscle strength, the occurrence of contracture resulting from their immobilization (broken arm, leg) and muscle strength training. Current flow is accompanied by loss of stimulation by causing thermal phenomena in the electrodes and between the electrode and the skin of the human limb, so it is advisable to carry out the analysis and identification of thermal phenomena during electrostimulation. The most effective pacing occurs at a specific moisture content of skin, limbs and good downforce, so the project will be developed textile electrodes that are placed in a wristband and socks. It depends on the place of electrical stimulation, or is on the hand or leg. The electrodes are integrated current sensors that measure surface and crossover muscles, and the temperature and humidity in the area of therapy. Construction of optimal electrode structure from the standpoint of electrical performance will be preceded by the development of different versions of the textile electrodes by the use of various technologies for their production. Expected to produce electrodes with electroconductive textile materials and fabrics by applying the electroconductive layer by sputtering or printing dyes elektroprzewodze˘cymi. Assumed to produce electrodes woven, knitted, nonwoven, and embroidered. The design of electrodes, their location and the conditions of electrical current will be developed in collaboration with the Medical University of Lodz. The study of electrodes and measuring systems will be performed on phantom limb constructed which maps the properties of electrically conductive. Phantom limb is to ensure the stationarity of the parameters. If the results of the entire system is successful it could be the basis for testing on patients at the Medical University. Tests measuring system and the effectiveness of electrostimulation require testing on a large number of patients and therefore should be subject to the next project.
Aims and objectives The project aims to design, produce and test the textronic system for electro stimulation of human muscles.
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The system will be used for the current electro stimulation of human muscles, in particular human limb muscles, to enhance muscle strength and muscle training. The specific objectives of the project are as follows: .
Conducting analysis and identification of thermal phenomena during electrical stimulation (stimulation current flow is accompanied by loss of power causing thermal phenomena in the electrodes and between the electrode and the skin of the human limb).
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Development of textile electrodes that are placed in a wristband and socks (the most effective pacing occurs at a specific moisture content of skin, limbs and good pressure).
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Establishing cooperation in the construction of the electrodes, their placement and the conditions of electrical current from the Medical University of Lodz.
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The construction of electrodes in the form of a matrix consisting of elementary electrodes that can be associated in any group adapted to the surface of stimulated body parts.
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Creation of unique design allows the power generator of medical shock stimulation of certain selected electrodes in the matrix of elementary.
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Constructing a unique device for automatic layering on the electroconductive layer of textile and quality assessment also plotted electroconductive layer by sputtering.
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Deliverables .
Designing of unique device for automatic layering of electroconductive layers on textiles and quality assessment of the layers.
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Development of textile electrodes in the form of a matrix consisting of elementary electrodes.
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The creation of unique design of medical power generator allows stimulation of selected elementary electrodes in the matrix.
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Development of phantom maping electroconductive properties of human limbs.
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Analysis and identification of thermal phenomena during electrostimulation.
Publications and outputs K. Gniotek, J. Zie˘ba, M. Frydrysiak, J. Les´nikowski, E. Rybicki, M. Kozicki, H. Kapusta, J. Błaszczyk, T. Nawarycz, “Gold medal for ‘The human phantom imitating impedance properties of human limbs’”, 4th International Warsaw Invention Show, Warsaw, Poland, 2010. K. Gniotek, J. Zie˘ba, M. Frydrysiak, J. Les´nikowski, E. Rybicki, M. Kozicki, H. Kapusta, J. Błaszczyk, T. Nawarycz, Diploma of Polish Minister of Science and Higher Education for “The human phantom imitating impedance properties of human limbs”, 18th Invention Exchange Awarded at the World Fairs in 2010, Warsaw, Poland 2011. Tokarska, M., Zie˘ba, J., Frydrysiak, M., Gniotek, K., Błaszczyk, J., Nawarycz, T., “The concept of the Forearm’s phantom to the research of textile electrodes”, Proceedings of 17th International Conference STRUTEX Structure and Structural Mechanics of Textiles, 18-19 November 2010, Liberec, Czech Republic.
Gniotek, K., Frydrysiak, M., Zie˘ba, J., Tokarska, M., Stempien´, Z., “Innovative textile electrodes for muscles electrostimulation”, Proceedings of 6th IEEE International Symposium on Medical Measurements and Applications MeMeA 2011, 30-31 May 2011, Bari, Italy. Stempien´, Z., Gniotek, K., Zie˘ba J., Tokarska M., Frydrysiak M., Te˘siorowski Ł., “Textile-based printed electrodes for muscles electrostimulation”, Proceedings of The Fiber Society Spring 2011 Conference, 23-25 May 2011, Hong Kong, China. Tokarska, M., Frydrysiak, M., Zie˘ba, J., Te˘siorowski, Ł., “Determination of electro conductive properties of textile electrodes based on selected methods of resistance measurement” (in Polish), Proceedings of Conference Basic Problems of Metrology PPM, Krynica Zdro´j, Poland, 12-15 June 2011.
Lodz, Poland Technical University of Lodz, Zeromskiego str 116, 90-924 Lodz. Tel: +48 426313321; +48 426313314; Fax: +48 426313320; E-mail:
[email protected] Principal investigator(s): Prof. Iwona Frydrych, PhD, DSc Research staff: Marian Rybicki, PhD, Janusz Zielin´ski, PhD, Graz˙yna Orawiec, MSc
Elaboration of new type of protective gloves from basalt fibers for hot workplaces Other Partners: Academic
Industrial
None Basaltex a.s. Czech Republic Project start date: 13 March 2010 Project end date: 18 March 2012 Project budget: 211600 Source of support: NCBiR – 127 000,00 PLN; PŁ – 84 600,00 PLN Keywords: Protective gloves, Basalt fibres, Hot workplaces Due to their special properties the basalt fibers can be used as a full substitute of special glass fiber threads for a high acid resistance request, heat resistant, non toxic and elastic structures for technical purposes, fillers for reinforcement polymer composites with low water absorption and high dielectric parameters. The noncombustible properties of basalt woven materials enable to resist flames for long perods of time. Basalt fibers are ecologically clean and non-toxic, which is the next technical advantage of such fibers. In this project we propose to design a new type of protective gloves intended for the use as a protection against thermal risks, especially by mastallurgists, founders or firefighters. The main activities within the project are following: (1) elaboration and laboratory assesment of basalat fibers; (2) modelling the structure of protective fabric from basalt fibers; (3) laboratory assessment of protective fabrics; (4) opatimization of fabric aluminizing; (5) elaboration and assessment of the aluminized protective fabrics made of protective clothing;
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(6) designing the construction of gloves taking into account the protective parameters; and (7) laboratory assessment of protective gloves.
Aims and objectives
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The aim of the project is to design a new type of protective gloves intended for the use as a protection against thermal risks, especially by mastallurgists, founders or fire-fighters. Due to their special properties the basalt fibers can be used as a full substitute of special glass fiber threads for a high acid resistance request, heat resistant, non toxic and elastic structures for technical purposes, fillers for reinforcement polymer composites with low water absorption and high dielectric parameters.
Deliverables The development of new type of protective gloves made of basalt fibers. This kind of PPE is very important for different industrial branches in which workers are simultaneously exposed to the heat or fire of differwent forms: fire, contact heat, conductive heaty, radiant heat, smal splashes or large quantities of molten metal. The new type of gloves will be costeffective in comparioson to those existed on the market. Publications and outputs A. Stefko, I. Frydrych, E. Irzman´ska, M. Bednar, “Thermal properties of chosen basalt fabrics”, paper presented at Autex Conference 2011, Mulhouse, 2011. A. Stefko, I. Frydrych, E. Irzman´ska, M. Bednar, “Basalt fabrics for thermal protection”, paper under review in Fibres and Textiles in Eastern Europe.
Loughborough, UK Environmental Ergonomics Research Centre, Loughborough Design School, Loughborough University, Loughborough, UK LE11 3TU. Tel: +01509 223031; Fax: +01509 223940; E-mail:
[email protected] Principal investigator(s): Prof. George Havenith Research staff: Sarah Davey, Victoria Richmond, Katy Griggs
Protective responsive outer shell for people in industrial environments (PROSPIE). Other Partners: Academic
Industrial
TNO; EMPA; Lithuanian Textile Institute Foritas; JSC Pakaita; I.O.C.P Spa; Capzo; Humanikin; Ergonsim; Merford Cabins; IFAK; D’Appolonia Spa;VanHoutte Consulting; Bel-Confect; Palemono Keramika AB. Project start date: 1 December 2009 Project end date: 30 November 2012 Project budget: 3.66e million
Source of support: European Union (Nanotechnologies, Materials and New Production). Keywords: Protective clothing, Physiological load, Sensors, Cooling systems In the Prospie-project a new generation of personal protective equipment (PPE) will be developed and produced. The special feature of the PPE will be a dynamic cooling system that prevents the worker to become hyperthermic. Although sweat evaporation is an excellent cooling mechanism for work in the heat, this system is compromised when working in protective clothing. The body temperature rises and consequently the vigilance and task performance decrease. Eventually the worker has to abandon his task due to incompensable heat strain. Prospie aims to supply the worker with personal protective equipment that enables him or her to work longer in protective clothing with less discomfort. Innovative cooling methods, like forced ventilation, phase change materials and encapsulated endothermic salts, will be integrated with protective clothing. Sensors in the suit will measure relevant physiological data, such as skin temperature, heat flux and heart rate, to assess the thermal status of the worker, and the environmental conditions (temperature, relative humidity). The physiological signals will be used in an algorithm that will generate a warning signal when a certain safety threshold is surpassed. Data will also be transferred to industrial safety systems in order to alert rescue workers if needed. The operational benefit of prototypes of the suit will be determined in a controlled setting as well as in the industry where protective suits are indispensable. The results will be disseminated to standardization organizations, the industry and public procurement organizations. A training program will be made that focuses on the acceptability of the system by SME’s and end-users. Although the system aims to contain the newest technology, human factors and practical usability including for instance ease of cleaning are leading in the design of the prototypes.
Aims and objectives To develop a protective clothing system to the production stage, incorporating physiological sensing and advanced cooling support.
Deliverables A clothing concept based on existing technologies that is ready for mass production. Publications and outputs See web site: www.prospie.eu; http://cordis.europa.eu (search for PROSPIE).
Manchester, UK Manchester Metropolitan University, Department of Clothing Design & Technology, Hollings Faculty, Manchester Metropolitan University, Old Hall Lane, Manchester, M14 6HR. Tel: +0161 247 2636; Fax: +0161 247 6354; E-mail:
[email protected] Principal investigator(s): David J. Tyler Research staff: Praburaj Venkatraman, Jane Ledbury
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Functional clothing with comfort Other Partners: Academic
Industrial
None None Project start date: April 2011 Project end date: August 2012 Project budget: £30,000 Source of support: Miriad Research Institute Keywords: Design principles, Compression, Impact protection, Comfort There is a rapidly growing interest in high performance materials and garments with enhanced functionality. This is partly because commodity garments are highly pricesensitive and are almost all manufactured in countries with low labour costs. Domestic industry is looking to supply products that have added functionality and enhanced performance. The programme of experimentation will establish protocols for obtaining reliable and valid data. The next steps involve looking at materials and commercial products. The research will develop design principles linking garment comfort and functionality
Aims and objectives .
to develop protocols for evaluating the impact protection provided by clothing materials;
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to build a database relevant to PPE and sportswear materials;
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to analyse base layer garments for sportswear, with particular reference to compression and comfort; and to develop design principles linking functionality and comfort.
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Deliverables At present, our focus is on academic deliverables: developing the knowledge base. Publications and outputs Not available.
Maribor, Slovenia University of Maribor, Faculty of Mechanical Engineering, Smetanova ulica 17, SI-2000 Maribor, Slovenia. Tel: +386 2 220 7960; Fax: +386 2 220 7996; E-mail:
[email protected] Principal investigator(s): Univ.-Prof. Drsc. Jelka GERSˇAK Research staff: Research Unit Clothing Engineering
Clothing engineering and textile materials
Other Partners: Academic
Industrial
None None Project start date: 1 January 2009 Project end date: 31 December 2012 Project budget: 85.000 ECU for 2010 Source of support: Slovenian Research Agency Keywords: Clothing, Fabric, Fabric mechanics, Behaviour, Comfort, Prediction The research programme comprehends tree thematically connected parts: . . .
study of draping behavior of woven fabrics; survey of draping of garments, their fit and 3D dynamic simulation of clothes; and research and development of a model for evaluation of thermo-physiological comfort related to wearing of garment items.
Within the first area, the studies related to complex deformation of fabrics and their draping behaviour have been carried out. Based on extensive research and study of draping behaviour of fabrics it was established that fabrics have complex threedimensional shape, which is a direct reflection of a fabric reaction against deformation. Specific geometry of a fabric drape is conditioned by anisotropic properties of textile materials depending on fibre type, kind, structures and construction of the yarn, fabric construction parameters, as well as on finishing, which directly influences the parameters of mechanical properties. Research results have shown that direction of twists in yarns of same constructional has a direct impact on fabric draping parameters as well as on geometry of draping area. Resulted changes in geometry of draping area can be assigned to differences related to friction between the fibres in a yarn and yarns in a fabric. In the area of research related to draping of garments, their fit and 3D dynamic clothing simulation, we were focused on research and development of virtually constructed garment models. For this purpose, we carried out the simulations of 3D models of garments based on material parameters, i.e. mechanical properties of applied fabrics. The purpose was to study the influence of particular mechanical parameters on fabric draping and to achieve a perfect fit of a garment. Real prototypes of garments have been produced in order to verify the virtually simulated garments constructed and modelled using a CAD system. Comparative analysis has shown the need for additional research related to description of material parameters, resp. for application of suitable and reliable rheologic models. The third area of research has been directed to study of relationship between material properties and different physiological parameters of thermal comfort in wearing of clothing. Based on experimental research related to material properties of fabrics and their sorption properties we have realised that there is interdependence between material characteristics of fabrics, quantity of absorbed sweat and thermal comfort. Achieved cognitions represent an important part of data needed for establishing a database about thermo-physiological comfort of a user of garments. At the same time, they will serve for the development and realisation of a numerical simulation of a thermo-physiological behaviour of fabrics, as parts of garments, in different climatic conditions.
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Aims and objectives The main aims and objectives of the research programme “Clothing engineering and textile materials” are as follows: .
to define the elastic behaviour of complex textile structures;
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evaluation of fabric behaviour at draping in a form of complex deformation;
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to define of reasons for asymetrical behaviour of complex textile structures;
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development of the material model and simulation of complex textile structures;
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design of the data base of factors related to the level of the appearance quality of business clothing;
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design of the model for definition of thermal resistance of one and multi-layer clothing systems;
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to set-up the characterisation of parameters related to thermophysiological comfort;
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design of the data base related to subjective estimation of thermal comfort; and
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design of the model for predicting the physiological and psychological comfort at garment wearing.
Deliverables The results of research programme will serve for setting-up the engineering concept for “knowledge-based products”. An important contribution to further development of the science is expected also from gained theoretical cognitions from the field related to the study of the relationship between the material properties of textile materials and heat transfer, as well as quantity of absorbed moisture/sweat and thermo-physiological and ergonomic comfort of a human being wearing different kinds of garments and thereof developed theories. Publications and outputs Tokmak, O., Berkalp, O.B., Gersˇak, J. (2010), “Investigation of the mechanics and performance of woven fabrics using objective evaluation techniques, Part 1: the relationship between FAST, KES-F and Cusick’s drape-mete parameters”, Fibres Text. East. Eur., Vol. 18, No. 2(79), pp. 55-9. Grujic´, D., Gersˇak, J., Ristic´, M. (2010), “Utjecaj fizikalnih i sorpcijskih svojstava tkanina na kolicˇinu upijenog znoja u odjec´i”, Tekstil, Vol. 59, No. 3, pp. 68-79. Vujasinovic´, E., Gersˇak, J., Dragcˇevic´, Z. (2010), “Objektivno vrednovanje kvalitete denim tkanine obradene enzimima”, Tekstil, Vol. 59, No. 6, pp. 228-44. Celcar, D., Gersˇak, J., Meinander, H. (2010), “Evaluation of textile thermal properties and their combinations (Vrednotenje toplotnih lastnosti tekstilij in njihovih kombinacij)”, Tekstilec, Vol. 53, No. 1/3, pp. 9-32. ¨ . (2010), “Fabric drape Al-Gaadi, B., Gersˇak, J., Go¨ktepe, F., Hala´sz, M., Tama´s, P., Go¨ktepe, O examination using ring-controlled equipment, V”, 4th International Technical Textile Congress, Istanbul, Turkey, 16-18 May 2010, Congress Proceedings, Istanbul: Engineering Faculty, Textle Engineering Department, 2010. Petrak, S., Glavica, B., Gersˇak, J., Mahnic´, M., Rogale, D., Ujevic´, D. (2010), “Garments prototype development using an innovative computer technology”, 5th International Textile, Clothing & Design Conference (also) ITC&DC, October 3 to October 6, 2010, Dubrovnik, Croatia, Magic World of Textiles: Book of Proceedings, Zagreb: Faculty of Textile Technology, University of Zagreb, pp. 488-93.
Gersˇak, J., Marcˇicˇ, M. (2010), Study of elastic behaviour of textile structures, 5th International Textile, Clothing & Design Conference (also) ITC&DC, October 3-6, 2010, Dubrovnik, Croatia, Magic World of Textiles: Book of Proceedings, Zagreb: Faculty of Textile Technology, University of Zagreb, pp. 588-93. ¨ zdemir, D. (2010), “Twist Go¨ktepe, F., Halasz, M., Tamas, P., Go¨ktepe, O¨., Gersˇak, J., Al-Gaadi, B., O direction and yarn type effect on draping properties”, 41st International Symposium on Novelties in Textiles and 5th International Symposium on Novelties in Graphics and 45th International Congress IFKT, Ljubljana, Slovenia, 27-29 May 2010, Proceedings, Ljubljana: Faculty of Natural Sciences and Engineering, Department of Textiles, pp. 171-77. Gersˇak, J., Marcˇicˇ, M. (2011), The peculiarities of a complex design concept for functional protective clothing”, Proceedings of CBMTS Industry VII “The World Congress on the CBRN Threat and Terrorism”, Cavtat, 10-15 April (in press).
Maribor, Slovenia University of Maribor, Faculty of Mechanical Engineering, Smetanova ulica 17, 2000 Maribor. Tel: +386 2 220-7500; Fax: +386 2 220-7990, E-mail:
[email protected] Principal investigator(s): Alenka Majcen Le Marechal Research staff: Bojana Voncina, Darko Golob, Ernest Sˇimon, Julija Volmajer Valh, Simona Vajnhandl, Vera Vivod
Novel selective materials for removal of organic pollutants from textile wastewater photochemically pre-treated Other Partners: Academic
Industrial
None
None
Lokateks, podjetje za zaposlovanje invalidov, d.o.o. Sˇkofja Loka Project start date: 1 May 2009 Project end date: 30 April 2012 Project budget: N/A Source of support: National Agency Keywords: Technical textiles, Selective filters, Cyclodextrins, Host-quest molecules, Textile surface modification, Nanoencapsulation, Toxic degradation products, Persistent organic pollutants, Phenols, Aromatic amines, Formaldehyde, Textile dyes, Textile wastewater, Recycling, Advanced oxidation processes, Textile wastewater treatment. The textile finishing industry is the second biggest water consuming sector in Europe after agriculture. The most important water consuming processes are washing, rinsing, dyeing (up to 300 L/kg) and finishing (up to 930 L/kg). Textile finishing industry in a broad sense of world is beside being the biggest consumer of water inside the industrial sector, also one of the main sources of emissions (high oscillation of ecological parameters like: COD from 150-12,000 mg/L and BOD from 80-6,000 mg/L). Beside dyes, the textile waste water can contain also surfactants, salts, heavy metals, fats, oils, many
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different organic and inorganic additives, finishing agents, even very toxic micro pollutants, etc. Due to increase of the prices of technical waters and waste water treatments and due to global scarcity of water, the recycling of waste water is becoming the necessity, but technological bottlenecks limit the application of water loop closure. As a result of continuous water recycling, several groups of substances are concentrated in the water loop and may cause water quality problems as well as health risks. The research is now focused also on the reduction/elimination of toxic organic pollutants resulting from of dyestuffs and auxiliaries or present in low concentrations in applied chemicals or basic materials. The textile industry is known as a potential source of various toxic pollutants like persistent organic pollutants (POPs), phenols, formaldehyde forming compounds, various aromatic amines, etc. To remove these toxic micro pollutants several separation techniques, based on filtration, adsorption, and extraction could be applied, like ultra filtration, nano filtration, reverse osmosis, activated carbon, nano spunge, liquid-liquid extraction, enzymatic methods and others. Current filtration/adsorption technologies fail to be implemented successfully in the textile waste water treatments for recycling due to limited efficiency, economical reasons, not environmentally friendly or selective enough, etc. Most of actual textile waste water treatment technologies focus on advanced water treatments for discharge. In the frame of the project various textile filter materials (based on immobilized cyclodextrins on water-insoluble organic support) for separation of organic pollutants will be prepared, with the emphasis on toxic micro pollutants removal from textile waste waters after advanced oxidizing process based on H2O2/UV. AOPs are usually combined with other techniques, like filtration. Prepared textile filters should be efficient and economically acceptable. Textile materials are very important as filter materials. Their cost is more acceptable, they have a sufficient mechanical strength, the pore size, the macro-pore size can vary (depending on the type of textile and on the diameter of fibres). Cyclodextrins form inclusion compounds with various small molecules. Such complexes can be formed in solution, in the solid state, as well as when cyclodextrins are linked to the textile surface where they can act as permanent or temporary hosts to small molecules. With the change of the polarity of the cyclodextrin cavity and with the change of the size of the cavity we can prepare the nanoassembly selective materials with filtration properties.
Aims and objectives The aim of the project is preparation of various novel selective materials for separation of main toxic organic pollutants from textile waste waters after AOP treatment. The H2O2/UV technology as one of AOPs has been recognized as a promising and powerful technology for the destruction of organic pollutants commonly present in textile effluents. It is characterized as oxidation processes in which hydroxyl radicals are the dominant reactive special with a high oxidation potential (2.8 V), much higher than molecular hydrogen peroxide (1.78 V). The H2O2/UV process has some advantages over some other AOPs such as Fenton, O3/UV and UV/TiO2. Firstly, hydrogen peroxide is completely miscible in water, thus causing no phase transfer problems. Furthermore, it is a chemically stable compound and commercially available in almost limitless quantities. Finally yet importantly, the absence of sludge formation is one of the major advantages of the H2O2/UV process. However, the use of energy demanding UV lamps to
produce the irradiation needed for the photolysis of the hydrogen peroxide gives rise to rather high operating costs. This disadvantage can be minimized by the process optimization which may make the H2O2/UV process economically more acceptable. The complete mineralization has normally very long treatment time which is again related with high energy consumption and thus leads to high operational costs, which can be minimised with an appropriate waste water train technology, composed with different techniques, also filtration, which have many drawbacks as already mentioned. For this reason within this project various textile filter materials for the separation of remaining organic pollutants and their oxidation products after H2O2/UV treatment from textile waste water will be prepared. Prepared filters should be efficient and economically acceptable textile filters. Textile materials are very important as filter materials. The cost of textile materials is more acceptable (PET; viscose), they have a sufficient mechanical strength, the pore size, especially the macro-pore size can vary, it depends on the type of textile (the density of non-woven material) and on the diameter of fibers. Textile materials can be further modified to prepare filtration materials with additionally improved adsorption. The amount of aromatic organic pollutant will be reduced from treated wastewater by using cyclodextrins which will be immobilized on water-insoluble organic support. Incineration of disposed used textile filter materials will not present a problem, because the combustion of selected textile material supports can be carried out completely. Textile filter materials are economically interesting; cyclodextrines which will be bound to the textile support to improve the filtering efficiency and selectivity do not represent an important additional financial charge. Cyclodextrins are cyclic oligosaharides consisting of 6, 7, or 8 glucose rings can form stabile inclusion complex with various organic molecules and with some metal ions as well. These torus shaped molecules have relatively hydrophobic interiors and hydrophilic exteriors with primary hydroxyl groups located on the smaller end of the torus, and secondary hydroxyl groups located on the larger end. Cyclodextrins are very well known »host guest« molecules which form inclusion complexes with various small molecules. Such complexes can be formed in solution, in the solid state, as well as when cyclodextrins are linked to a surface where they can act as permanent or temporary hosts for small molecules. The stability of the complex formed depends on the polarity of the “guest-host” molecules. The polarity of cyclodextrins and the selectivity for forming complexes with different molecules can be tailored by the substitution of the hydroxyl groups of cyclodextrins and with the linking/crosslinking systems used for covelent bonding of cyclodextrins onto insoluble support. With the change of the polarity of the cyclodextrin cavity and with the change of the size of the cavity (use of alfa, beta or gama cyclodextrins) we can prepare different assemblies (networks) with selective filtration properties. After filtration process, the organic support with cyclodextrin containing organic compounds can be incinerated.
Deliverables Final report not available yet. Publications and outputs Novak, Nina, Majcen Le Marechal, Alenka, Bogataj, Milosˇ, “Determination of cost optimal operating conditions for decoloration and mineralizatzion of C.I. reactive blue 268 by UV/H2O2 process”, Chem. Eng. J. 1996. (Print ed.), 2009, Vol. 151, Iss. 1/3, pp. 209-19. Voncˇina, Bojana, Vivod, Vera, Chen, Wen-Tung, “Surface modification of PET fibers with the use of (beta)-cyclodextrin”, J. Appl. Polym. Sci., 2009, Vol. 113, Iss. 6, pp. 3891-5.
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Majcen Le Marechal, Alenka, Vajnhandl, Simona, Krizˇanec, Bosˇtjan, Novak, Nina, “H2O2/UV and ultrasound assisted decolouration and their effect on the formation of toxic organic compounds: V”, 1st International Workshop on Application of Redox Technologies in the Environment, Istanbul Technical University, September 14-15, 2009, Istanbul, Tu¨rkiye. Arte’2009: CD of Proceedings, ¨ niversitesi: Bogazic¸i U ¨ niversitesi, 2009. Istanbul: Istanbul Teknı´k U Voncˇina, Bojana, “Assembly of nanocapsules on textile substrates for postponed release of active compound: V”, Innovations in Textiles 2009, 18-19 March 2009 Royal College of Physicians, London, Smart, Nano and Technical Textiles for Medical, Industrial and Clothing Applications: Conference Handbook. Stirling, Scotland: Institute of Nanotechnology, Cop. 2009, p. 43. Zupanc, Maja, “Preparation of textile materials for selective filtration of phenol from wastewater”, Master thesis (Maribor: M. Zupanc), 2009. Majcen Le Marechal, Alenka, Vajnhandl, Simona, Jericˇ, Tina, Mattioli, Davide, Grilli, Selene, “Strategies for water recycling implementation in Slovene textile companies: V”, Perrin Akcakoca, E. (ur.). 12th International Izmir Textile and Apparel Symposium, 28-30 October 2010, Izmir, Turkey. Proceedings: IITAS 2010. Izmir: Ege University, Department of Textile Engineering: Ege University Textile and Apparel Research – Application Center, 2010, pp. 146-50. Novak, Nina, Majcen Le Marechal, Alenka, “Optimization tools for the treatment of colored wastewater by UV/H2O2: V”, VII ANQUE International Congress, 13-16 June 2010, Oviedo, Spain, Integral Water Cycle: present and future: “a shared commitment”: abstracts book. Madrid: Asociacio´n Nacional de Quı´micos de Espan˜a (ANQUE), 2010. Majcen Le Marechal, Alenka, Vajnhandl, Simona, Jericˇ, Tina, Mattioli, Davide, Grilli, Selene, “Global approach to water recycling in Slovene textile companies: V”, 6th Central European Conference 2010, 13-14 September, 2010, Bratislava, Slovak Republic, Fibre-Grade Polymers, Chemical Fibres and Special Textiles: (Proceedings). Bratislava: Slovak University of Technology in Bratislava, Faculty of Chemical and Food Technology, Department of Fibres and Textile Chemistry, 2010. Golob, Darko, Majcen Le Marechal, Alenka, Brodnjak-Voncˇina, Darinka, Vajnhandl, Simona, “Required water quality in textile finishing industry: V”, 10th Autex Conference, June 21-23, 2010, Vilnius, Lithuania, Proceedings of Autex 2010, Kaunas: Kaunas University of Technology, Faculty od Design and Technologies, Department of Textile Technology, 2010.
Maribor, Slovenia University of Maribor, Faculty of Mechanical Engineering, Smetanova ulica 17, 2000 Maribor. Tel: +386 2 220-7500; Fax: +386 2 220-7990; E-mail:
[email protected] Principal investigator(s): Alenka Majcen Le Marechal Research staff: Julija Volmajer Valh, Bojana Voncina, Simona Vajnhandl, Tina Jeric, Darko Golob, Ernest Simon, Vera Vivod, Lidija Skodic
Combination of cunstructed wetland and upgraded AOP reactor for the wastewater treatment in textile finishing industry Other Partners: Academic
Industrial
None
None
Tekstina D.D., Slovenia; Stazione Sperimentale per la Seta, Italy; OBEM S.P.A. Dyeing and Steaming Machinery, Italy Project start date: 1 January 2009 Project end date: 30 October 2011 Project budget: 0.64 Me Source of support: National Agency Keywords: Water pollution, Water treatment, Wastewater effluent Water is important natural resource for sustainable ecosystems, human life and economical development. Management of technological wastewater includes interdisciplinary and multidisciplinary approach and adjustment with more and more rigorous legislative. Organic contaminants in wastewater present a specific problem due to their toxicity, bioaccumulation and poor biodegrability. Textile industry is one of the greatest water consumers in Europe. Processes, where most water is consumed are printing and dyeing, in average 100-150 m3/t, with annual consumption at the European level of 600 million m3. Besides being one of the greatest consumer of the water, textile industry is also one of the highest pollutants because of the large use of numerous organic compounds and different auxiliary substances. On average, 90% of the water input in textile finishing operations needs to be treated end-of-pipe and 1 kg of chemicals and auxiliaries is processed per kg of textile products. In Europe, 108 million tons of wastewater is produced on a yearly basis and 36 million tons of chemicals and auxiliaries have to be removed from the textile wastewater. Specific water usage rates may vary among different textile operations from 50 to over 500 m3/t. Textile wastewater typically contains a complex mixture of organic and inorganic chemicals, and this is the reason that the processes of cleaning and recycling of wastewater are difficult to perform. Organic contaminants in wastewater present a specific problem due to their toxicity, bioaccumulation and poor biodegradability. The price for wastewater treatment varies in average from 0.5-2.5e/m3 and it is expected that the price in the future will increase (estimation value is from 3-5e/m3). Due to the strict environmental legislation and high wastewater treatment cost the proposed project activities will be oriented in developing an effective wastewater technology train in the textile company Tekstina. Individualized and preselected technology train concept for the textile wastewater treatment will combined from constructed wetland (CW), prefiltration and advanced oxidation unit. During the project each unit will be studied as an individual treatment step and also as train technology treatment with adequate combination to achieve the best water quality for the lowest price. Tekstina as end-users in this project is a SME, manufacturing and marketing fashion and technical fabrics. The company has serious problems with more efficient use of their water resources and with the highly coloured effluent discharge into environment. That is why the reduction of fresh water in their industrial processes and their effluent discharge into environment (high taxes), beside their product quality and process stability is of their major concern. The actual wastewater treatment solution (end-ofpipe) does not give satisfactory results and the company is seeking an urgent solution.
Aims and objectives Due to the strict environmental legislation and high wastewater treatment cost the proposed project activities will be oriented in developing an effective wastewater technology train in the textile company Tekstina. Individualized and preselected
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technology train concept for the textile wastewater treatment will combined from constructed wetland (CW), prefiltration and advanced oxidation unit. During the project each unit will be studied as an individual treatment step and also as train technology treatment with adequate combination to achieve the best water quality for the lowest price. The aim of the project is: Development and implementation of integrated tailor-made technology treatment line for textile wastewater based on prefiltration, advanced oxidation treatment using AOP pilot reactor and biological treatment using constructed wetland.
Deliverables Final report not available yet. Publications and outputs Jericˇ, Tina, Majcen Le Marechal, Alenka, Kavsˇek, Darja, Brodnjak-Voncˇina, Darinka, “Characterization of textile waste water streams: V”, Valant, Matjazˇ (ur.), Pirnat, Ursˇa (ur.), Slovenska konferenca o materialih in tehnologijah za trajnostni razvoj, Ajdovsˇcˇina, 11-12 maj 2009, Knjiga povzetkov, Zbornik, V Novi Gorici: Zalozˇba Univerze, 2009, pp. 99-103. Majcen Le Marechal, Alenka, Vajnhandl, Simona, “AOP pilotni poskusi v tekstilnih tovarnah: V”, Simoncˇicˇ, Barbara (ur.), Gregor-Svetec, Diana (ur.), Forte-Tavcˇer, Petra (ur.). 42. simpozij o novostih v tekstilstvu, 2. junij 2011, Ljubljana in 6. simpozij o novostih v grafiki, 2. junij 2011, Ljubljana. Nove tehnologije - da ali ne?. Ljubljana: Naravoslovnotehnisˇka fakulteta, Oddelek za tekstilstvo, 2011, str. 165-8.
Nottingham, UK Nottingham Trent University, School of Art and Design, Bonington Building, Nottingham NG1 4BU. Tel: +0115 848 6518 E-mail:
[email protected] Principal investigator(s): Professor Tilak Dias Research staff: Ms Tessa Acti
High performance flexible fabric electronics for megahertz frequency communications Other Partners: Academic
Industrial
Department of Electronic and Electrical Antrum Ltd, Defence Marine Systems Ltd Engineering, Loughborough University and Advanced Therapeutic Materials Ltd Project start date: 1 November 2010 Project end date: 31 October 2013 Project budget: £434,000 Source of support: IeMRC/EPSRC Keywords: Fabric antennas, Digital embroidery, Conductive fabrics, Textile sensors This project will develop new technologies capable of creating wearable, flexible yet functional antennas able to perform in even the harshest environmental conditions.
Monopole antennas associated with search and rescue technology are acknowledged to be cumbersome; prone to breakage and potentially even a source of additional risk to the user, e.g. they have pierced life rafts. This new technology will be expressed in demonstrator antennas that integrate into flexible, wearable fabric, miniaturising the technology and making it discrete, easy to use, robust, reliable and cost effective. A team of academics, manufacturers and textile specialists have come together to examine every characteristic of the technology and identify and overcome areas for refinement, e.g. the most suitable material to connect the antenna. The team will focus on developing a technology with due consideration to such manufacturing related issues as sustainability, quality control, cost, and complexity of manufacturing process. The project will deliver research and technology infrastructure that has been rigorously tested and designed not only to meet the needs of the end-user but also to be capable of being manufactured by a process which meets the criteria of best practice in the industry-sustainable, cost-effective, and of the highest quality. The technology has the potential to spread to a number of industry sectors and these potential opportunities will be explored and defined. The primary goal is to research and test the capability of the technology through the design of a fabric-based antenna capable of maintaining a strong radio signal, even when the antenna is slightly bent vertically, horizontally or diagonally and send location information to a remote control centre. This demonstrator will also be subject to challenging environmental testing to ascertain the limits of the technology’s performance. The objectives of this project will be achieved by a team approach, ensuring that the expertise and industry insight of each partner is fully utilised. An initial step, championed by Antrum Ltd, will be to fully understand the capabilities of the antenna using computer simulations. A wide-range of testing scenarios will be simulated and investigated. These will include extremes of temperature, precipitation and salination. The results will be used to inform the development of representative samples that can be further tested and measured. This detailed process will feed into the pre-production prototyping drawing on the expertise of our industrial partners in manufacturing and the academic specialists in textile fabrication at CReATe (Centre for Research in Advanced Textiles) in the School of Art and Design of the Nottingham Trent University. Laboratory and pre-production prototypes will be repeatedly tested and refined until optimum capability is reached. This is an iterative process that will undoubtedly reveal new challenges along the way leading to further lines of enquiry.
Aims and objectives The overall aim is to develop and share the capability to produce a viable pre-production demonstrator/prototype of a fabric antenna, integrated into clothing, which can be translated into mass manufacture, initially for the search and rescue market. Further, to identify the most appropriate manufacturing methodology in conjunction with industrial partners and to plan how the technology will evolve into a viable product capable of meeting end-user needs. To achieve this, the laboratory prototype now requires refinement and testing with significant input from manufacturers and endusers to ensure that it is both fit for purpose and capable of manufacture in an efficient, cost effective and sustainable manner. Key objectives of the project can be divided into technical/manufacturing challenges, which will be overcome using a team approach pooling expertise from the academic and industrial partners, and market place
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challenges relating to the identification of markets and the development of a detailed understanding of end-user requirements and the dissemination of information relating to this technology to raise awareness of its potential. Research technological/manufacturing objectives: (1) to refine the electromagnetic design rules; (2) to research and define how connections will be made to the antennas; (3) to achieve suitable integration of the antennas into a textile system; (4) to devise ways of minimising body interference from the wearer; (5) to examine the impact of different environmental factors on the performance of the antenna; (6) to define the manufacturing process ensuring that it is green, sustainable and cost effective; (7) to understand how fabric treatments, e.g. waterproofing, might affect performance. Market place objectives: (8) to identify further possible applications/markets for this technology; and (9) to identify end-users of the technology and ensure that their requirements are reflected in the functionality of the technology and the effectiveness of its manufacture.
Deliverables Technical: (1) Representative prototype antennas targeted for Search & Rescue applications, integrated into life jackets. Tested under all applicable environmental conditions. (2) Design guidelines for production of fabric-based antennas with a variety of materials for this application. (3) An effective interconnection system for fabric based systems working at lower frequencies. (4) Production of multilayer devices using textiles. (5) One of the challenges in realising wireless fabric based devices is to find materials that are not only functional but also adaptable under bending conditions and harsh weather conditions. Non-technical: (6) A detailed market potential assessment examining the potential of alternative markets and an initial market penetration strategy. (7) Steps taken to protect all intellectual property and necessary contracts relating to commercialisation in hand. (8) A future development plan agreed between all partners and steps taken to secure further funding to sustain the project. (9) An assessment of new markets, such as sports wear with a preliminary market penetration strategy. Publications and outputs Acti, T., Zhang, S., Chauraya, A., Whittow, W., Rob Seager, R., Dias, T. and Vardaxoglou, Y., “High performance flexible fabric electronics for megahertz frequency communications”, LAPC2011.
Ohtsu, Japan SCI-TEX, 12-15 Hanazono-cho, Ohtsu, 520-0222 Japan. Tel: +077-572-3332; Fax: +077-572-3332; E-mail:
[email protected] Principal investigator(s): Tatsuki Matsuo Research staff: N/A
Potential and limitation in fibrous configurational functions as materials Other Partners: Academic
Industrial
None None Project start date: August 2010 Project end date: Februray 2011 Project budget: N/A Source of support: N/A Keywords: Configurational function of fibrous material, Its potemtial and limitation Recently fibers have been intensively applied to technical textiles as functional materials. Further, several kinds of new fibrous materials such as carbon nano-tube, organic and inorganic nano-fibers, and metallic nano-wires have been intensively developed. The configurational functions of fibrous materials are consisted of the following four elements: (1) They are flexible (pliable). (2) They can have high ability in their axial transmission in such matters as mechanical load, heat conduction, electric conduction, optical light, liquid, particles and ion. (3) They have comparatively high extended specific surface area. (4) They have technological easiness in transformability into fiber assembly structures such as threads, fabrics, nonwovens paper and 3D structures. In this study, how effectively these configurational functions are used in several technical textile applications are investigated. What kinds of limitations as compared with the other kinds of material forms are there in the application of fibrous materials is also investigated. Finally, the potential in the new applications of fibrous materials in the near future are discussed.
Aims and objectives To try to clarify the potential and limitation of fibrous configurational functions as compared with the other kinds of materials such as bilk and particle.
Deliverables Not yet.
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Publications and outputs The results of this study will be presented the 39th Textile Research Symposium held at New Delhi in 2010 December.
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SCI-TEX, 12-15, hanazono-cho, Ohtsu-city, 520-0222 Japan. Tel: +81-77-572-3332; Fax: +81-77-572-3332; E-mail:
[email protected] Principal investigator(s): Tatsuki Matsuo Research staff:
Propagation of knowledge on new textile science and technology Other Partners: Academic
Industrial
None None Project start date: N/A Project end date: On going Project budget: N/A Source of support: N/A Keywords: Advanced technical textiles, Knowledge propagation The importance of advanced technical textiles has increased in the textile industry of developed countries. In addition, R&D on nano-technologies and electric-textiles are now intensively carried out. In this situation, propagation of knowledge on new textile science and technology must be meaningful. This project is being conducted individually by T. Matsuo through symposium lectures, journal articles and monographic books.
Aims and objectives Deliverables Not available. Publications and outputs Not available.
Terrassa, Spain UPC-EET, Colom, 1, 08222-Terrassa, Spain. Tel: +937398249; Fax: NA; E-mail:
[email protected] Principal investigator(s): Prof. J.M. Canal Research staff: Dr C. Canal, C. Labay
Cloths for medical and cosmetical applications Other Partners: Academic UPC Project start date: 2009 Project budget: N/A Source of support: N/A Keywords: N/A
Industrial Yes Project end date: 2013
Aims and objectives Deliverables Not available. Publications and outputs Not available.
Wuxi, China Jiangnan University, Lihu Road 1800, Wuxi, China, 214122. Tel: +86-510-85327307; Fax: +86-510-85327307; E-mail:
[email protected] Principal investigator(s): Liu Jihong Research staff: Qian Kun, Panruru, Yang Ruihua
Mechanical property and application of “8” shape 3D woven enhancing composite Other Partners: Academic
Research register
Industrial
Jiangsu Information College Nanjing Composite Company of China Project start date: 1 January 2008 Project end date: 31 December 2011 Project budget: $20,000 Source of support: Nanjing Composite Company of China Keywords: 3D woven enhancing fabric; Composites; Binder yarn; Mechanical Property; Model; “8” Shape Three-dimensional (3D) woven enhancing fabric and its composite was produced on a modified rapier loom. Weaving parameters were studied and restructuring method was researched. After that mechanical property including tension, compress, and so on will be modelled an research. The results express that the property has relationship with the direction of fabric and layers.
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Aims and objectives (1) Research on the parameters of produceing woven fabric. (2) Build a model and research on mechanical properties.
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(1) A reconstruction loom for producing “8” shape woven fabric. (2) A kind of method for producing composite of “8” shape woven fabric. Publications and outputs Weaving Thickness Parameters of “8” Shape 3D Woven Enhancing Fabric. Mechanical Property and Model of “8” Shape 3D Woven Enhancing Composite.
Zagreb, Croatia Faculty of Textile technology, Prilaz baruna Filipovica 28a, 10000 Zagreb, Croatia. Tel: +385 1 3712 540; Fax: +385 1 37 12 599; E-mail:
[email protected] Principal investigator(s): Dubravko Rogale Research staff: Zvonko Dragcˇevic´, Gojko Nikolic´, Maja Vinkovic´, Snjezˇana Firsˇt Rogale, Slavenka Petrak, Goran Cˇubric´
Intelligent garment and environment Other Partners: Academic
Industrial
None None Project start date: 2007 Project end date: 2012 Project budget: 100 000e Source of support: Ministry of Science, Education and Sports Keywords: Intelligent garment, Thermal protection, Environment Investigations, construction and development of intelligent article of clothing related to its direct environment by developing an adaptable bed, adaptable ironing machine and measuring instrument for multiaxial testing physical-mechanical properties of technical textile and joined parts. The purpose of the project is that a research team makes researches resulting in a construction and realization of the first intelligent garment whose basic function is active thermal protection. It contains a sensor system for monitoring the values of air temperature inside and outside of the garment, data bus for data transfer, microcomputer and micro controller, and execution devices for the automatic regulation of thermal protection value. Controlling conduction and convection of the heat of the human body regulates thermal protection in such a way that based on anthropometric measurements several types of various air thermo insulation elastic chambers are constructed which are integrated into the construction of the garment between the outer shell and lining.
Thermoinsulation chambers consist of several segments and have a twofold function so that by inflating sealing properties are assumed, and the heat loss of the human body by convection can be regulated and the thickness of the air chambers can be changed by program, whereby the heat loss of the human body by conduction can to be regulated. Micropneumatic elements and the chambers would be equipped with sensors of air pressure integrated into them, because depending on air pressure values in the chambers there will be defined chamber forms, their sealing properties and thickness on which thermal resistance depends. Investigations would prove that the integration and efficient joint operation of the integrated sensors, microcomputers with associated algorithms of intelligent behavior and actuators so that an independent action of the garment is realized with the aim of thermal protection whereby the garment would have the attribute of active, adaptable and intelligent behavior in variable temperature conditions. Communication possibilities of intelligent garment with the environment would be examined and an intelligent sick bed, adaptable ironing-machine and an instrument for testing load would be developed. They would practically use the same or very similar sensor, computer and micropneumatic actuator systems, connection techniques, constructions and design as well as intelligent garment.
Aims and objectives The basic aim of the proposed research project is to investigate the possible construction and practical realization of an intelligent article of clothing with thermal protection, adaptable bed, ironing machine for the technological manufacturing process and necessary measuring instruments. The purpose of the investigation is to investigate characteristics of all elements of the system and behavior of the system as a whole and the communication between intelligent garment and environment. In addition to the basic aim of all investigations it is necessary to point out other aims too emerging as the result of the said investigation. Establishment of the leading European and world scientific role in investigations and development of intelligent garment. Writing 4 doctoral dissertations in the mentioned field (two dissertations in the mentioned field have been registered and approved by the Senate of the University of Zagreb. To prove that the Croatian clothing industry possesses a strong scientific research basis that guaranties it a technological excellence on demanding foreign markets.
Deliverables The final assumed investigation results are practically applicable immediately upon completion of the project. It may be expected that the industrial production of intelligent garment with active thermal protection could be commenced immediately upon completion of the project. The examined and realized intelligent article of clothing would be a world unique item and might become an original Croatian product, especially from the point of view that original production principles have been protected by patent so that the future production rights are unquestionable. The developed intelligent article of clothing is very interesting for all the people being in extreme climatic conditions (soldiers, policemen, security services agents, construction workers, sailors, maintenance of roads, buildings and industrial facilities, drivers of trucks and
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construction machinery, athletes, recreationists, and other persons who wish to have such an article of clothing). In addition to the clothing industry, other industry branches such as mechanical engineers, electronics engineers, and programmers, participate in the production of intelligent garment, so that benefits can be expected for them too.
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Publications and outputs Rogale, D., Firsˇt Rogale, S., Dragcˇevic´, Z., Nikolic´, G., “Intelligent article of clothing with an active thermal protection”, European Patent Office, Munich, Germany, No. PCT/HR2004/000026. Firsˇt Rogale, S., Nikolic´, G., Dragcˇevic´, Z., Rogale, D., Bartosˇ, M., “Arhitecture of clothing with an active thermal protection”, Proceedings of the 16th DAAAM International Symposium: Intelligent Manufacturing & Automation: Focus on Young Researchers and Scientists/Katalinic´, Branko (Ed.), Vienna, DAAAM International Vienna, 2005, pp. 121-2. Rogale, D., Firsˇt Rogale, S., Dragcˇevic´, Z., Nikolic´, G., Bartosˇ, M., “Development of intelligent clothing with an active thermal protection”, 6th World Textile Conference, 11-14 June 2006, North Carolina, pp. 106-12. Petrak, S., Rogale, D., “Methods of automatic computerised cutting pattern construction”, International Journal of Clothing Science and Technology, Vol. 13, No. 3/4 (2001), pp. 228-39. Firsˇt Rogale, S., Dragcˇevic´, Z., Rogale D., “Determining reaction abilities of sewing machine operators in joining curved seams”, International Journal of Clothing Science and Technology, Vol. 15, No. 3/4(2003), pp. 179-88. Rogale, D., Petrunic´, I., Dragcˇevic´, Z., Firsˇt Rogale, S., “Equipment and methods used to investigate energy processing parameters of sewing technology operations”, International Journal of Clothing Science and Technology, Vol. 17, No. 3/4(2005), str. 179-87. Petrak, S., Rogale, D., “Systematic representation and application of a 3D computer-aided garment construction method, Part I 3D garment basic cut construction on a virtual body model”, International Journal of Clothing Science and Technology, Vol. 18 (2006), No. 3, pp. 179-87. Petrak, S., Rogale, D., Mandekic´-Botteri, V., “Systematic representation and application of a 3D computer-aided garment construction method, Part II spatial transformation of 3D garment cut segments”, International Journal of Clothing Science and Technology, Vol. 18(2006), No. 3, pp. 188-99. Firsˇt Rogale, Snjezˇana; Rogale, Dubravko; Dragcˇevic´, Zvonko; Nikolic´, Gojko, Bartosˇ, Milivoj., “Technical systems in intelligent clothing with active thermal protection”, International Journal of Clothing Science and Technology, Vol. 19(2007), No. 3/4, pp. 222-33. Firsˇt Rogale, Snjezˇana; Rogale, Dubravko; Dragcˇevic´, Zvonko; Nikolic´, Gojko, Runkas, Martin, “Intelligent clothing whit programmabile insulation, DAAAM International Scientific Book 2008, Branko Katalinic´ (Ed.). Vienna: DAAAM International, 2008, str. 273-86. Firsˇt Rogale, S., Rogale, D., Dragcˇevic´, Z., Nikolic´, G., Bartosˇ, M., “Technical systems in intelligent clothing with active thermal protection”, Annual 2007 of Croatian Academy of Engineering, Zlatko Kniewland (Ed.), Zagreb: Croatian Academy of Engineering, 2007, pp. 301-17. Firsˇt Rogale S., Rogale, D., Dragcˇevic´, Z., Nikolic´, G., “Realization of the prototype of intelligent article of clothing with active thermal protection”, Tekstil, Vol. 56, 2007, No. 10, pp. 610-26. Firsˇt Rogale, S., Rogale, D., Nikolic´, G., Dragcˇevic´, Z., Bartosˇ, M., “Chambers in the intelligent clothing with active thermal protection”, Proceedings of 5th International Conference IMCEP 2007, Jelka Gersˇak (Ed.), Maribor: University of Maribor Faculty of Mechanical Engineering, 2007, pp. 23-33. Nikolic´, G., Firsˇt Rogale, S., Rogale, D., Dragcˇevic´, Z., Bartosˇ, M., “Pneumatic system of the intelligent article of clothing with active thermal protection”, Ventil., Vol. 14, 2008, No. 6, pp. 552-6. Firsˇt Rogale, Snjezˇana, Rogale, Dubravko, Dragcˇevic´, Zvonko, Nikolic´, Gojko, Runkas, Martin, “Intelligent clothing whit programmabile insulation”, DAAAM International Scientific Book 2008, Branko Katalinic´ (Ed.), Vienna: DAAAM International, 2008, pp. 273-86.
Firsˇt Rogale, S., Rogale, D., Nikolic´, G, Dragcˇevic´, Z., “Controllable ribbed thermoinsulative chamber of continuallyadjustable thickness and its application”, European Patent Office, Munich, Germany, No. PCT/HR2009/000008; 2009.
Research register
Zagreb, Croatia University of Zagreb, Faculty of Textile Technology, Prilaz baruna Filipovica 30, HR-10000 Zagreb, Croatia. Tel: +385 1 37 12 566; Fax: +385 1 37 12 599; E-mail:
[email protected] Principal investigator(s): Prof. Maja Andrassy, PhD Research staff: Prof. Zvonko Dragcevic, PhD; Assoc.Prof. Emira Pezelj, PhD; Prof. Dubravka Raffaelli, PhD; Assist. Prof. Edita Vujasinovic, PhD; Zvonko Orehovec, PhD; Vera Friscic, MSc; Ruzica Surina, BSc; Prof. Majda Sfiligoj Smole, PhD
High performance textile materials and added-value fibres Other Partners: Academic
Industrial
University of Maribor Faculty of None Mechanical Engineering, Maribor, Slovenia Project start date: 1 January 2007 Project end date: 31 December 2011 Project budget: N/A Source of support: Ministry of Science, Education and Sport, Republic of Croatia Keywords: HP materials, Textile fibers, Textile design Contemporary global trends of development in the field of textile fibres and fibrous materials have led to their increased use in various fields of industry and technique. Increase in consupmtion of these types of materials has constantly been recorded and by the beginning of the 21st century technical fibres account for half of all the fibres manufactured. The requirements imposed on fibres and materials in particular fields of application and extraordinary high and specific. These requirements have been met through fibre engineering, i.e. development of new generic types of fibres. It can be assumed that innovative manufacturing and finishing processes, applied to conventional fibres, will result in their added value, so that they can be used to design new fabrics of predetermined end-use properties. Such improvements in fibre properties and their use in fabric manufacture of added market value and broader scope of application are completely in accordance with the intentions of the European technological platform for future textile and garment, but it can also strongly stimulate the development of Croatian textile industry and its comptetitiveness in the global market. This is supported by the fact that there are considerable research, industrial and raw-material potentials in Croatia, necessary to accomplish the goals. Although domestic production is mostly based on imported fibres, clearly defined modifications of fibre structure and propertties, even for domestic fibres, such as wool, flax, textile regenerates and fibres made from recycled PET,
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that have been used in Croatian textile industry insufficiently until now, could be used as a starting raw material for the manufacture of high-performance textiles. In this manner, domestic fibrous raw materials would cease being waste material and would become strategic Croatian raw material, as well as a basis of future rational management of natural resources and a step in approaching sustainable development trends, recommended by the European Union and United Nations. The investigations proposed aim at establishing the possibilities of modifying conventional fibres, as well as developing the methods and procedures of objective measurement and evaluation of unconventional textile materials, in accordance with specific rules and requirements for individual types of high-performance textiles, including composites reinforced with fibres of modified properties. The results obtained will offer the construction of high-performance materials based on conventional fibres of added value, as well as the design and optimisation in accordance with the properties of the fibres used and pre-determined high end-use properties.
Aims and objectives The main purpose of the project proposed is to determine possible interventions and modifications of conventional fibres and textiles, so as to obtain added value and to broaden the scope of their application. This immrovement of fibres and their application in the manufacture of new, knowledge-based innovative textiles of added market value is in accordance with the short term (energy and materials) and long-term (nano-science, new materials, constructions and production processes) strategic trends of research in the Republic of Croatia, strategies of the European technological platform for the future of textiles and garment in the XXI century, as well as with the trends of rational management of raw material resources and the concept of sustainable development, as proposed by the EU and UN recommendations. Valuable results and new knowledge are expected, especially regarding ecologically friendly and economically feasible production of high-performance textiles through the usage of domestic raw materials in their manufacture. There is a broad diversity of fibres and constructions present in the area of non-conventional textile materials and structures, which makes objective characterisation of their quality a difficult task, we propose to develop new methods, procedures and equipment for testing, so as to enable higher degree of objectivity in quality evaluation. The investigations are planned to initiate the development and optimising of the manufacture of high-performance textiles, matched with their increased and more and more specified areas of application. The results expected to be obtained will enhance the scope of knowledge in the field of textile fibres, materials and textile testing, also valuable in the education of young researchers, knowledge transfer and preparation of future textile engineers for the European labour market.
Deliverables The results of the investigation will be directly applicable in Croatian textile industry, since new solutions for designing high-performance materials, based on conventional fibres of added value, will be proposed as based on the results of the investigations proposed. As there are some processing capacities still in Croatia (Regeneracija, Kelteks, Vrbenka, Konoplja, LIO, Feniks), working with imported fibres, the system of objective description and evaluation of domestic fibrous raw materials (especially flax and wool), as well as some instructions regarding their environmentally acceptable manufacture, processing and modifications, with the aim of enhancing end-use properties, are
expected to create adequate conditions for econbomically feasible manufacture of textiles. Higher content of domestic fibres and raw materials in manufacture of textile would be a sound basis for new development and growth of the Croatian textile industry and its competitiveness in the European and global markets, as well as for realising the principles of sustainable development and rational raw material resource management. Developments and innovations in testing metodology and objective evaluation of relenat properties of the modified fibres and new high-performance textiles will enhance objectivity of testing and evaluation of high-performance technical textiles in general, which is, not only in Croatia but globally as well, a problem with no acceptable solution on the horizon. Some testing methods are expected to be used in production monitoring and control, which could contribute to more reliable and stable manufacture and realising pre-planned levels of quality. The investigations proposed open the way to scientific and professional collaboration with other institutions and with the industry. Publications and outputs Ruzˇica Sˇurina i Maja Somogyi, “Biodegradable polymers for biomedical purpose”, Tekstil, Vol. 55(2006), No. 12, pp. 642-5. Ruzˇica Sˇurina i Maja Andrassy, “Resistance of lignocellulosic fibers to microorganisms, XX. hrvatski skup kemicˇara i kemijskih inzˇenjera, knjiga sazˇetaka, posvec´en Lavoslavu Ruzˇicˇki i Vladimiru Prelogu, hrvatskim nobelovcima u kemiji, Zagreb, 26. veljacˇa – 01, ozˇujka 2007, 286. Cindric´, Jasna, “Improvements properties of flax fibers”, diploma work, Zagreb, Tekstilno-tehnolosˇki fakultet, 25 April 2007, 56 str. Voditelj: Andrassy, Maja. Klasic´, Sanja, “Usable properties of modified flax fabric”, diploma work, Zagreb, Tekstilno-tehnolosˇki fakultet, 25 April 2007., 53 str. Voditelj: Andrassy, Maja. Sˇurina Ruzˇica i Andrassy Maja, “Quality of modified flax fibers”, The 18th International DAAAM Symposium, “Intelligent Manufacturing & Automation: Focus on Creativity, Responsibility and Ethics of Engineers”, 24-27 October 2007 (in press). E. Vujasinovic, Z. Jankovic, Z. Dragcevic, I. Petrunic, D. Rogale, “Investigation of the strength of ultrasonically welded sails”, International Journal of Clothing Science and Technology, Vol. 19(2007), No. 3/4, pp. 204-14, ISSN: 0955-6222. E. Vujasinovic, Z. Dragcevic, Z. Bezic, “Descriptors for the objective evaluation of sailcloth weather resistance”, Proceedings of 7th Autex Conference 2007, Tampere 26-28 June 2007, Finland, ISBN: 978-952-15-1794-5.
Zagreb, Croatia Faculty of Textile Technology, University of Zagreb, Prilaz baruna Filipivic´a 30, HR-10 000 Zagreb, Croatia. Tel: +38514877351; Fax: +38514877357; E-mail:
[email protected] Principal investigator(s): Prof. emeritus, Ivo Soljacˇic´, PhD Research staff: Asoc. Prof. Tanja Pusˇic´, PhD; Prof. Ljerka Bokic´, PhD; Asst. Prof. Branka Vojnovic´, PhD; Iva Rezic´, PhD; Prof. Jelena Macan, PhD; Asoc. Prof. Barbara Simoncˇic´, PhD, Prof. Sonja Sˇostar-Turk, PhD; Asist.Prof. Sabina Fijan, PhD; Mila Nuber, MSc; Ivan Sˇimic´, MSc; Dinko Pezelj, PhD, Versˇec Josip, MSc
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Ethics and ecology in textile finishing and care Other Partners: Academic
Industrial
University of Maribor and University of Labud, d.d. Zagreb and Vodovod, Zagreb Ljubljana, Slovenia Project start date: 1 January 2007 Project end date: 31 December 2011 Project budget: N/A Source of support: Ministry of Science, Education and Sports, Republic of Croatia Keywords: Wellness finishing of textiles, Determination of harmful substances on textiles, Toxicological and alergenic properties, Environmental protection, Hygiene and effects of textile care, Textile material sample preparation Modern textile finishing processes have to fulfill high demands due to the expectations of new textile materials properties and their persistence during care. Especially interesting in this respect are the new production processes of socks which include implementation of microcapsules that can release active materials for skin moisturizing. Their primal role is prevention of dryness, dandruff and allergenic reactions of the skin. The most suitable analytical methods for determination of durability to washing, friction and sweat will be tested. Durability to washing of products with special properties will be tested with different amounts of anionic and cationic surfactants in liquid detergents. The mechanism of adsorption and desorption, their influence on primary effect of the treatment, and the influence of the pH value and the mechanical way of treatment will be tested. On the ground of the obtained results, analytical methods for determination of micro components in the macro components of textile materials should be proposed, without regards to the specifications of the materials or the method of the treatment. The testing will involve a review of the analytical method of each individual analytical procedure as well as its impact on the obtained information. The parameters of the analytical procedure will be worked out with the purpose of restoration of historical textile by destructive and non-destructive methods for the preservation of national heritage. European controlling methods of new materials have ethical demands involving the human population health which demands an environmental friendly process. For this purpose the processes of textile finishing and care will be optimized. The possibility of obtaining new preventive properties, which were not previously present on the textile material or improvement of present protection, will be tested. The impact of washing cycles with detergent and UV absorber on pastel colored textile materials made of cotton, polyester and their mixtures on UPF and the shade change will be investigated. The quality control of water and effluents will be based on the determination of micro quantities of potential allergens, heavy metals, pesticides, dyes, and surfactants. The traces of solvents will be controlled on the clothing material and in the air during the chemical cleaning and further treatment processing.
Aims and objectives The main goal of this investigation is to stimulate ethic ecological demands on the production processes, care processes, and thereby on the utilization properties of the textile materials wherewith it would be possible to get the optimal properties of
materials regarding their functional properties by avoiding all possible harmful allergenic and toxicological influences of textile materials to consumers. Elaboration of production and textile finishing processes for the optimal effects (wellness finishing, protection from unwanted changes of utilization properties in texcare, elaboration of pastel dyed textiles laundering in detergent with UV absorber, additional laundering quality – UV protection), formulation of new compositions for laundering for the purpose of avoiding secondary harmful effects in modern conditions with maximal saving of water and energy, more safe treatment with solvents during dry cleaning. By monitoring of harmful inorganic and organic substances that are present in micro quantities on the textile materials, textile accessories, textile wastewaters and finished textile products, new analytical methods would be determined. Sampling procedures, sampling preparation steps, selection of appropriate analytical method and the processing of the obtained result will be optimized. In this investigation the mathematical modes for guiding of analytical procedure will be applied, what is economically justified because the time spend for investigation is much shorter, and the consumption of chemical reagents, energy and emission of harmful substances to the environment reduced. Special contribution will be in development of analytical methods for determination of components present on the historical textile, for the purpose of avoiding the damaging of the textile material during restoration conservation treatments.
Deliverables The project is scheduled over three years. Eco problems and human ecology, especially presence of heavy metal traces in textile processes and fibres will be investigated and some results will be published. Analytical methods for qualitative and quantitative determination will be developed. The influence of sweat on the heavy metal emission will be tested from colored textile materials. Possibility and durability of wellness finishing effects particularly on PA pantyhose’s as well as methods will be established. UPF and change in shade of white and pastel colored textiles made from cotton, PET, PA and their blend with cotton during laundering with addition fluorescent compounds in detergent will be researched, too. Hygienic laundering with chemothermic and chemical treatments in order to destroy micro-organisms in compliance with existing recommendations will be done. Potentially irritations of the skin caused by textiles, finishing agents and inadequate rinsing during laundering will be studied. Investigation of anionic, cationic and nonionic surfactant adsorption and desorption influenced by different composition of textile fibres, pH and temperature will be performed. The adsorption and desorption will be studied in order to establish a correlation between zeta potential and swelling capacity of textile fibres. Publications and outputs Rezic´, Iva, Steffan, Ilse, “ICP-OES determination of metals present in textile materials”, Microchemical Journal, Vol. 85(2007), No. 1, pp. 46-51 (scientific paper). Fijan, Sabina, Pusˇic´, Tanja, Sˇostar-Turk, Sonja, Neral, Branko, “The influence of industrial laundering of hospital textiles on the properties of cotton fabrics”, Textile Research Journal, (2007) (in press). Pusˇic´, Tanja, Jelicˇic´, Jasenka, Nuber, Mila, Soljacˇic´, Ivo, “Istrazˇivanje sredstava za kemijsko bijeljenje u pranju”, Tekstil (2007) (in press).
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Pusˇic´, Tanja, Soljacˇic´, Ivo, “Changes in shade of cotton fabrics during laundering with detergents containing fluorescent brightening agent and UV absorber”, AATCC Review, (2007) (in press). Vojnovic´, Branka; Bokic´, Ljerka, Kozina, Maja, Kozina, Ana, “Optimization of analytical procedure for phosphate determination in detergent powders and in loundry wastewater”, Tekstil (2007) (in press).
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Zagreb, Croatia University of Zagreb, Faculty of Textile Technology, Prilaz baruna Filipovic´a 30, HR-10000 Zagreb, Croatia. Tel: +385 1 37 12 521; Fax: +385 1 37 12 599; E-mail:
[email protected] Principal investigator(s): Assoc. Prof. Emira Pezelj, PhD Research staff: Prof. Ruzˇica Cˇunko, PhD; Prof. Maja Andrassy, PhD; Assist. Prof. Edita Vujasinovic, Prof. Vili Bukosˇek, PhD; Antoneta Tomljenovic´, PhD; Sanja Ercegovic´, M. Sc.; Maja Somogyi, B. Sc.; Dubravka Gordosˇ, M. Sc.
Multifunctional human protective textile materials Other Partners: Academic
Industrial
None None Project start date: 1 January 2007 Project end date: 31 December 2011 Project budget: N/A Source of support: Croatian Ministry of Science, Education and Sport, Republic of Croatia Keywords: Protective textiles, Multifunctionality, Smart textiles, Ceramic coatings, Sol-gel process The investigations proposed have been motivated by the fact that people are more and more exposed to various influences from the environment, which can be harmful to their health. Such harmful influences are, for example, UV irradiation, electromagnetic smog, high temperature, fire, etc. Contemporary textile materials for personal protection are required to offer high efficiency, in most cases multifunctionality, as well as a necessary level of comfort. The fabrics used are high-performance ones and interdisciplinary approach is necessary in research dealing with their development and manufacture. The thesis we propose is that the application of contemporary research results in the field of materials can be used to offer a new contribution to the development of multifunctional protective textile materials. The accent will be given to a purposeful surface modification of fabrics, using environmentally friendly agents and processes, which is in accordance with contemporary European trends of research in the field of materials. Special attention will be paid to investigating modifications using the new sol/gel process, combined with preceding ultrasound, laser and plasma treatment of textile surfaces. New possibilities of manufacturing efficient protective layers will be investigated, using various inorganic substances, including functional layers of nano-
dimension made of hybrid inorganic-organic polymers. The aim is to optimise modification parameters of achieving efficient protection from UV and EM irradiation, as well as to increase resistance to abrasion, cutting and heat in particular materials, establishing antimicrobial properties at the same time. Adequate testing procedures will be established to evaluate the newly created materials. New levels of knowledge is expected to be achieved regarding correlation of protective properties and textile fabric composition, as well as the development of practical processes of obtaining aimed fabric modifications and the development of the methods of new material evaluation. New knowledge will contribute to the quality of education in the field of textile materials. Transfer of knowledge into actual industrial production is also expected. The results will be presented on international conferences and will be published in relevant international publications. The obtained results to be obtained could be used to stimulate manufacture of new high-performance textile materials for special purposes in Croatia.
Aims and objectives The purpose of the investigations is to obtain new knowledge in the field of material development, especially regarding the new composites with textiles as a basic component. The knowledge should be directly applicable in practice, and simultaneously used to improve the quality of education, of both students, young researchers and experts from the industry. The new knowledge is expected to further the development of the Department of textile materials, where the investigations are organised. Based on the knowledge of high-performance materials, that has resulted in the development of the composites, and the role of textile component in them, the possibility will be investigated of obtaining high-performance composites for protection, in which textiles are the basic component. These are new textile materials to be used as protection from harmful influences of the general and working environment in high-risk industrial processes and other activities where people are exposed to risks of mechanical, thermal or chemical injuries, of infection by micro-organisms and even fatal risks from the causes. This is why protective materials are expected to offer high efficiency under various conditions, while the best solutions are aimed at obtaining multi-functional protection by a single material. The purpose of the research is to investigate the solutions that could be applied in textile industry, which could stimulate the introduction of knowledge-based and new-technology-based production in the industry, through adapting the industry to manufacture high-performance composite materials for special purposes. The aim of the investigation is to determine the procedures of obtaining multi-functional textiles for personal protection, simple to manufacture and use. The protective properties will be obtained by modifying the surfaces of the fabrics of various constructions, with the aim to establish optimal modification procedures and processing parameters which could offer efficient protection from individual influences, or, otherwise, protection from more influences. The investigations are supposed to result in solutions for objective evaluation of the effect achieved and the durability of protection as well, but also in the evaluation of the adequacy of the materials for a particular purpose. Adequate testing methods and procedures will be developed, appropriate indicators defined and the correlation of the modification parameters and properties achieved established.
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Deliverables The purpose of the investigations is to obtain new knowledge in the field of material development, especially regarding the new composites with textiles as a basic component. The knowledge should be directly applicable in practice, and simultaneously used to improve the quality of education, of both students, young researchers and experts from the industry. The new knowledge is expected to further the development of the Department of textile materials, where the investigations are organised. Based on the knowledge of high-performance materials, that has resulted in the development of the composites, and the role of textile component in them, the possibility will be investigated of obtaining high-performance composites for protection, in which textiles are the basic component. These are new textile materials to be used as protection from harmful influences of the general and working environment in high-risk industrial processes and other activities where people are exposed to risks of mechanical, thermal or chemical injuries, of infection by micro-organisms and even fatal risks from the causes. This is why protective materials are expected to offer high efficiency under various conditions, while the best solutions are aimed at obtaining multi-functional protection by a single material. The purpose of the research is to investigate the solutions that could be applied in textile industry, which could stimulate the introduction of knowledge-based and new-technology-based production in the industry, through adapting the industry to manufacture high-performance composite materials for special purposes. The aim of the investigation is to determine the procedures of obtaining multi-functional textiles for personal protection, simple to manufacture and use. The protective properties will be obtained by modifying the surfaces of the fabrics of various constructions, with the aim to establish optimal modification procedures and processing parameters which could offer efficient protection from individual influences, or, otherwise, protection from more influences. The investigations are supposed to result in solutions for objective evaluation of the effect achieved and the durability of protection as well, but also in the evaluation of the adequacy of the materials for a particular purpose. Adequate testing methods and procedures will be developed, appropriate indicators defined and the correlation of the modification parameters and properties achieved established. Publications and outputs R. Cˇunko, S. Ercegovic´, D. Gordosˇ, E. Pezelj, “influence of ultrasound on physical properties of wool fibres”, Tekstil, Vol. 55 (2006), pp. 1-9. A. Tomljenovic´, E. Pezelj, F. Sluga, “Application of TiO2 nanoparticles for UV protective shade textile materials”, Proceedings of 38th Symposium of Textile Novelity, Ljubljana, 21 June 2007, Slovenia. E. Vujasinovic, Z. Jankovic, Z. Dragcevic, I. Petrunic, D. Rogale, “Investigation of the strength of ultrasonically welded sails”, International Journal of Clothing Science and Technology, Vol. 19 (2007), No. 3/4, pp. 204-14, ISSN: 0955-6222. E. Vujasinovic, Z. Dragcevic, Z. Bezic, “Descriptors for the objective evaluation of sailcloth weather resistance”, Proceedings of 7th Autex Conference 2007, Tampere, 26-28 June 2007, Finland, ISBN: 978-952-15-1794-5. Ruzˇica Sˇurina i Maja Somogyi, “Biodegradable polymers for biomedical purpose”, Tekstil, Vol. 55 (2006), No. 12, pp. 642-45. Ruzˇica Sˇurina i Maja Andrassy, Resistance of lignocellulosic fibers to microorganisms, XX. hrvatski skup kemicˇara i kemijskih inzˇenjera, knjiga sazˇetaka, posvec´en Lavoslavu Ruzˇicˇki i Vladimiru Prelogu, hrvatskim nobelovcima u kemiji, Zagreb, 26. veljacˇa – 01. ozˇujka 2007, 286.
Sˇurina Ruzˇica i Andrassy Maja, “Quality of modified flax fibers”, The 18th International DAAAM Symposium, “Intelligent Manufacturing & Automation: Focus on Creativity, Responsibility and Ethics of Engineers”, 24-27 October 2007.
Research register
Zagreb, Croatia Faculty of Textile Technology, University of Zagreb, Prilaz baruna Filipovic´a 30, HR-10 000 Zagreb, Croatia. Tel: +385 1 48 77 352; Fax: +385 1 48 77 352; E-mail:
[email protected] Principal investigator(s): Prof. Drago Katovic´, PhD Research staff: Asoc. Prof. Sandra Bischof Vukusˇic´, PhD; Prof. emeritus Ivo Soljacˇic´, PhD; Dubravka Dosˇen Sˇver, PhD; Sandra Flincˇec Grgac, BSc; Asoc. Prof. Radovan Despot, PhD; Asist. Prof. Jelena Trajkovic´, PhD; Asist. Prof. Branka Lozo, PhD; Luka Cˇavara, MSc; Bozˇo Tomic´, M.c.; Prof. Charles Yang, PhD; Prof. Christian Schram, PhD
Alternative eco-friendly processing & methods of cellulose chemical modification Other Partners: Academic
Industrial
Faculty of Forestry, Croatia; Faculty of Cˇateks, d.d., www.cateks.hr Graphic Art, Croatia; University of Georgia, USA; University of Innsbruck, Austria Project start date: 1 January 2007 Project end date: 31 December 2011 Project budget: N/A Source of support: Ministy of Science, Education and Sports, Republic of Croatia Keywords: Multifunctional eco-friendly textile finishing, Polycarboxylic acids, Protective functionalities, Chemical modification of cellulose, Microvawe treatment of cellulose materials One of the requests of European Union for higher competiteveness of European market is rebuilding and reconstruction of traditional industrial sectors, especialy textile and wood industry. According to the strategical goals of the Republic of Croatia the project emphasizes the use of highly sofisticated production processes and treatments of cellulose materials, i.e. obtaining additional and improved characteristics of wooden and paper matherials which can be acchieved by using high-tech processes and by introduction of nano- micro- and bio-technologies. One of the alternative methods for replaciong the conventional reactants containing formaldehyde which were used in textile and wood treatments so far, would be the modification with eco-friendly agents such as polycarboxylic acids. Efficiency of these treatments will be determined quantitatively by ester crosslinking analytical methods or by means of isocratic HPLC
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and spectrophotometric FTIR method. Standard methods of textile, wood and paper material testing would be used for examining their protective performance and resistance to weathering conditions. Part of the proposed project will be development of optional multifunctional treatment that would provide better protection of cellulose materials against microorganisms, UV, electromagnetic rays, flame, oil or water. Therefore, a particular attention will be payed to development and application of the agents which will not only improve the characteristics of textile matherials but also give it permanent freshness and provide additional care and protection, i.e. medical characteristics. Optimisation of alternative processing and methods will provide ecologically and economicaly favorable characteristics of treated matherials. Further process optimisation in order to improve processing quality could be obtained with new alternative method using microwave energy. Improved characteristics obtained with this method in our previous research confirm its usability in textile finishing processes as well as in chemical modification of wood. Previous research in this field represent worlwide novelty which should be by all means continued.
Aims and objectives The purpose and aim of the proposed project is to obtain highly valuable and multifunctional treated textile materials that will acquire analogous price on the demanding market. This is the basic condition for the survival of Croatian textile, wood and paper industry on EU market. In textile area experiments will be conducted to obtain multifunctional environmentally friendly textile material which will simultaneously offer dimensional stability, flame retardancy, crease and antimicrobial resistance and will have no effects on human health. Further goal is to obtain chemicaly modified wood that will have reduced shrinking and water absorption as well as to obtain flame retardancy on wood and paper products. One of the equally important goals is construction of a semi industrial microwave device for continuous planar treatment of cellulose materials. The results obtained would be presented in the world best known papers in the relevant field. The most important goal of the project is affirmation of Croatian science in Europe and rest of the World, by presenting the results in international papers so as on International Conferences. It is important to stress that established cooperation with EU and USA experts, so as with their scientific institutions will be continued and expanded. In this project, where will scientists from abroad have an active contribution with their work, further contribution to development of high quality products will be added. We certainly hope it will affect development of Croatian industry and economy.
Deliverables Not available. Publications and outputs Katovic´, D., Bischof Vukusˇic´, S., Flincˇec Grgac, S. (2007), “Crosslinking cotton with citric acid and organophosphorus agent for the purpose of flame retardant finishing”, 85th Textile Institute Conference, Colombo, Sri Lanka, pp. 820-4. Bischof Vukusˇic´, S., Flincˇec Grgac, S., Katovic´, D. (2007), “Catalyst influence in low formaldehyde flame retardant finishing system”, 7th AUTEX Conference, Tampere, pp. 60-1.
Flincˇec Grgac, S., Katovic´, D., Bischof Vukusˇic´, S. (2007), “Combination of organophosphorus agent and citric acid in durable press finishing of cellulose fabrics”, XX. Croatian Society of Chemical Engineers, Zagreb, Croatia, p. 281. Bischof Vukusˇic´, S., Flinecˇ Grgac, S., Katovic´, D. (2007), “Antimicrobial textile treatment and problems of testing methods”, Tekstil, Vol. 56, accepted for publication.
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University of Zagreb Faculty of Textile Technology, Prilaz bazuna Filipovic´a 30, HR-10000 Zagreb, Croatia. Tel: +385 1 48 77 359; Fax: +385 1 48 77 355; E-mail:
[email protected] Principal investigator(s): Prof. Ðurdica Parac-Osterman, PhD Research staff: Martinia Ira Glogar, PhD; Assist.Prof. Darko Golob, PhD; Assoc. Prof. Marija Gorensˇek, PhD; Assoc. Prof. Darko Grundler, PhD; Assoc. Prof. Nina Knesˇaurek, PhD; Prof. Nina Rezˇek-Wilson; Assist.Prof.Tomislav Rolich, PhD; Ana Sutlovic´, M.Sc; Vedran Ðurasˇevic´ BSc
Colour and dyestuff in processes of ecologically acceptable sustainable development Other Partners: Academic
Research register
Industrial
University of Ljubljana and Maribor, Jadran Stockings Factory Slovenia Project start date: 1 January 2007 Project end date: 31 December 2011 Project budget: N/A Source of support: Ministry of Science, Education and Sports, Republic of Croatia Keywords: Dyestuff selection, Nano-technology, Optimizing dyeing process, Purifying and decolouring wastewaters, Colour management, Fuzzy logic Scientific contribution to sustainable development relies on unlimited support of basic, developing and employable research. Therefore, selection of multi-functional dyes (UV protection, antibacterial protection, micro capsules of multi-functional performance), applying nano-technology in the dyeing processes with the aim of preventing water contamination, development of new methods as well as purifying dyed wastewaters contribute to sustainable development. Both input and output parameters of water will be controlled throughout the entire dyeing process: amount of residual dye in dye-bath using Lamber-Beer absorption model; X, Y, Z standard spectral characteristics of colour defined by specific absorption coefficient SAC and water quality defined by BOD5, COD, TOC, AOX, electrical conductivity and other defining values. System of control comprising advance models of control such as fuzzy logic (model based on rules) and model based on physical and chemical processes will be developed and applied. Capital area of research will involve models of dyeing processes, colour control and its correlation to dye as well as the interactive system of dye control. Models
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should describe and predict kinetics, reactivity, affinity, exhaustion, fixation and interaction of solutions containing various dyestuffs. Prediction of output process result as well as definition of both physical and chemical parameters crucial for controlling the process will be conducted based on afore-mentioned models. These models encompass kinetic models (according to Nernst and Langmuir) modified for interactions between dyestuff on fibre and in the solution. Interdisciplinarity of dye within the system of sustainable development is based on spectral characteristics of colour as the fundament model dependent of the employment conditions. Instrumental measurement of colour is involved in all industrial production processes: textile technology, design, graphic industry and elsewhere which enables implementing control and colour harmonization. Application of evolutionary algorithms for modeling computer aided design of textiles based on principals of examinee’s subjective evaluation. Methods of descriptive statistics as well as methods of statistic reasoning will be applied within the frame of statistic analysis. Scientific affirmation of research results will be computer simulation as well as in vivo confirmation.
Aims and objectives Contribution to sustainable development relies on unlimited support of basic, developing and employable research. Aim of the project is to contribute to humane ecology (regarding UV, antibacterial and other protective properties), through use of multifunctional dyes and selection of appropriate waste water discoloration and purifying methods, all in order of obtaining biological quality of water (free of toxic, aromatic components which may form in the process of dye degradation). Cognition of structure and use of thermo sensible nano sized dyes will enable their use on fibres for special purposes. Advance dyeing technologies, with the overview on pretreatment of textile substrates (enzymatic, plasmatic and other) in order of preserving environment and saving energy, will be applied. Base of the project is application of dyeing process control, including advance models of control; fuzzy logic and model based on physico-chemical processes. Colour used as constant value will be applied for formation of fuzzy logic model, used for complex colour designing, automatic dye selection, direct transfer of colour coordinates data into the dyeing recipe setup system, advance recipe correction, as well as control and colour matching. Project research will enable use of new instrumental methods and development of researcher’s creativity, while graduate students and potential PhD students will be given a chance to get acquainted with scientific methodology, development of experimental skills and writing scientific papers.
Deliverables Influence of dye’s chemical constitution and mode of dye-fibre bond onto antibacterial (e.g. Staphiloccoci, Escherichia), UVA and UVB protection properties. Influence of additives (electrolytes and surfactants) on dyeing process and degree of water pollution. Control of, in dye-bath and wastewaters, present electrolytes – elaboration of mathematical model. Further results considering influence of dye onto protection properties are expected. Application of thermo sensible dyes on children clothing. Influence of textile substrate’s pre-treatment (enzymatic, plasmatic pre-treatment, etc.) on dyeing kinetics and energy saving. Results of wastewater purifying and discoloration methods, with the emphasis
on salt removal using physico-chemical methods, nano filtration and reverse osmosis. Colour as constant value of monitoring process, dye properties and colour matching in design applying evolutionary algorithms. Application of nano size particles. Influence of surfactants onto reactivity, affinity, exhaustion and fixation degree of reactive dyes. Advantages and disadvantages of physico-chemical decolouring methods. Dye degradation products and their toxicity (considering aromatic components) in wastewaters. Selection of dyestuff and its interaction with in the dye-bath present additives. Mathematical model based on measured values will be elaborated, while control system including a model based on physico-chemical processes will be applied. Fuzzy logic model, based on colour as constant value within control system will be worked out. Application of capsulated dyestuff and nano particles of zink and silver for special use (medical textiles). Pre-treatment of hydrophobic, synthetic fibres in the aim of increasing hydrophility and applicability of, in water soluble, dyes. From the economical and ecological aspect, a more acceptable system of purifying and decolouring wastewaters ii expected. Mathematical model based on the analyses of input and output measured values, considering coloured waters, will be elaborated, while a control system using advance models, such as fuzzy logic (model based on rules) and based on physicochemical processes model. Evolutionary algorithms for modelling computer design of fabrics based on principals of subjective assessment. Model must comply with standards, flexible, stabile, precise, and easily applicable. It includes complete process modelling: dyeing, colour control and its relation to dye. These models involve kinetics models (Nernst, Langmuir) modified for dye – dissolved dye. Applying computer colour matching (CCM) methods based on Kubelka-Munk theory, spectral characteristics and colour parameters according to CIEL*a*b*system, a model of fuzzy logic for complex design by colour, automatic dye selection, direct transfer of colour coordinates data into the dyeing recipe setup system, advance recipe correction, as well as control and colour matching, will be elaborated. Evolutionary algorithms for modelling computer design of fabrics based on principals of subjective assessment. Publications and outputs Ðurdica Parac-Ostreman, Ana Sutlovic´, Vedran Ðurasˇevic´ and Tjasa Griessler Bulc, “Use of wetland for dye-house waste waters purifying purposes”, Asian Journal of Water, Environment and Pollution, Vol. 4, No. 1, pp. 101-6. Ðurdica Parac-Osterman, Vedran Ðurasˇevic´, Ana Sutlovic´, “Comparison of some chemical and physical-chemical waste water discoloring methods”, Chemistry in Industry (in press). Martinia Ira Glogar, Darko Grundler, Ðurdica Parac-Osterman, Tomislav Rolich, “Fuzzy logic based approach to textile surface structure influence in colour matching”, AATCC Rewiev (in press). Vesna Tralic´-Kulenovic´, Livio Racane, Ana Sutlovic´, Vedran Ðurasˇevic´, “Dyeing properties of new benzothiazol disperse dyestuff, XX”, Croatian Meeting of Chemists and Chemical Engineers, Zagreb, Croatia, February 26-March 1, 2007. Ðurdica Parac-Ostreman, Nevenka Tkalec Makovec, Ana Sutlovic´, Ljerka Dugan, “Staphylococcus aureus and escherichia coli behavior on undyed and dyed wool, XX”, Croatian Meeting of Chemists and Chemical Engineers, February 26-March 1, 2007, Zagreb, Croatia. Ðurdica Parac-Osterman, Ana Sutlovic´, Vedran Ðurasˇevic´, “Application of wetland system”, Textile Dyes Zagreb 2007, March 9, 2007, Zagreb, Croatia.
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Ðurdica Parac-Osterman, Ana Sutlovic´, Martinia Ira Glogar, “Dyeing wool with natural dyes in light of the technological heritage”, 7th Annual Textile Conference by Autex: “From Emerging Innovations to Global Business”, 26-28 June 2007, Tampere, Finland. Ðurdica Parac-Osterman, Ana Sutlovic´, Vedran Ðurasˇevic´, “Application of wool, CA and PP fibers as filters in wetland pretreatment media formation”, University of Zagreb, Faculty of Textile technology International Conference on Multi Functions of Wetland Systems, Legnaro (Padova), Italy, 26-29 June.
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Zagreb, Croatia Faculty of Textile Technology University of Zagreb, Prilaz baruna Filipovic´a 30, HR-10 000 Zagreb, Croatia. Tel: +38513712500; Fax: +38513712599; E-mail:
[email protected] Principal investigator(s): Prof. Darko Ujevic´, PhD Research staff: Jadranka Akalovic´, BSc; Prof. Jadranka Bacˇic´; Prof. Zoltan Baracˇkai, PhD; Vinko Barisˇic´, BSc; Ing. Iva Berket; Bajro Bolic´, BSc; Blazˇenka Brlobasˇic´ Sˇajatovic´, BSc; Ksenija Dolezˇal, BSc; Mirko Drenovac, PhD; Prof. Milan Galovic´, PhD; Marijan Hrastinski, BSc; Renata Hrzˇenjak, BSc; MD, Natasˇa Kaleboti; Prof. Isak Karabegovic´, PhD; Ivan Klanac, BSc; MD, Irena Kos-Topic´; Prof. Tonc´i Lazibat, PhD; Nikol Margetic´, BSc; Prof. Zlatka Mencl-Bajs; MD, Zˇeljko Mimica; Prof. Gojko Nikolic´, PhD; Alem Orlic´, BSc; PhD, MD, Vedrana Petrovecˇki; BSc M.E. Zˇeljko Petrovic´; Prof. Dubravko Rogale, PhD; Prof. Andrea Russo; Igor Sutlovic´, PhD; Prof. Vlasta Szirovicza, PhD; Irena Sˇabaric´, BSc; MSc, MD, Nadica Sˇkreb-Rakijasˇic´, Marija Sˇutina, BSc; Prof. Larry C. Wadsworth, PhD
Anthropometric measurements and adaptation of garment size system Other Partners: Academic
Industrial
None None Project start date: 1 January 2007 Project end date: 31 December 2011 Project budget: N/A Source of support: Ministry of Science, Education and Sports, Republic of Croatia Keywords: Anthropometric measurements, Garment size system Systematic anthropometric surveys have been conducted since 1901 with the aim of developing and improving systems for clothing and footwear sizes. The measurement results show how a national population changes over a period of several decades in physical build and size due to a series of factors (food habits, sports development, genetic predispositions, population migrations, climatic conditions, etc.). Based on the results of anthropometric measurements in the Republic of Croatia (2004/05) on the sample of 30,866 test persons aged between 1 and 82 a statistical
analysis of body measurements was performed, a database including 5 basic studies of sex and age as well as a new standard for clothing and footwear was built. These results enable a significant and stimulating continuation of scientific research and a comparison to other national standards and their contributions to the creation of systems for clothing and footwear sizes. Elements common for national standards of garment sizing by an exact approach will be investigated and analyzed, in particular because the presumptions of national systems and starting elements, respectively, are not universally founded like intersize intervals which differ in sizes since the conformity of individual starting places is missing. Data will be provided for a common base with methods of body measuring and size designation of clothes according to the recommendations of the Technical Committee TC133 within ISO and EN standards as well as the design and development of a sophisticated computer system (DOV-KO) for unifying all body measurements and basic garment construction based on one or all other sizes. Within the scope of this project and based on experience, a very important cycle of anthropometric measurements of the sporting population in football, water polo, rowing, basketball and handball will be performed. 4,000 test persons from Zagreb, Osijek, Rijeka, Split and Dubrovnik will be measured, whereby specific body differences and deformations of muscles caused by longstanding training will be analyzed. A comparative analysis of the representative sample of the anthropometric measurements of sportsmen and other population as well as the investigation of other trends of body measurements will be performed. This will enable an exceptional insight into the anthropometric dimensions which reflect body shape, proportionality, composition and elements of success in sports, respectively. Stadiometar or a new measuring instrument for continuous measuring body height, foot length and width will be designed too.
Aims and objectives Problems of garment sizing and fit affect the market globally, and a consequence of bad predictions of the quantity of necessary stocks for manufacturers and dealers poses a risk of high costs. In the case of domestic manufacturers samples may be additionally divided. Particular solutions may be considered more efficiently by interpreting the data from the anthropometric database connecting 5 studies according to sex and age and the system of sizing. Therefore, using the results of the anthropometric measurements taken and the basic projection of the new standard for clothing and footwear, one of the directives of the project is to investigate other national standards of Europe and the world and to create size intervals and a new Croatian standard. The study of body differences and specific deformities of the body muscles during the longstanding practice of athletes such as leg circumference, chest circumference, torso, shoulder width, arm and leg length, body height, palm length is an additional aim of this project which will show the body elements affecting success level in sport. Besides a greater adaptation of clothing and footwear to the home market, it would be advisable to ensure the continuity of investigating the national size standard by creating a sustainable Croatian system of clothing and footwear sizes in conformity with anthropometric surveys that are conducted periodically and systematically in developed
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countries in which a change in the morphology of the human body occurred over the last decades. By way of proof, systematic anthropometric measurements and sizing in France showed a tendency of average height growth. In Great Britain in female population a growth of bust circumference was recognized, whereas in USA studies point to the tendency of an increase in obesity (besides an aesthetic also a health problem). The interest of the scientific and professional public, manufacturers, tradespeople and consumers in sizing will continue to grow, since a faster change in established body proportions may be expected thanks to changes in living and food habits of the population, an unavoidable mingling of ethnic groups, increase in the number of older consumers of clothing and footwear which will be doubled in the next two decades, etc. Thus, it is additionally stressed how much it essential at the moment to ensure a valid starting point or a Croatian standard to pursue next movements of body dimensions in order to avoid a discrepancy and imposition of the specificities of domicile consumers to home and foreign manufacturers.
Deliverables Anthropometry is the study of the measurement of the human body, but Pheasant has expanded it as “applied anthropometry” including quantitative data of size, forms and other physical characteristics of people that can be used in garment design. Since the form of the human body changed through time, the problem of ageing proved to make a contribution to perceived changes in body shape and size more than any other individual factor, such as for example improved nutrition and prolonged life, in particular the knowledge that the number of older consumers will be doubled by 2003. Therefore, the systems of sizing shall be updated periodically to ensure a correct fit of ready-made clothing. On the other hand, the home industry of clothing, fashion wear and footwear disposes of modest and aged data based on the out-of-date anthropometric measurements from 1962. It was therefore necessary to conduct a new cycle of anthropometric measurements and to use the obtained results. World fashion industry shows a special interest in measuring anthropometric characteristics of the population so that it gathers such data permanently, motivated by the wish for designing articles of clothing for all population groups, including the persons with pronounced specificities (higher stature, higher body weight, etc.). The use of investigations will contribute to creating a new and modern Croatian standard for clothing and footwear harmonized with ISO and EN standards. Besides the clothing and footwear industry, pediatricians, specialists of occupational and sports medicine, experts in wood processing industry, automotive industry, in the army and police will benefit from the investigation results. Teachers and students in undergraduate and graduate studies as well as teachers and pupils at technical schools will benefit from the development results of the computer system based on the selection of garment sizes. By using the investigations of the sporting population, one can get an insight into tendencies of diversities of body measurements and changes in muscles as a result of longstanding practice. Various specialists of sports medicine, orthopedists, garment and footwear designers will benefit form the results of this investigation because based on previous experience it is evident that mass customization is necessary for athletes. Knowing dimensional characteristics, this method would be considerably promoted and improved.
Publications and outputs Ujevic´, D., Rogale, D., Hrastinski, M., Drenovac, M., Szirovicza, L., Lazibat, T., Bacˇic´, J., Prebeg, Zˇ., Mencl-Bajs, Z., Mujkic´, A., Sˇutina, M., Klanac, I., Brlobasˇic´ Sˇajatovic´, B., Dolezˇal, K., Hrzˇenjak, R., (2006), “Normizacija, antropometrijski pregledi i Hrvatski antropometrijski sustav”, Tekstil, Vol. 55, No. 10, pp. 516-26. Ujevic´, D., Firsˇt-Rogale, S., Nikolic´, G., Rogale, D. (2006), “Pregled razvojnih dostignuc´a u tehnologiji sˇivanja – IMB 2006”, Tekstil, Vol. 55 No. 12, pp. 624-31. Ujevic´, D., Dolezˇal, K., Lesˇina, M. (2007), “Analiza antropometrijskih izmjera za obuc´arsku industriju”, Poslovna izvrsnost, Vol. 1 No. 1, pp. 171-83. Ujevic´, D., Hrzˇenjak, R., Dolezˇal, K., Brlobasˇic´ Sˇajatovic´, B. (2007), “Hrvatski antropometrijski sustav – jucˇer, danas, sutra”, HZN Glasilo, Vol. 3 No. 1, pp. 5-10. Hrzˇenjak, R., Ujevic´, D., Dolezˇal, K., Brlobasˇic´ Sˇajatovic´, B. (2007), “Investigation of anthropometric characteristics and body proportions in the Republic of Croatia”, Proceedings of 7th Annual Textile Conference by Autex, Tampere, Finland, 25-28 June, pp. 1191-8. Ujevic´, D., Brlobasˇic´ Sˇajatovic´, B., Dolezˇal, K., Hrzˇenjak, R., Mujkic´, A. (2007), “Rezultati prvog antropometrijskog mjerenja stanovnisˇtva Republike Hrvatske”, Drugi kongres hrvatskih znanstvenika iz domovine i inozemstva, Split, Croatia, 5-10 May. Nikolic´, G., Ujevic´, D. (2007), Protractor for Measuring Shoulder Slope, Patent. Ujevic´, D. (2007), One-arm and/or two-arm anthropometer, Patent.
Zagreb, Croatia Faculty of Textile Technology, University of Zagreb, Prilaz baruna Filipovic´a 30, HR-10 000 Zagreb, Croatia. Tel: +385 1 48 77 352; Fax: +385 1 48 77 352; E-mail:
[email protected] Principal investigator(s): Prof. Drago Katovic´, PhD Research staff: Asoc. Prof. Sandra Bischof Vukusˇic´, PhD; Prof. emeritus Ivo Soljacˇic´, PhD; Dubravka Dosˇen Sˇver, PhD; Sandra Flincˇec Grgac, BSc; Asoc. Prof. Radovan Despot, PhD; Asist. Prof. Jelena Trajkovic´, PhD; Asist. Prof. Branka Lozo, PhD; Luka Cˇavara, MSc; Bozˇo Tomic´, M.C.; Prof. Charles Yang, PhD; Prof. Christian Schram, PhD
Alternative eco-friendly processing & methods of cellulose chemical modification Other Partners: Academic
Industrial
Faculty of Forestry, Croatia; Faculty of Cˇateks, d.d., www.cateks.hr Graphic Art, Croatia; University of Georgia, USA; University of Innsbruck, Austria Project start date: 1 January 2007 Project end date: 31 December 2011 Project budget: N/A Source of support: Ministy of Science, Education and Sports, Republic of Croatia
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Keywords: Multifunctional eco-friendly textile finishing, Polycarboxylic acids, Protective functionalities, Chemical modification of cellulose, Microvawe treatment of cellulose materials One of the requests of European Union for higher competiteveness of European market is rebuilding and reconstruction of traditional industrial sectors, especialy textile and wood industry. According to the strategical goals of the Republic of Croatia the project emphasizes the use of highly sofisticated production processes and treatments of cellulose materials, i.e. obtaining additional and improved characteristics of wooden and paper matherials which can be acchieved by using high-tech processes and by introduction of nano- micro- and bio-technologies. One of the alternative methods for replaciong the conventional reactants containing formaldehyde which were used in textile and wood treatments so far, would be the modification with eco-friendly agents such as polycarboxylic acids. Efficiency of these treatments will be determined quantitatively by ester crosslinking analytical methods or by means of isocratic HPLC and spectrophotometric FTIR method. Standard methods of textile, wood and paper material testing would be used for examining their protective performance and resistance to weathering conditions. Part of the proposed project will be development of optional multifunctional treatment that would provide better protection of cellulose materials against microorganisms, UV, electromagnetic rays, flame, oil or water. Therefore, a particular attention will be payed to development and application of the agents which will not only improve the characteristics of textile matherials but also give it permanent freshness and provide additional care and protection, i.e. medical characteristics. Optimisation of alternative processing and methods will provide ecologically and economicaly favorable characteristics of treated matherials. Further process optimisation in order to improve processing quality could be obtained with new alternative method using microwave energy. Improved characteristics obtained with this method in our previous research confirm its usability in textile finishing processes as well as in chemical modification of wood. Previous research in this field represent worlwide novelty which should be by all means continued.
Aims and objectives The purpose and aim of the proposed project is to obtain highly valuable and multifunctional treated textile materials that will acquire analogous price on the demanding market. This is the basic condition for the survival of Croatian textile, wood and paper industry on EU market. In textile area experiments will be conducted to obtain multifunctional environmentally friendly textile material which will simultaneously offer dimensional stability, flame retardancy, crease and antimicrobial resistance and will have no effects on human health. Further goal is to obtain chemicaly modified wood that will have reduced shrinking and water absorption as well as to obtain flame retardancy on wood and paper products. One of the equally important goals is construction of a semi industrial microwave device for continuous planar treatment of cellulose materials. The results obtained would be presented in the world best known papers in the relevant field. The most important goal of the project is affirmation of Croatian science in Europe and rest of the World, by presenting the results in international papers so as on
International Conferences. It is important to stress that established cooperation with EU and USA experts, so as with their scientific institutions will be continued and expanded. In this project, where will scientists from abroad have an active contribution with their work, further contribution to development of high quality products will be added. We certainly hope it will affect development of Croatian industry and economy.
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Not available. Publications and outputs Katovic´, D., Bischof Vukusˇic´, S., Flincˇec Grgac, S. (2007), “Crosslinking cotton with citric acid and organophosphorus agent for the purpose of flame retardant finishing”, 85th Textile Institute Conference, Colombo, Sri Lanka, pp. 820-24. Bischof Vukusˇic´, S., Flincˇec Grgac, S., Katovic´, D. (2007), “Catalyst influence in low formaldehyde flame retardant finishing system”, 7th AUTEX Conference, Tampere, pp. 60-61. Flincˇec Grgac, S., Katovic´, D., Bischof Vukusˇic´, S. (2007), “Combination of organophosphorus agent and citric acid in durable press finishing of cellulose fabrics”, XX. Croatian Society of Chemical Engineers, Zagreb, Croatia, pp. 281. Bischof Vukusˇic´, S., Flinecˇ Grgac, S., Katovic´, D. (2007), “Antimicrobial textile treatment and problems of testing methods”, Tekstil, Vol. 56 (in press).
Zagreb, Croatia Faculty of Textile Technology, University of Zagreb, Prilaz baruna Filipovic´a 30, HR-10 000 Zagreb, Croatia. Tel: +385 1 4877 360; Fax: +385 1 4877 355; E-mail:
[email protected] Principal investigator(s): Prof. Ana Marija Grancaric´, PhD Research staff: Assoc. Prof. Tanja Pusˇic´, PhD; Assist. Prof. Zˇeljko Penava, PhD; Anita Tarbuk, M. Sc., Lea Markovic´, B. Sc., Assist. Prof. Jasenka Bisˇc´an, PhD; Sonja Besˇenski, M. Sc., Ivancˇica Kovacˇek, PhD, D. Med., Prof. Djamal Akbarov, PhD, Prof. Emil Chibowski, PhD, Prof. Rybicki Edward, PhD, Prof. Eckhard Schollmeyer, PhD, Prof. M.M.C.G. Warmoeskerken, PhD
Interface phenomena of active multifunctional textile materials Other Partners: Academic
Research register
Industrial
Croatian National Institute of Public Health, Zagreb; Tashkent Institute of Textile and Light Industry, Uzbekistan; Maria Curie-Skłodowska University, Lublin, Poland; Technical University of Lodz, Poland; Deutsches Textilforschungsinstitut Nord-West eV; Institut der Universitat Duisburg Essen; University of Twente, Netherlands Pamucˇna industrija Duga Resa, Duga Resa Project start date: 1 January 2007 Project end date: 31 December 2011
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Project budget: N/A Source of support: Ministry of Science, Education and Sports, Republic of Croatia Keywords: Textile material, Interface phenomena, Surface modification and finishing, Multifunctionality The goal of the project is synergistic effects of some compounds on modified textile surfaces for achieving multifunctionality of textiles. Interface phenomena of textile surfaces with special accent on surface free energy, zeta potential, electroconductivity, adsorption and desorption of surfactants and other compounds usually used in textile finishing will give a great contribution to multifunctionality of textile. The mechanism of adsorption and desorption of surfactants and other finishing agents on modified textile surfaces is expected to be clarified in the present project. Different surface modifications, pretreatment and finishing of textile, especially cotton and polyester, will be performed according to European Technology Platform for the future of textile and clothing. For such purpose advance processes like mercerization, cationization, alkali, EDTA, other compounds and enzymes for surface hydrolysis of PET fabric, optical bleaching, implementation of nano antimicrobial active silver ions and mineral delivery mechanism, zeolite and others will be performed. Aminofunctional and other compounds will be added to azalides for the synergistic high antimicrobial effects. In cotton pretreatment enzymatic scouring will be applied using enzymes pectinase and the newest cutinase, for removal of pectins and bioplymers from cotton impurities with lipophylic character, instead of ecologically unfavorable alkali scouring. The goal of the project is synergistic effects of some compounds on modified textile surface. Interface phenomena of the new textile materials produced from electroconductive, low electro resistance fibers will be investigated for the purpose of static electricity and electromagnetic protection and for its implementation as sensors or other electronic devices in intelligent textiles. Traditional protection and aesthetic role of textile will be spread in active textile multifunctionality. Project will deal with elektrokinetic phenomena (zeta potential, isoelectric point, IEP, point of zero charge, PZC, surface electrical charge, surface free energy), hydrophility and hydrophobilicity, whiteness, fluorescence and phosphorescence, friction, fabric cover factor, elasticity, air and water vapor permeability of textile materials and their protection on UV radiation, microbes and fungi, coldness, heat and flame, static electricity and electromagnetic field.
Aims and objectives Project will continue researching on assignments from previous project (0117012). Purpose of these investigations is based on lightening of interface phenomena on textile which effect directly to its adsorption and interaction intensity between textile fibers and chemical compounds. Almost all possibilities in modification during manufacturing high performance synthetic fibers are used, therefore nowadays attention and research is on textile surface modification. Procedures and compounds for that modification varies, as their effect varies, but the purpose and aim are directed to synergism of two or more components for accomplishing hydrophob or hydrophil textile, textile highly resistant to atmospheric condition, bacteria, microbe and fungi, UV radiation and open flame. Furthermore, important aim of the project is cotton high level of purity by unconventional agents and material pretreatment procedures for mercerization and
cationization. Pectinase in previous project investigation showed good elimination of pectine from primary cotton layer, but hydrophility was not so high like alkali scoured cotton. Chemical composition of cotton cuticula has lypophilic polymers, biopolyesters, which can be degraded by cutinase, new enzymes for degradation of waxes for better hydrophility. Cotton cationization during mercerization is the most important innovation of previous project and the patent for it was asked. Electronegative cotton surface charge, of which anionic substances adsorption depends, is lower after cationization in harsh mercerization conditions. The aim of this project is antibacterial, UV and flame protection by nanoparticle implementation (Ag) using mineral delivery compound (zeolite and others) as well. Electroconductive fibers implementation in yarns of textile materials should result in static electricity removal, and hopefully other effects. The aim of polyester surface modification, optical bleaching, other compounds treatments is well-known aesthetic, as well as high UV protection, high material elasticity as a result of changes in fiber microstructure. Interface phenomena research on wide range possible fabric knitted and woven construction will givethe solution of problems of fabric construction influence to high effect in this project.
Deliverables Interface phenomena of textile materials surface in wet medium results in textile electric surface charge cognition and surface free energy as well on which adsorption depends. Important application of this project results is in ecological enzymatic scouring with pectinases.Enzymatic scouring with new enzymes, cutinase, will remove biopolyester cuticula and improve cotton hydrophility, and therefore replace harsh conventional alkali scouring entirely. Important application will have, patent requested cotton cationization during mercerization. By this pretreatment electropositive cotton is achieved, with great anion adsorption on its surface in all textile finishing processes. These anions enclose all low and high molecular compounds for textile finishing and all pricondensates. Implementation of nanoparticles (Ag and others) is predicted during mercerization and cationization processes, therefore it is important to emphasize rational component of these procedures which gives cotton multifunctionality in all textile usage. The next important application is antibacterial textile accomplished with azalide treatment especially in synergism with aminofunctional and other compounds and systems. It is well-known that fluorescence of optically bleached increases whitening of textiles. Optical brighteners and other compounds researching will be of great importance in UV protection with textile material. Heavy metals are toxic and their research is of great importance in human health protection. Furthermore, in nowadays growing demands on life safety from external influences especially UV radiation, research of differently structured textile material interface phenomena will find application in textile for summer clothing. Publications and outputs Grancaric´, Anamarija, Pusˇic´, Tanja, Tarbuk, Anita, “Enzymatic scouring for better textile properties of knitted cotton fabrics”, Biotechnology in Textile Processing, Guebitz, Georg, Cavaco-Paulo, Artur; Kozlowski, Rysard (Ed.), New York: The Haworth Press, Inc., 2006. Grancaric´, Ana Marija, Tarbuk, Anita; Dumitrescu, Iuliana, Bisˇc´an, Jasenka, “UV protection of pretreated cotton – influence of FWA’s fluorescence”, AATCC Review, Vol. 6 (2006), No. 4, pp. 2-6. Anita Tarbuk, Ana Marija Grancaric´, Volker Ribitsch, “Electrokinetic phenomena of textile fibers”, Book of abstracts XX.Croatian meeting of Chemists and Chemical Engineers 2007, 301.
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Ana Marija Grancaric´, Lea Markovic´, Anita Tarbuk, Eckhard Schollmeyer, “Properties of multifunctional cotton in accordance with international standards”, Conferece of Textile Days, Zagreb 2007. Ana Marija Grancaric´, Anita Tarbuk, Ivancˇica Kovacˇek, “Micro and nanoparticles of zeolite for the protective textiles”, Book of Proceedings of 7th Annual AUTEX Conference, AUTEX 2007, P-1123, Tampere, Finland. Anita Tarbuk, Ana Marija Grancaric´, Mirela Leskovac, “Surface free energy of pretreated and modified cotton woven fabric”, Book of Proceedings of 7th Annual AUTEX Conference, AUTEX 2007, P-1104, Tampere, Finland.
Research index by institution
Index by institution
Institution
Page
Ghent University
11-32
Heriot Watt University
6, 7
Hong Kong Polytechnic University
32
Jiangnan University
63
Laoughborough University
48
Manchester metropolitan University
50
Nottingham Trent University
58
Sci-Tex
60, 62
Technical University of Lodz
34-48
University of Maribor
8, 50-58
University of Zagreb
64-87
University Polytechnic of Catalonia
62
89
Research index by country
IJCST 23,6
90
Country
Page
Belgium
11-32
China
63
Croatia
64-87
England
48, 49, 58
Japan Hong Kong Poland
61, 62 32 34-48
Scotland
6, 7
Slovenia
8, 50-58
Spain
62
Research index by subject Anthropometric measurements, Garment size system
80
Air jet loom, Weft preparation system, Speed increase
28
Biodegradability (Polymers, Textiles, Non-fibrous products, Non-wovens)
42
Bio-textiles, Biotechnology
11, 14, 16, 26, 42
(Garments, Insect repellent, Slow release, Bioengineered cotton fibres, Self assembling peptides, bio-functional, Enzymes, Grafting, Fictionalisation, Surface modification, Biopolymer, Nano-structuring, Biodegradability, Non-fibrous products, Non-wovens) Care and Wellness (Finishing of textiles, Harmful substances, Toxicological and allergenic properties, Environmental protection, Hygiene, Protective textiles, Multi-functionality, Smart textiles, Ceramic coatings, Sol-gel process, Multifunctional eco-friendly textile finishing, Polycarboxylic acids, Protective functionalities, Chemical modification of cellulose, Microwave treatment of cellulose) Carpet wear, Evaluation, Image processing Cotton (Bioengineered, Sirospun, Fibres, Yarns)
Fabric mechanics, Clothing, Behaviour, Comfort, Prediction
50
Fibre composites, Renewables
19
Hollow fibre-water absorption - PP
24
HP materials, Textile fibres, Textile design
67
Medical, Cosmetics, Clothing
62
Nanotechnology
69, 72, 75
6
47, 48, 49, 64, 69, 72, 75 (Protective gloves, Basalt fibres, Hot workplaces, Design principles, Compression, Impact protection, Comfort, Physiological load, Sensors, Cooling systems, Intelligent garment, Thermal protection, Environment) Protective clothing
14, 18, 31
17, 20, 23, 26, 27, 29, 53, 77
(Nanofibres, filters, Decubitus, Electrotherapy textiles, Flame retardants, Nanoclays, Biotechnology, Enzymes, Grafting, Fictionalisation, Surface modification, Biopolymer, Nano-structuring, SMI nanoparticles, Imidisation, Surface properties, Water filtration, MBR, Dyestuff selection, Optimizing dyeing process, Purifying, Decolouring, Wastewaters, Colour management, Fuzzy logic) Photovoltaics Thin-film silicon, Solar energy, Textile fabrics
20
Index by subject
91
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92
Research (Research infrastructure, Laboratory, Textiles, Clothing technology, Modelling, Rapid machine setting, Simulation, Physical behaviour, Online process, Artificial intelligence, FEM models) Synthetic ropes, Dynamic behaviour
32, 34, 38
Technology transfer, Textiles, Networking, Innovation Water treatment (Industrial water, Paper, Food, Chemistry, Modelling, Water quality, Water pollution, Water treatment, Wastewater effluent)
27
Technical textiles 53, 61, 62, 85 (Selective filters, Cyclodextrins, Host-quest molecules, Textile surface modification, Nanoencapsulation, Toxic degradation products, Persistent organic pollutants, Phenols, Aromatic amines, Formaldehyde, Textile dyes, Wastewater, Recycling, Advanced oxidation processes, Textile wastewater treatment, Technical textiles, Surface modification, Multi-functionality)
22, 25 9, 53, 56
Wireless 7, 21, 30, 45, 58 (Smart, Interactive, Garment, Clothing, Textile antennas, Music, Stretchable electronics, Smart textiles, E-textiles, Wearable micro systems, Wearable electronics, Textile electrodes, Textronics, Electro stimulation, Human muscles, Fabric antennas, Digital embroidery, Conductive fabrics, Textile sensors) 3D Fabric (Composites, Binder yarn, Mechanical Property, "8" Shape)
12, 63
Research index by principal investigator Principal investigator
Page
Alenka Majcen Le Marechal 9, 53, 56
Maja Andrassy
67
Mather, P.R.
Canal, J.M.
63
Tatsuki Matsuo
Karen De Clerck
13, 15, 16, 17, 18, 25, 29
Dias, T.
58
Iwona Frydrych
47
Jelka Gersˇak
50
Krzysztof Gniotek
45
Ana Marija Grancaric
85
Havenith George
48
Liu Jihong
63
Drago Katovic Kiekens, P. Ryszard Korycki Izabella Krucin´ska, Leman
75, 83 22, 24, 25, 26, 27 34 38, 42 30
Index by principal investigator
Ðurdica Parac-Osterman
6 61, 62 77
Emira Pezelj
72
Ivelin Rahnev
31
Dubravko Rogale
64
Ivo Soljacˇic´
69
Stylios. G.K.
7
Tyler, D.J.
49
Darko Ujevic
80
Vanfleteren
30
Van Langenhove Lieva Philippe Westbroek Wilson, J.I.B. Tao Xiaoming
12, 20, 21, 28, 30 16, 17, 19 6 32
93
So, for indicating the visco-elastic behavior modeling is utilized by the use of spring composition for showing elastic character and dashpot, for showing viscous character. Hezavehi et al. (2008) presented a new way in which they could study the torsional behavior of worsted fabric in different angles in accordance with different torsional rated. They found out the extension of torsional force depended on the increase of torsional angle. They also perceived that the varieties among materials are more visible from 32 angles. Gersak et al. (2005) focused on the study of the relaxation phenomena of fabrics containing elastane yarn. In there, Maxwell’s model and the modified standard linear solid model were used for explaining the relaxation. Shaikhzadeh Najar et al. (2009) studied the wrinkle parameters of worsted fabrics included. Force, energy, hystersis and resilience were in regards to the varieties of fabrics. They recognized that the wrinkle parameters in alignment of warp are completely different from the alignment of weft. In this method, the amounts of force, energy and resilience in alignment of warp are more than weft. But wrinkle hystersis in a cycle of to and fro in alignment of weft is more than warp. They also perceived that the parameters of wrinkle worsted fabric depended on the visco-elastic properties which belonged to consumed fiber. Also, with the extension of polyester percentage in worsted fabric, the amount of force, energy of wrinkle is considerably increased. Chapman (1974a, b, 1976) studied the function of visco-elastic properties fiber from wrinkle recovery. In this regard, he presented a reological model including a linear visco-elastic element that is parallel to a frictional element. He believed that the behavior of visco-elastic fiber is depended on bending moment and fibers friction. Denby (1974, 1980) believes that if woven fabric is bended in the axis of warp or weft, the force applied curvature on each fiber is approximately equal to the forced applied curvature on the whole fabric. Thus, he believes the recovery of fabrics from wrinkling can be calculated through the knowledge of stress relaxation. Knowing mechanical properties are very important for the consumer, in predicting the final behavior and interval usage of the texture. Mechanical property depends on (Popper, 1966) some factors such as fiber, yarn, structure of fabric and its internal relationship. However, there is no information available to study the stress relaxation of worsted fabrics under the combined influences of compression and torsional strains. In the last few years, a number of researchers also did similar work in this field. Abghari et al. (2004) considered the contributions of in-plane fabric tensile properties in bagging behavior of woven fabrics using a new test method. Maklewska et al. (2007) described new measuring device designed fore measuring the pressure exerted by textile products used in healing therapy of hypertrophic scars. The testing device called “textilpress” has been used for verification of the usually used method of designing and manufacturing ready-made compression garment products. The aim of this paper is the analysis of the stress-relaxation behavior of the different worsted fabrics under constant torsional strain in wrinkled state. For this purpose, a new method for determination of stress-relaxation behavior of the fabric was used while keeping the torsional strain constant. 2. Experimental 2.1 Materials Different worsted fabrics with twill structure were used in this study. The general fabric specifications are shown in Table I. All experiments were performed under the standard conditions of 22 ^ 28C and 65 ^ 2 percent r.h.
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Table I. Fabric general specifications
Fabric Construction A B C D E F G H I J K L M
T2/2 T2/1 T2/1 T2/1 T2/1 T2/1 T2/1 T2/1 T2/1 T2/1 T2/1 T3/1 T2/2
Yarn density Weight Thickness Fiber content (%) (g/m2) Picks/cm Ends/cm (mm)
Yarn count (Tex) 50 50 50 50 42 42 42 33 33 33 33 33 33
45w 45w 20w 7w 45w 30w 38w 20w 35v 7w 20w 45w 45w
55p 55p 80p 93p 55p 70p 55p, 7v 80p 65p 64p, 29v 80p 55p 55p
268 256 260 233 222 229 231 221 192 195 213 225 195
18 18 18 19 21 19 20 19.5 24 25.5 22 26 22
29 29 28.5 32 29 31 29 28.8 27 31 36 34.5 34
0.686 0.664 0.586 0.67 0.57 0.6 0.58 0.67 0.475 0.57 0.543 0.59 0.48
Notes: w, wool; p, polyester; v, viscose; T, twill
2.2 Experimental setup To investigate the relation of fabric torsional strain properties with woven fabric stress relaxation behavior, a new test method is developed. A photograph of the stress-relaxation tester is shown in Figure 1. A schematic control block diagram of stress Stepper Motor
Spiral Shaft
Driving Gear
Active Gear
Sample
Load Cell
Figure 1. A photograph of the stress relaxation tester
Note: Modification wrinkle tester Source: Shaikhzadeh Najar et al. (2009)
relaxation tester is also shown in Figure 2. The stress-relaxation tester includes of two main electrical and mechanical parts. 2.3 Electrical Includes load cell (Model BONGSHIN, Type DBBP-S-Beam, 20 kg), stepper motor (Model Sanyo Denki, Type 103H 89222-6341, 22 kg · cm), and intermediate board and also a computer as external equipment in order to send the information and also receiving and displaying them. Micro controller receives voltage from load cell and converts it to digital information so a 12 bit, A/D is being used with this regard. Micro controllers through their continuous connections with the computer, besides sending the detected driving force from load cell, runs the stepper motor according to the received comments from the computer. Lab view 6 software (National Instrument Co.) is used for data showing and controlling. This program is able to run system on various speeds and moving upper textile jigsaw down by screwing movement (down jigsaw is fixed) considering to the ability of mentioned software the measurement possibility of screwing stress-relaxation percentage is available both in stress relaxation and unwrinkling positions. Moving speed is (4 step/s) and the movement direction is clockwise compare to the textile wrinkle. The exactness is 1 g on force measurement, 0.8 mm for screwing movement and 0.4 mm on vertical direction.
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2.4 Mechanical Fabric by 290 £ 160 mm dimensions is being wrapped between the two jigsaws which the up one is moving and the down one is fixed. In this research, we used a spiral shaft
Load Cell
Serial Port of the Computer
Main I/O Control Board
Power Supply
Stepper Motor Drivers
Stepper Motor
Figure 2. A schematic control block diagram of stress relaxation tester
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with spiral angle of 32.148, in order to apply torsional strain that its characteristics are shown in Table II. A typical diagram of the stress relaxation against torsional strain for 300 s is shown in Figure 3. The experimental results of fabric stress-relaxation values were statistically analyzed using ANOVA and multiple range test methods. The experimental results of fabric stress-relaxation percentage test is shown in Table III. A new parameter named as the stress-relaxation percent for warp and weft directions defined as equation (1): Stress relaxation % ¼
TMax2 TMin £ 100 TMax
Shaft specification
Table II. Spiral shaft specification
Figure 3. A typical diagram of the stress relaxation for fabric type D in warp direction
Total effective length (mm) Number of rotation turns through out the effective length External diameter (mm) Pitch (mm) Spiral angle (degree) Rotational levels (turn/m)
Note: Lab view software ver 6 online measurement
ð1Þ
Number of shaft 1 110 1 22 110 32.4 9.10
Fabric
Stress relaxation SD Weft direction (%)
SD
1.24 1.01 0.7 4.66 1.46 0.65 2.24 1.31 0 1.27 2.64 1.14 3.25
1.18 1.8 0.93 1.85 2.16 1.96 0.58 1.03 0 0.52 2.37 2.64 1.33
Warp direction (%)
A B C D E F G H I J K L M
26.95 29.60 21.77 23.07 30.16 29.16 36.32 27.14 100 35.85 30.26 37.22 46.11
29.09 57.70 28.85 29.36 34.85 33.24 86.6 31.97 100 38.28 36.63 38.35 64.62
Note: Mean value
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Table III. The experimental results of the stress-relaxation
The output data online are transferred to a PC using the data acquisition system. To store and analyzed the data, special software is developed using Lab view ver 6 programming. Note: the stress in shell equal equation (2): T 2prt where: T, torsional force; r, radius; and t, thickness. Stress ¼
ð2Þ
3. Results and discussion 3.1 The effect of fabric type on stress-relaxation percentage along warp and weft alignment The statistical analysis results of stress relaxation in 5 percent confidence limit for different worsted fabrics are shown in Tables IV-VII. The variation of these stress-relaxation percent along two warp and weft directions is also shown in Figure 4. As shown in these tables, fabric type has significantly influenced on stress relaxation along two warp and weft directions. Tables VI and VII compare and classify the stress relaxation along warp and weft directions according to fabric type. It is shown that in warp direction A, D and C have the least stress relaxation and the fabrics of I, M and L have the highest stress-relaxation, which in regard to the analysis of wrinkle force behavior these fabrics endure the highest and lowest wrinkle force, respectively. Also fabrics of C, D have higher quantity of polyester in comparison to standard worsted fabrics and in terms of thickness, they are thicker.
Between groups Within groups Total
Sum of squares
df
Mean square
F
Sig.
24,408.538 156.868 24,565.406
12 52 64
2,034.045 3.017
674.265
0.000
Table IV. Analysis of variance of stress relaxation percentage in warp direction
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In the same way, I and M fabrics have the lowest wrinkle force and in terms of weight and thickness have the lowest weight and thickness in the weft direction also I, G and M fabrics have the highest stress-relaxation percentage. This is in such a way that these fabrics endure the least wrinkle force and the fabrics of C, A and D have the lowest stress relaxation percentage. These fabrics have a higher endurance of wrinkle force and in terms of thickness and weights are higher than other fabrics; other fabrics lie within these fabrics. 3.2 Fitting the resulting diagrams in Maxwell models A typical diagram of the fitting stress relaxation with lowest correlation coefficient (type D) in one of the Maxwell models is shown in Figure 5, and a typical diagram of the fitting stress relaxation with highest correlation coefficient (type I) in another Maxwell models is shown in Figure 6. In order to achieve this software (curve expert 1.3) was used. The stress relaxation equation of the mentioned diagram is the same as equation (3). Equation (3) is the equation of the Maxwell model. A schematic diagram of Maxwell model is shown in Figure 7: y ¼ aeð2x=bÞ
ð3Þ
Also equation (3) extend for Maxwell model are shown in Table VIII.
Table V. Analysis of variance of stress relaxation percent in weft direction
Table VI. Duncan homogeneous subsets test of stress relaxation percent of worsted fabrics in warp direction according to fabric type (%)
Sum of squares
df
Mean square
F
Sig.
32,919.997 134.678 33,054.675
12 52 64
2,743.333 2.590
1,059.221
0.000
Between groups Within groups Total
Type
n
1
C D A H F B E K J G L M I Sig.
5 5 5 5 5 5 5 5 5 5 5 5 5
21.7740 23.0760
2
26.9500 27.1540 29.1600
Duncana Subset for a ¼ 0.05 3 4
5
6
29.1600 29.6000 30.1620 30.2680 35.8520 36.3280 37.2280 46.1140
0.241
0.062
0.366
0.244
1.000
100.0000 1.000
Notes: aUses harmonic mean sample size ¼ 5.000; mean for groups in homogeneous subsets is displayed
Type
n
1
C D A H F B E K J G L M I Sig.
5 5 5 5 5 5 5 5 5 5 5 5 5
28.8540 29.0940 29.3680
2
3
31.9780 33.2460
Measurement of stress relaxation
Duncana Subset for a ¼ 0.05 4 5 6
7
8
9
395 33.2460 34.8560
34.8560 36.6340
36.6340 38.2800 38.3520 57.7060 64.6260 86.6040
0.638
0.218
0.120
0.087
0.117
1.000
1.000
1.000
100.000 1.000
Notes: aUses harmonic mean sample size ¼ 5.000; mean for groups in homogeneous subsets is displayed
Table VII. Duncan homogeneous subsets test of stress relaxation percent of worsted fabrics in weft direction according to fabric type (%)
120 Warp
Stress Relaxation
100
Weft
80
60
40
20
0 A
B
C
D
E
F G H I Type of Fabric
J
K
L
M
Note: Warp and weft direction
The fabrics that have larger polyester percentage have larger b coefficient. The fabric I with 0.99 percentages of correlation coefficient shows the most amount of correlation with Maxwell model while the D fabric with correlation coefficient of 0.85 shows the least correlation with this model. The amount of correlation coefficient with Maxwell
Figure 4. Comparison of stress relaxation percent in woven fabrics
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0.97
396
Stress (N/cm2)
Experimental 0.92 0.87 0.81 0.76
Figure 5. A typical diagram of the fitting stress relaxation for fabric type D in warp direction
0.70 0.0
31.2
62.3
93.5
124.7
155.8
187.0
Time (Sec)
0.04 Maxwell Model
Stress (N/cm2)
0.04
Figure 6. A typical diagram of the fitting stress relaxation for fabric type I in warp direction
Experimental
0.03 0.02 0.01 0.01 0.00 0.0
29.3
58.7 88.0 Time (Sec)
117.3
146.7
model in direction of weft is more than warp. By decreeing b coefficient the percentage of stress relaxation is increased too results showed that in first 30 seconds the stress relaxation is in highest amount. 4. Conclusion The aim of this paper was to put forward a new electro-mechanical method in order to measure and produce a protocol of stress-relaxation behavior of worsted fabrics in a wrinkled state with a constant torsional strain. The result of this experiment illustrated that the stress-relaxation behavior of worsted fabrics is related to the viscoelastic properties of the fibers used, and also the properties of the fabric such as thickness and weight. In such a way, that with increased thickness and weight of the fabric the stress-relaxation percentage
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397
hE
Figure 7. A typical diagram of Maxwell model
Coefficients Type A B C D E F G H I J K L M
a
Warp direction b
R
a
Weft direction b
R
0.45 0.31 0.87 0.87 0.58 0.68 0.55 0.49 0.41 0.21 0.39 0.73 0.19
200.1 383.28 496.13 681.3 434.02 442.82 208 588.43 23.95 343 508.37 398.11 162.27
0.97 0.88 0.93 0.85 0.88 0.88 0.98 0.87 0.99 0.91 0.91 0.9 0.94
0.49 0.15 0.66 0.56 0.34 0.41 0.34 0.46 0.03 0.29 0.53 0.19 0.18
166.3 175.74 322 330.02 217.53 432.01 47.2 195.64 7.7 330.04 272.96 355.92 71.26
0.98 0.91 0.97 0.85 0.97 0.86 0.98 0.97 0.99 0.9 0.94 0.9 0.93
was decreased. It was also illustrated that with increased polyester the stressrelaxation percentage is decreased, and stress relaxation percentage was greater in weft direction than that of the warp direction. This phenomenon is due to the lower density of the weft in comparison to the density of warp. It was also illustrated that the stress-relaxation equation corresponds to Maxwell model, and compare to other usual models for considering the stress relaxation, is more satisfying.
Table VIII. The coefficients of equation (3)
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[email protected]
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