Advances in Applied Mechanics, Volume 34

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Advances in Applied Mechanics Volume 34

Editorial Board Y. C. FUNG AMES DEPARTMENT OF CALIFORNIA, SANDIEGO UNIVERSITY LA JOLLA,CALIFORNIA PAULGERMAIN ACADEMIE DES SCIENCES PARIS,FRANCE C.3. YIH(Editor, 1971-1982) JOHN W.

HUTCHINSON (Editor 1983-1997)

Contributors to Volume 34 ELENAV. BOFDANOVA-RYZHOVA PEDROPONTECASTAGEDA PAULR. DAWSON ESTEBAN B. MARIN EDUARD RIKS OI.EGS. RYZHOV PIERRESUQUET WEI H. YANG

ADVANCES IN

APPLIED MECHANICS Edited by Erik van der Giessen

Theodore Y. Wu

DELFT UNIVERSITY OF TECHNOLOGY DELFT, THE NETHERLANDS

DIVISION OF ENGINEERING AND APPLIED SCIENCE CALIFORNIA INSTITUTE OF TECHNOLOGY PASADENA, CALIFORNIA

VOLUME 34

ACADEMIC PRESS San Diego London Boston New York Sydney Tokyo Toronto

This book is printed on acid-free paper. @ Copyright 0 1998 by ACADEMIC PRESS All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher.

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Contents vii

CONTRIBUTORS

ix

PREFACE

Buckling Analysis of Elastic Structures: A Computational Approach Eduard Riks I. 11. 111. 1V. V.

2

Introduction Basics, the Geometrical Point of View Basics, the Stability Point of View Computations Examples and Conclusion References

6 22 40 61 72

Computational Mechanics for Metal Deformation Processes Using Polycrystal Plasticity Paul R. Dawson and Esteban B. Marin I. 11. 111. IV. V. VI . VII. VIII. IX. X.

Introduction Orientations and Orientation Distributions Evolution of Texture and Strength Field Equations for Deformation Computing the Deformation by Using the Finite-Element Method Application to Forming Processes Studies of Microstructure Summary Notation Appendix: Matrix Representations Acknowledgments References

78 81 88 99 113 121 133 152 157 161 162 163

Nonlinear Composites Pedro Ponte Castaiieda and Pierre Suquet I. Introduction 11. Effective Behavior and Potentials 111. Variational Methods Based on a Homogeneous Reference Medium IV. Variational Methods Based on a Linear Comparison Composite V

172 175 187 192

Contents

vi V. VI. VII. VIII. IX.

A Second-Order Theory A Selection of Results for Linear Composites Applications to Nonlinear Composites and Discussion Concluding Remarks Appendices Acknowledgments References

216 228 231 280 28 1 295 295

The Mathematical Foundation of Plasticity Theory Wei H. Yang I. 11. 111. IV. V. VI.

Abstract Introduction Minkowski Norms and Holder Inequality Generalized Holder Inequality Constructing the Dual Norm Application to Plasticity A Duality Theorem for Plane Stress Problems References

303 304 307 308 309 311 313 315

Forced Generation of Solitary-Like Waves Related to Unstable Boundary Layers Oleg S. Ryzhou and Elena I.: Bogdanoua-Ryzhoua 1. Introduction: Historical Perspective 11. The Triple Deck 111. The BDA System IV. The KdV System V. Solitons and the Onset of Random Disturbances Acknowledgments References

AUTHOR INDEX SUBJECT INDEX

318 326 335 316 403 413 413

419 421

List of Contributors Numbers in parentheses indicate the pages on which the authors’ contributions begin.

ELENA V. BOGDANOVA-RYZHOVA (3171, Department of Mathematical Sciences, Rensselaer Polytechnic Institute, Troy, New York 12180

PEDROPONTECASTA~~EDA (171), Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6316 PAULR. DAWSON (77), Sibley School of Mechanical and Aerospace Engineering, College of Engineering, Cornell University, Ithaca, New York 14853-3466

ESTEBAN B. MARIN(77), Beam Technologies, Inc., Ithaca, New York 14850 EDUARD RIKS(l),Delft University of Technology, Faculty of Aerospace Engineering, 2629 HS Delft, The Netherlands OLEG S. RYZHOV(317), Department of Mathematical Sciences, Rensselaer Polytechnic Institute, Troy, New York 12180 PIERRESUQUET(171), Laboratoire de MCcanique et d’Acoustique/ C.N.R.S., 13402 Marseille Cedex 20, France WEI H. YANG(303), Mechanical Engineering Auto Laboratory, The University of Michigan, Ann Arbor, Michigan 48109-2121

vii

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Advances in Applied Mechanics has a history of publishing comprehensive, state-of-the-art articles in numerous subfields of applied mechanics. But in no way does this imply that this particular area has been fully excavated. The articles in the present volume give convincing evidence that the developments often continue, requiring an update of previous advances. Eduard Riks' article gives an up-to-date overview of the advancements made in the area of (post)buckling analysis since the often-quoted article in this series by B. Budiansky in 1974 (Vol. 14, pp. 2-65). In addition to providing a thorough outline of modern, computational techniques for buckling and postbuckling analysis of structures, this article also discusses recent methods of carrying out transient analyses after loss of stability. The latter offers new interesting insights into the notorious phenomenon of mode jumping. The article by Paul R. Dawson and Esteban B. Marin is related to R. J. Asaro's contribution to this series (Vol. 23, 1983, pp. 1-11.9,which marked the beginning of a rapid expansion of numerical applications of crystal and polycrystal plasticity. The article in this volume gives an exposition of some important refinements in computational methods that make polycrystal plasticity a viable tool for actually solving engineering forming processes. Particular emphasis is placed on recent innovations in the description of crystal orientations. In addition, this paper presents numerous examples of metals with a hexagonal close packed (HCP) crystal structure. Owing to seminal work in the 1960s, the linear-elastic properties of composite materials can now be estimated analytically from the properties of their constituents, along with the microstructure, with remarkable accuracy. Estimates of composite properties in the case of nonlinear material behavior, such as creep or plasticity, of one or more of the components are much more difficult to obtain. Analytical approaches to this problem that incorporate microstructural information have only been attempted during the last decade or so. The article by Pedro Ponte Castefiada and Pierre Suquet gives an overview of the latest developments

X

Preface

in this field based on variational methods. This scholarly work summarizes the key theoretical tools and presents applications to numerous model materials, with an emphasis on the effect of microstructure. The Chapter by Oleg S. Ryzhov and Elena V. Bogdanova-Ryzhova is a pioneering study of the fully developed nonlinear instability of viscous boundary layer during the final stage of transition into turbulent flow. This study is based on the important discoveries of several remarkable phenomena, first found by experiment at the Novosibirsk branch of the Russian Academy and now by theory, that the underlying mechanism actually involves generation of solitary waves under resonant forcing from flowboundary roughness and vibration. It appears that these results will be of general interest to researchers in this important field. In the article by Wei H. Yang, the author presents a task of integrating the existing and new bases of the mathematical theory of plasticity. In addition to the previously established conditions of convexity and normality as two pillars of support, an additional pillar, called the duality, is introduced here in terms of an equality inclusive condition which is claimed to bring the foundation to completion for the constitutive modeling of the mathematical theory of plasticity. This series had the fortune of being cultivated during the period 1971-1982 under the editorship of Professor Chia-Shun Yih, who made outstanding contributions in realizing advances of this series with distinction and subsequently continued serving as a wise counsel until his passing on 25 April 1997. It is with our sincere appreciation of his dynamic leadership and guidance that we pay our warm tribute to his memory. Theodore Y. Wu and Erik van der Giessen

Advances in Applied Mechanics Volume 34

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ADVANCES IN APPLIED MECHANICS. VOLUME 34

Buckling Analysis of Elastic Structures: A Computational Approach EDUARD RIKS Faculty of Aerospace Engineering Delft University of Technology Delft. The Netherlands

I . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2

I1. Basics. the Geometrical Point of View . . . . . . . . . . . . . . . . . . . . . . . A . Notation. Assumptions. Governing Equations . . . . . . . . . . . . . . . . .

6 6 9 B . Adaptive Parametrization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . Special Points: Bifurcation and Limit Points . . . . . . . . . . . . . . . . . . 12 D . Implicit Representation of the Bifurcation Branch . . . . . . . . . . . . . . . 17

22 I11. Basics. the Stability Point of View . . . . . . . . . . . . . . . . . . . . . . . . . . 22 A . Stability and Loss of Stability . . . . . . . . . . . . . . . . . . . . . . . . . . B . Critical Equilibrium States as Special Cases . . . . . . . . . . . . . . . . . . 24 25 C . The Notion of Attraction and Repulsion . . . . . . . . . . . . . . . . . . . . 29 D . Stability at the Critical States . . . . . . . . . . . . . . . . . . . . . . . . . . 36 E . Reactive Forces at the Critical States . . . . . . . . . . . . . . . . . . . . . . 38 F . Incipient Motion at Unstable Points . . . . . . . . . . . . . . . . . . . . . . . IV . Computations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 40 A . Local and Global Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . B . Perturbation versus Path-Following Methods . . . . . . . . . . . . . . . . . . 43 49 C . Linearized Buckling Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . D . Buckling and Postbuckling Analysis . . . . . . . . . . . . . . . . . . . . . . 52 54 E . TransientBehavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 F . Transient Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G . Transient Analysis After Loss of Stability . . . . . . . . . . . . . . . . . . . 58 V . Examples and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 A . ShellModeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 62 B . Mode Jumping of a Plate Strip . . . . . . . . . . . . . . . . . . . . . . . . . . C . The Esslinger Cylinder Buckling Experiment . . . . . . . . . . . . . . . . . 67 D . Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

72

I ISBN 0-12-0(12034-3

ADVANCES I N APPLIED MECHANICS. VOL. 34 Copyright 0 1998 by Academic Press. All rights of reproduction in any form reserved . 0065-2165/98 $25 00

2

Eduard Riks

I. Introduction Twenty-two years ago, Budiansky presented in this periodical a very comprehensive overview of the theory of elastic stability as it had been established up to that date (Budiansky, 1974). This exposition of the state of the art in stability analysis was, to a large extent, based on the general theory of buckling and postbuckling behavior founded by Koiter some 30 years earlier (Koiter, 1945), a theory that had suffered from a very slow start in becoming known and accepted in the engineering community after its appearance. In 1945, this new theory represented an important step forward in the understanding of the buckling behavior of structures as it was observed in engineering practice and experiments. It was this theory that was able to explain why the determination of the bifurcation point in the initial load deformation response could not provide enough information to predict the stability behavior of a structure with sufficient accuracy. As it was demonstrated by Koiter, the bifurcation point could not, by itself, be used to predict the failure load of the structure. To come to a better evaluation of this load, it was also necessary to establish the intrinsic properties of the bifurcation point itself. If the bifurcation point were stable, as in the case of a simply supported flat plate, the system could be loaded beyond the critical load that is associated with this point. On the other hand, if the bifurcation point turned out to be unstable, as in the case of a thin-walled cylindrical shell in compression, the structure could be expected to fail long before the critical load was reached, although it was difficult to predict with precision the load at which this would occur. This so-called sensitivity of the failure load for initial imperfections in the geometry, boundary conditions, etc., existed if the bifurcation point itself was unstable. In contrast, imperfection sensitivity did not play a detrimental role if the bifurcation point turned out to be stable. Apart from this important observation, the theory also provided the keys to the determination of the equilibrium states that bifurcate from the initial state and a means of assessing the strength of the imperfection sensivity in the case where this sensitivity could be established. The available methods of solution in 1974 were primarily analytical in nature. Computers were already in use, but their influence on the development of the solution methods was at first more in the area of the solution of complicated analytical formulations rather than systematic discretization of the governing equations from the start. At that time, there were three basic difficulties connected with the application of the theory. In the first place, the theory was an asymptotic theory, i.e., it relied on series expansions of the governing equations and therefore the solutions had a restricted range of validity. Second, if the primary solution path

Buckling Analysis of Elastic Structures: A Computational Approach

3

turned out to be nonlinear, the problem could turn out to be inaccessible for analysis, and this situation presented itself automatically if the structure was governed by a limit point rather than a bifurcation point. There was also a third difficulty. This had to do with the structural complexity of the structures that could be analyzed. The solution of the governing equations was only possible if the geometry and material build-up of the structure under investigation remained relatively simple. If this was not the case, the obstacles for analysis could soon become insurmountable. Thus it is not surprising that the practical applications of the theory remained restricted to structures with a simple geometry such as plates, cylindrical shells, and curved stiffened panels, and this in conjunction with an elementary type of loading: uniform compression, for example. Since then, many years have passed and the situation has gradually changed. This change was brought about by the advent and evolution of the digital computer, which made it possible to develop computational tools with a range and power that were unheard of before this evolution started. The emergence of the finite-element method is undoubtedly one of the most important advances in numerical analysis of this time, and since 1974 it has also had an impact on the modeling of the stability behavior of structures. Two schools of thought on modeling arose. The first is based on the discretization of Koiter’s asymptotic theory, at times amended with extras that the increased freedom of this numerical approach allows. Early accounts of this treatment can be found in Haftka et al. (1971), and more recent contributions are given in Damil (1992), Arbocz and Hol(1990), Casciaro et ul. (1992), Azrar et al. (1993), and Lanzo and Garcea (1996), which also contain further references. The other school is a more radical departure from the perturbation theory and is based on the continuation principle (see, for example, Riks, 1973, 1984a; Rheinboldt, 1977; Seydel, 1989; Crisfield, 1991; Kouhia, 1992), which in turn uses the principles of the numerical solution of nonlinear equations (Ortega and Rheinboldt, 1970). The continuation approach as a general and practical tool for the solution of elastic stability problems was probably first considered in 1970 (Riks, 1970, 1972), but the finite element modeling capabilities of that time were not yet fully developed (in the nonlinear range), so that the first applications appeared years after these capabilities became available. Since then, progress in the further development and implementation of these techniques has been steady. In what respect does the continuation method (also called the incremental method) differ from the classical perturbation method? The basic difference is that the solutions are no longer restricted to a small domain of the configuration space as with the perturbation method, but can be obtained everywhere in this space. The continuation method is thus a global method, whereas the perturbation

4

Edua rd Riks

method is a local method. With the continuation method, the initial load deformation path, as pictured in Figure 1, can be computed irrespective of degree of the nonlinearity of the problem. With this approach the stability of the solutions can be monitored during the computations, and by doing this the critical point at which loss of stability occurs (A or B) can be determined. The technique also offers a way to compute the branches of bifurcation points (under certain restrictions), so that it becomes possible to assess the postbuckling behavior of the structural model. Because of the versatile finite element modeling capabilities that are currently available, the applications of this type of analysis are no longer confined to standard problems with simple geometries, but can be extended to real world systems. Recent examples of such analyses can be found in Vandepitte and Riks (1992), Young and Rankin (1996), and Nemeth et al. (1996). Thus the continuation principle in combination with the finite-element discretization method enables one to determine the static equilibrium branches (for as far as is deemed necessary) of a very general class of nonlinear structural models. Once these solutions are obtained, the stability behavior of these structures can be explained by examining the particular geometrical properties of these branches.

load

A B

I I deformation

I

deformation F I G . 1. Initial stable response followed by collapse.

>

Buckling Analysis of Elastic Structures: A Computational Approach

5

But a stability analysis as described above is still a product of the classical quasistatic approach whereby only the solutions of the equilibrium equations are reviewed. According to the philosophy behind this approach, loss of stability is a dynamical transformation of state (see Figure 1) that starts at an unstable critical equilibrium state (a bifurcation point or limit point) but will end in a state in which the structure is no longer usable. Consequently, the critical state at which the motion starts is of interest, but what happens after this state is reached is not. However, it can be asked whether this quasistatic point of view can always be maintained. It has been known for a long time that unstable buckling does not always lead to an unserviceable state of the structure. To the contrary, it can happen that after such an event further loading is still possible. This occurs, for example, with plates and stiffened panels, and in these particular cases the phenomenon is called mode jumping. Thus it is not possible, at least not in the general case, to predict beforehand what will happen when an unstable critical point is reached. The passage through the critical state may have the result that the structure will end up in a new state with irreparable damage, but it may also happen that the structure remains in operation with no damage at all. In general, the actual outcome is dependent on the problem at hand and can only be predicted by an extended analysis, i.e., by taking the transient motion into account. The methods for integrating the equations of motion in the field of solid mechanics are actually quite well developed (Belytschko and Hughes, 1983; Argyris and Mlejnek, 1991), and the computer resources that are available at the present time no longer hinder the use of these methods. Consequently, in this chapter we not only consider the use of continuation methods for the solution of the equations of equilibrium, but also the use of transient methods to provide an answer to the question of how an actual buckling process works and where to it will lead. We believe that there are many problems in engineering practice where the answer to this question is badly needed. The discussion will closely follow the ideas that were developed in two recent publications (Riks et al., 1996; Riks and Rankin, 1997), but we aim here at a more complete presentation. Just as in the two references mentioned, we will introduce the numerical procedures by first giving a review of the elementary bifurcation theory for ordinary nonlinear equations that depend on a single parameter. The first part of this review is purely a geometrical introduction of this subject that is meant to serve as a preparation for the development of the static methods to be discussed later. The second part is focused on the stability or loss of stability that occurs at bifurcation or limit points, which is necessary for the understanding of what happens when such a point is reached.

6

Eduard Riks

The introduction to the computational procedures begins with a short description of the path-following method to be used for the computation of the static equilibrium branches, together with additional techniques that are needed for the analysis of these solutions. The computation of the buckling motion that starts at the point of loss of stability is the next subject, and the synthesis of this technique with the previous methods ultimately leads to the appropriate computational strategy, which makes it possible to numerically simulate the quasi-static as well as the dynamic elements of a complete buckling event. A good way to demonstrate the feasibility of a new strategy is to verify its predictive power by means of test results of well-documented buckling experiments. Therefore, the chapter will end with the description of the numerical simulation of two well-known buckling tests: the mode-jumping experiment of a plate strip carried out by Stein (19594 and the classical tests on cylindrical shells in compression that were carried out by Esslinger and collaborators in 1970 (Esslinger, 1970; Esslinger et al., 1977).

11. Basics, the Geometrical Point of View A. NOTATION, ASSUMPTIONS, GOVERNING EQUATIONS The structural models that will be studied here are supposed to be purely elastic. It is further assumed that an appropriate discretization procedure is available that allows us to represent the state of the structure in terms of a vector of finite dimension. In the following two sections we will first concentrate on the solutions of the static equations of equilibrium. To understand what type of loadings will be considered here, it is convenient at first to make the distinction between the configuration space C.N+K, in which the state d" of the structure is described and the computional space D.Nin which the freedoms, d, that are to be determined are described. Here N is the dimension of DN and ( N K) is the dimension of C N + K .Thus the computational space DN,which is a subspace of C.N+K, refers to all of the freedoms that are determined by the governing equations, while the configuration space refers to the same freedoms plus the variables that are prescribed by the kinematical boundary conditions. In this manner, the configuration of the structure under load can, at all times, be represented by an ( N K)-dimensional vector,

+

+

N+K

diei,

d" = i=l

Buckling Analysis of Elastic Structures: A Computational Approach

7

+

where ei (i = 1 , 2 , 3 , . . . , N K ) are the natural base vectors that span C N + K . The subset {ei} (i = 1 , 2 , 3 , . . . , N ) spans DN. We assign to the base vectors ei the following properties: e'ej

= 6ij

(where 6 i j is the Kronecker delta)

(2.2)

where aTb denotes the inner product of any two vectors a, b E DNor C N + K . In the general case, the structure is loaded by forces and by the prescription of certain displacements. The loading of the first type can be described as follows: N

L =CLiei.

(2.3)

i=l

The loading of the second type is given by N+K

b=

C

biei

i=N+1

and is thus in a subspace Di of CN+Kcomplementary to DN. In principle, the load system (2.3,2.4) can be varied in a completely independent manner, in which case it is defined by M 5 ( N K ) parameters. But in the practical situation it is customary to vary the load system proportionally for certain parts of the analysis. In this case we write (2.3,2.4) in the form

+

N

i=l

N+K

b=hbo = h

boiei r=N+l

where the (fixed) combination of parameters {Loi)and {boj}define a base load that describes the shape of the loading, and h is the intensity that belongs to this system. It is noted that the load intensity h can be seen as a function of the time, but only in the sense that when time passes, the variation of h is infinitely slow. Thus we will consider only loads that are applied in a quasi-static fashion. The structures and the load systems that will be acting on them are supposed to be quasi-conservative. This means that when a structure is loaded and unloaded in an infinitely slow fashion, the initial state can be recovered without the dissipation of energy. The structure then behaves as if it is completely elastic. Quasiconservative also means that the external forces (2.3) that are prescribed can be

8

Eduard Riks

derived from a potential energy function. Only when the structure is in motion can dissipation of energy in the form of Rayleigh damping take place. The assumption of a quasi-conservative class of structures implies that we can define a potential energy function

P = Pud; hbo; hLoD = W[d; hboD - hdTLo

(2.6)

from which the static equations of equilibrium can be derived. The function W in the right-hand side of this expression stands for the internal elastic energy of the structure, while the second term denotes the potential of the force system L. Please note that the notation P = Pud; hb; hD with the arguments d; hb; h between open-faced brackets [ D means that P is a function of these arguments. This notation will be used here and in the following to avoid confusion with the use of the brackets of the type [ [ ( ) } ] that are reserved for the purpose of grouping objects and algebraic terms. After these preliminaries it is now no longer necessary to carry along the explicit distinction between the displacement type of loading and the force type of loading. This means that the potential energy function will simply be written as' :

P = P[d; AD.

(2.7)

However, it should always be kept in mind that both types of loadings can be applied simultaneously at all times. The equations of equilibrium follow from the requirement that P must be stationary:

ap 6d = Pdud; hD6d = f T 6d = 0 6P = ad

for V6d E IIDN

(2.8)

and 6d stands for an arbitrary virtual variation of d in DN. This leads to the set of equations

f[d; AD = 0

(2.9)

where it is understood that

d = diej

'

(sum i = 1, . . ., N ) .

(2.10)

It should be noted that on the basis of the previous assumptions, the loading is generally dependent on the state d, which is due to the displacement-induced part of the load. This stands in contrast to many treatments of these type of problems, where only dead-weight loads are considered.

Buckling Analysis of Elastic Structures: A Computational Approach

9

In formal terms, the vector function f is a mapping, f: DN x IW1 -+ FN,where FN is the space (dual to DN) in which the forces are defined. In the context of the computations described here, a distinction between these two N-dimensional spaces is not required, and it is convenient therefore to write RN for both of them. It is this convention that will be adopted hereafter.

B. ADAPTIVE PARAMETRIZATION One aspect of the formulation that needs consideration is the parametrization of the governing equations. In the case of a one-parameter loading, the load intensity h emerges as the natural parameter that steers the deformation process in the actual physical case. But for the analysis of (2.9) and for development of the computational process, the load parameter h is not always suitable, and therefore it is useful to discuss some other choices for the parametrization of the solutions of (2.9). As mentioned, it is natural to choose h thus to view the solutions of (2.9) as

d = d[hD

(2.1 1)

but this leads to difficulties when we reach a state d* for which the corresponding value of h = h* satisfies h- < h* and h+ < h*, where the - and + denote the solutions dub-), d@+D just before and after d*. This is of course a limit point for h, and the failure of the description (2.11) in this case has to do with the fact that in the neighborhood of [d*,h*]no solutions of (2.9) exist for h > h*. A possible way out of this predicament is to exchange one of the displacement variables d~ (1 5 K 5 N ) and write

(2.12)

+

Equations (2.9) admit such a change, because there are (N 1) unknowns for N equations. A more general and, for our purposes, preferable choice is a parametrization that is adapted to the properties of the solution path in the domain where the solutions are described. This is a so-called local parametrization, where the term local implies that its definition is only in effect in a restricted domain of the solution space (see, for example, Rheinboldt, 1981; Riks, 1970, 1972; Seydel, 1989).

Eduard Riks

10

Suppose we have to describe the solutions in the neighborhood of a configuration [dl, h l ] ,which is a solution of (2.9). A change of basis for the decomposition of d in this neighborhood can be introduced by

d=dl+an+c, d l , n , c E RN, 0 E R1, cTn = O , n Tn = l ,

(2.13)

where the base vector n (or director) is chosen in some advantageous way, and the vector c is arbitrary, except that it must be independent of n. To introduce this new basis in the equations of equilibrium, the potential energy function is written as

P* = P[dl + a n

+ C; h] + KCTn

(2.14)

where the orthogonality condition in (2.13) is enforced by means of the Lagrange multiplier K . The stationary value of this function with respect to a,c, and K determines the equilibrium states of the structure, and this leads to the equations

+ a n + c; h] = 0, f[dl + o n + c; h ) + = 0 ,

(2.15b)

cT n = 0 .

(2.15~)

nTf(dl

K n

(2.15a)

+

This is a set of ( N 2) equations (completely equivalent to (2.9)) in the unknowns {a,ci (i = 1 , 2 , . . . , N ) , K , and h},one of which can be chosen as the path parameter. Suppose now that this is a. The solution of (2.15) in the neighborhood of [dl; hl] can then be presented as

d = duo],

d = dl

h = h[o],

h = hi

+ an + cQaD, + Ah[a].

(2.16)

Inspection of eqs. (2.15a) and (2.15b) shows that K = 0; this means that we can eliminate (a) from (2.15) and write for the part that remains,

fad; AD = 0 ,

(2.17a)

nT[d - dl) - a = 0.

(2.17b)

In comparison with the original formulation, the governing equations are now extended by one equation, and the extension defines the parameter a by the choice of n. The solution path in the neighborhood of [dl , h l ] is thus defined through (2.17) for some range of values of a. The geometrical meaning of this device is pictured in Figure 2.

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11

It can now be deduced from Figure 2 and (2.17) that the equilibrium points [d[uD, h[uD]for a certain range of a: a* < a < u**, are defined by the intersection of equation (b) with the solution of (a) as long as nTd’, # 0, where d; = {dd[aD/doJ,=,, is the tangent to the path duo) in IWN at d[olD. The parameter choice a is thus “optimal” (at least to some extent), if we choose n = d ; , because in that case the range in which we can use the definition of a by (2.17b) can be expected to be “the largest.” The use of a suitable path parameter by the means of an extended system can further be generalized by setting

f [ d ;hD = 0 , h [ d ;AD - D = 0.

(2.18)

where h is a function h: RN x IW1 + IW1 that is chosen appropriately in the sense discussed above. We will call a the path parameter of the solution (d[uD,h(aD), and its precise meaning will depend on what will be chosen for h. Note that in principle, h is now also included in the definition of a. After these preliminaries we are now ready to discuss the solutions of (2.18). A loading process initiated from the unloaded state (d, h ) = (0, 0) will generally result in deformation states that are initially stable in the sense of the stability theory (see, for example, Koiter, 1945; and Thompson and Hunt, 1973). In the context of the assumptions of this theory, continued loading may result in loss of stability, and this will then take place at a particular point (d, h) = (dc;A,) of the solutions of (2.18). This particular point can be identified as either a limit point or a bifurcation point. It is not always realized, however, that bifurcation points and limit points, which are solutions of (2.18) with very special geometrical properties, do not automatically coincide with the collection of solutions of (2.18) at which loss of stability occurs. The coincidence occurs only a for a small subset of the bifurca-

FIG.2. Definition of the path parameter u .

Eduard Riks

12

tion and limit points that are determined by (2.18). In other words, loss of stability takes place at either a bifurcation point or at a limit point, but it is not true that every bifurcation point or limit point is connected with stability loss. To make this clear, we will first derive the geometrical conditions that determine bifurcation and limit points as special solutions of equations (2.18). The concept of the stability and loss of stability that leads to a restricted class of these special solutions will be introduced later.

c. SPECIAL POINTS: BIFURCATION AND LIMITPOINTS The notation for the governing equations (2.18) can be shortened to

F[x, a] = 0,

F E RN+I

(2.19a)

where

and we will use this abbreviation (2.19a) instead of the extended form (2.18) whenever it is convenient to do so. It is now advantageous to make a distinction between the path parameter a that is introduced by (2.18b) and a special choice of o,denoted by s, which is the arc length of the path x[aD. The latter satisfies the condition

dx Tdx -=(x)

(ds)

ds

x =1

(2.20)

#1

(2.21)

while for our choice of a,

(g)Tg

= (x) i T xi

Suppose now that a branch of the solutions of (2.18) c.q. (2.19) is known and is given by

xi = xi[aD

(2.22)

for a certain range of a,a* < a < a**.The governing equations are then identically satisfied, so that

F[x~;

= 0.

Repeated differentiation of X I [o)with respect to o,and noting the meaning (2.18) of F, results in the sets of equations

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where F, is the Jacobian of the extended system of equation, a matrix with ( N 1) x ( N 1) components,

+

+

(2.24a) defined by (2.24b) It is noted that F, is nonsymmetrical in general, as a result of the arbitrariness of the auxialiary equation (2.18b). It is further noticed that we use the notation

(2.25) etc., where y=yae,,

a = 1 , 2 ,..., N + 1 ,

z=zaea,

a = 1 , 2 ,..., N + 1 ,

and it is understood that summation convention is implied. Equations (2.23) determine the so-called path derivatives xi; xr; x;”; etc. along the solution branch xl[aD, from which the tangent xo, the curvature xoo, etc. of x1 [a)can be constructed.They thus represent the local geometrical characteristics of x1 [a)at a. As long as the Jacobian F, (2.24) is nonsingular, the solutions of these equations exist and are unique, but this situation changes when F,(xl (a)) becomes singular at some value of a = a,. It is this special case that we will consider below. 1. Bifurcation According to the notions of linear algebra, the solutions of (2.23, i = 1, 2, . . .) exist and are unique when Rank{F,} = Rank{F,; R(’)] = N

+1

(i = 1 , 2 , 3 , . . .)

(2.26)

Eduard Riks

14

where {F,; R(')}is the extended matrix of the system (i) of (2.23). We will call the points of the equilibrium path x(oD at which this condition holds, regular solution points. Of particular interest are the points of xl[aD where loss of uniqueness of eqs. (2.23) occurs. Suppose this happens at a = a,. If multiple solutions of (2.23) exist, we must have Rank(F,} = Rank(F,; R(')] < N

+1

(i = 1 , 2 , 3 , .. .).

(2.27)

This condition means that multiple solutions of (2.23) are possible if F, is singular and the nonhomogeneous terms, the vectors R(') of (2.23), stay in the range of F,. Please note that this condition must hold for all suitable but otherwise arbitrary choices of h[xD in (2.18, 2.19). In this chapter it suffices to consider only a particular case of (2.27), i.e., Rank(F,) = Rank{F,; R(')} = N .

(2.28)

As will be shown, this special case corresponds to a so-called simple bifurcation point where only two solution branches cross. When (2.28) holds, the solution for the derivatives x ( ~of ) eqs. (2.23) can be written as - K(i)b+ y(')

.(i)

where K

( ~ is )

(2.29a)

an as yet undetermined parameter and b and y(') are the solution of (2.29b)

Thus b is the right null vector of F, at a, and y(') are particular solutions of (2.23(i)). The singular F, also has a left null vector, which we denote by c:

cTFx= 0.

(2.29~)

Condition (2.28) implies that C T ~ ( l= ) cT e N + 1

c'R'') = 0,

=o,

(2.30a)

i = 2 , 3 , 4 , ..., N ,

(2.3Ob)

because R(') = e N + 1 and R(') should be in the range of the singular F,. From (2.30a) it follows that c can be written as

c=(K)

EIwN+~,

aER,v.

(2.3 1)

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Noting the structure of F, (2.24b), eqs. (2.29) then lead to the observation that

aT f d = o , T

a

(2.32a) (2.3 2b)

fh=O,

and because fd = symmetric (since fd = (Pd):):

fda = 0.

(2.33)

In the following we will often denote fd by

K =fa

E

X

RN.

(2.34)

We can then summarize the conclusion as following. If the system of eqs. (2.23( 1)) has two solutions, it is not only follows that F, is singular, but also that K = f d is singular, K having a one-dimensional null space spanned by a (2.32b) and a‘f, = 0 (in general). It also means that the Taylor expansion

x = x[c] = x[c,-D

+ x’[a,D(a

+ 21 x”[a,-D(c - a,)’ + . . .

- c,-)

-

(2.35)

has two solutions implying that two solution branches of (2.18) or (2.19) are intersecting at x[c,-D. The path derivatives of these branches can be obtained from the sets of equation

where R(’) are defined in (2.23), ~ ( 1 )are parameters and y(’) are particular solutions of equations (1, 2, 3, . . . , N ) . Note that the singular condition of K at the bifurcation point x[ecD implies that K is semidefinite, i.e., it can take values V’KV 5 0 for any vector v # a in RN.It is also of interest to note that the construction of the solution of equation (i = 1) is particularly simple if the derivative of the primary path at x[acD is known beforehand. This situation presents itself automatically when arc-length continuation is used for the computation of these branches, because in that case, the direction of the path that is traversed is always known (to some approximation or accurately) (see, for example, Riks, 1984b; Riks et al., 1990).

2. Stationary Points, Limit Points Apart from bifurcations, the solutions x[cD can have special features, such as a stationary point with respect to the direction eN+1, where the path derivative x’[e*D satisfies ei+lx’[c*D = h’[e*D = 0 (see Figure 3). At these points, the

Eduard Riks

16

II d II

w FIG.3. Stationary points with respect to h.

load parameter may have reached a maximum or a minimum, and if this property can be established, such points are referred to as limit points. It will be seen later that among the equilibrium states at which the load h[aD reaches a maximum or minimum, there are “some” that represent loss or gain of stability, and these points are then the proper limit points in the sense of the stability theory. We consider now a regular solution (F, is nonsingular) along the path x[aD, where I’ = 0. Inspection of (2.23) in this particular case shows

Kd’ = 0

(2.37a)

hdd‘ = 1 Kd”

+ fddd’d’ 4-fhh.” = 0 hdd” + hhh” = 0

(2.37b)

etc. Thus it follows that at a solution where I’ = 0, the tangent x’ is given by (2.38) where a must be the null vector of K = fd. Consequently, at stationary points of h = h[aD for a = a,, K = fd is also singular and, just as before, semidefinite. It can be further seen that at such points, the question whether IQa,Dis a maximum or minimum is decided by the solution of (2.37b). Again by inspection, it follows from this equation that at a = ac, can be written as

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(2.39) The stationary point is thus a proper maximum if (2.40) and a minimum if (2.41)

D. IMPLICIT REPRESENTATION OF THE BIFURCATION BRANCH There are two contrasting ways to represent the solutions of the branching diagrams at bifurcation points. One form is explicit, i.e., in terms of a (multiple valued) Taylor series, as given by (2.35). The other is implicit, in terms of the socalled fundamentalbifurcation equation. For our exhibition,the latter formulation is preferable because the important issues to be discussed here are determined by this equation. As follows from the previous considerations, at bifurcation points of the solutions of (2.18) or (2.19), we are confronted with the conditions (2.32), which are equivalent to fd(a,] is singular,

fh E Range{fd[a,)}

(2.42)

where as before, the attention is restricted to the case where the null space of fd is one-dimensional, so that only simple bifurcation points are considered. In the same terms, the conditions that are connected with the occurrence of a stationary point with respect to the load intensity h are (see (2.37a), (2.39(2)): fd[acD is singular,

fh $ Range{fd[a,D}.

(2.43)

As before, the null vector of fd[a,D is denoted by a E RN.It is clear that this vector plays an important role in the solutions of equations near the point XI(ac),because it is one of the base vectors that determines the tangents to the two paths that are crossing at XI(a,]. The other base vector is a particular solution of (2.23( I)), for which we will take the tangent to the primary path x;[ac,-. In the case of a stationary point h; = 0 (2.42), a is the direction of the primary path at xi (a,) (see also (2.38)).

Eduard Riks

18

To describe the solutions near XI [o,),it is useful to make use of the LyapunovSchmidt-Koiter2 reduction of the equilibrium equations (2.9). For an in-depth exposition of this method, we refer to Golubitsky and Schaeffer (1985). A convenient starting point for the construction of the reduction is the principle of the stationary value of the potential energy. The solutions in the neighborhood of the special point x@,D can be written as

d=d,+pa+v,

aT v = O , (2.44)

h=h,+Ah

where

Note that this transformation involves a change of basis and that p measures the distance along the mode a, while the additional term v is forced to be perpendicular to a. The equilibrium equations that correspond to this transformation can now be derived from the modified potential energy P*:

P* = P[d,

+ pa + v; h, + Ah) + KaTv

(2.45)

in exactly the same way that this was done earlier in Section 1I.B. The governing equations follow from the stationary value of P* with respect to arbitrary variations of the amplitude p, the vector v, and the Lagrange multiplier K . The result is the system

+ v; h, + A h ) = 0, f[d, + pa + v; h, + A h ) + Ka = 0, aTf[d, + p a

aT v = O ,

(2.46a) (2.46b) (2.46~)

which is again completely equivalent to the system in (2.9). In comparison with the appearance of the transformation (2.15) that we derived in Section II.B, there is little that has changed, except that the direction vector n in (2.13) is now specified as n = a. The state at which equations (2.15) are evaluated is different, however, because here we have fd[x,D is singular, whereas in (2.15), the condition of fd was not specified. The power of the reduction (2.46) in the singular case is that the ( N 1)dimensional set of equations in v, K given by (b) and (c) at (2.46) can still be

+

2Koiter devised this method independently in terms of a variational procedure, which is the reason we also attach his name to it (Koiter, 1945).

Buckling Analysis of Elastic Structures: A Computational Approach

19

solved uniquely in terms of p and Ah, at and in a small neighborhood of x,. This follows because the Jacobian of this system

J" =

[

K

aT

a . 0] is nonsingular

(2.47)

near and at x,. The solution of (2.46b, c) can therefore be assumed to exist in a small neighborhood of x, and can be written as

v = V ( p ;Ah].

(2.48)

Once V is constructed, the completion of the solution can be obtained by solving the so-called reduced equation (a): (2.49) which, in the present case, has the properties (2.50) The reduced equation is thus singular at x,, and it satisfies either the bifurcation condition gh = 0 or the condition for a stationary point with respect to A,h; = 0. The similarity transformation that stands at the basis of the LyapunovSchmidt-Koiter reduction splits the original (singular) N-dimensional set of equilibrium equations (2.9) into a small subset of equations containing the singularity and a large complementary set of equations that are regular. In the case of only one zero eigenvalue of fd, the case we consider here, the dimension of the reduced set is one. The interesting (and essential) part of the behavior of the solutions is completely described by this reduced set, and because it is small, it is more easily accessible than the original set of equations. It is now useful to consider the asymptotic solution of (2.49). An approximation of this kind can be obtained if we first solve (2.46b, c) for small variations of Ah and p. The solution can be carried out using a standard pattern, starting with the assumption that v in (2.46b, c) can be represented by the power series

+ + pAhw11 + Ah2w02 + higher order terms = AhKO1 + p2K20 + pAhK11 + Ah2K02 + higher order terms

v = Ahwo~ p2w20

(2.51a)

K

(2.51b)

Introduction in (2.46b, c) then results in four sets of equations:

(2.52a)

20

Eduard Riks

where

The underscore ( J is used here to remind the reader that the derivative terms are evaluated at the singular point xc = x(acD. Because the Jacobian J” (2.47) is nonsingular at xc = x[acD,the individual terms in the approximation for v defined in (2.51) can be obtained from these equations. Substitution of the result in (2.46a) and expansion then leads to gap: Ah) = A’, Ah

+o

+ 2AiAhp + 3A3p2 + 4 A i p 3 ( ~a h 2~, ah2p) ,

(2.53a)

where:

1 A; = -[aTfdha 2

A’, = aTfA; ‘

T

A3 = - a fddaa; 3!

+ aTfddaw01];

A: = $ aTfdddaaa-

I

(2.53b)

wlofdw20.

The reduction process can of course be extended in a very general way to cover a whole wealth of phenomena. Here we deliberately confined it to the three basic forms of singular behavior that are the most elementary among the solutions of the equations of elasticity. A natural way to represent the solutions is to plot them in the (A,p) plane, as has been done in Figure 4 for very small values of Ah and p. The three cases to be distinguished can then be specified as follows. (i): Limit point: A’, # 0

A’,A3 > 0 -+ branch (1); AiA3 < 0 + branch (1’).

(2.54)

(ii): Skew-symmetric bifurcation: A’, = 0

A;A3 > 0 -+branch ( l ) , (2); AkA3 < 0 -+ branch (I), (2’).

(2.55)

(iii): Symmetric bifurcation (pitchfork): A’, = 0

A i A i > 0 + branch (l),(2); A i A i < 0 -+ branch ( l ) , (2’).

(2.56)

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21

1

Limit points

Skew - symmetric bifurcations

Pitchfork bifurcations

FIG.4. Basic forms: singular behavior.

Thus the solutions of (2.53) represent: (i) a maximum or minimum with respect to A, (ii) a simple bifurcation point where two solutions cross at x, with A{,* # 0, and a simple bifurcation point with A{ # 0; A; = 0. It is noted that the latter type is often referred to as pitchfork bifurcation. The analysis of the foregoing concerned the geometrical form of the solutions of the equilibrium equations in the neighborhood of points where fd becomes singular. These results are derived under the assumption that the external circumstances such as the loading or kinematical boundary conditions are absolutely static and thus are in no way dependent on the time. However, in the actual physical situation, the structure is always subject to finite time-dependent disturbances that are induced by the environment. No matter how small these disturbances are, they will induce motions around the equilibrium state, which may or may not stay in the neighborhood of this state when time evolves. There is thus the question whether the equilibrium states determined by (2.9) are physically attainable, i.e.,

Eduard Riks

22

whether the time-dependent configurations of the structure in the actual physical situation will stay close to the equilibrium state that is determined in the imaginary situation where no disturbances can affect this state. The question of the existence of attainable states of equilibrium is, of course, equivalent to the question of the stability of these states. The need to distinguish stable solutions from unstable solutions, and to understand the mechanical significance of the notion of loss of stability is not only important for the computation of the load-carrying capacity of a given structure; it turns out also to be important for computation of the behavior of the structure after loss of stability. This is why we will now investigate the stability of the solutions presented in (2.54)-(2.56).

111. Basics, the Stability Point of View A.

STABILITY AND

LOSS OF STABILITY

The dynamical concept of stability of elastic structures is attributed to Lyapunov. Lyapunov’s criterion considers the motion of a structure initially at rest that is disturbed by a small perturbation (see, for example, Koiter, 1965, 1967a). If the incipient motion grows without bounds, independent of how small the initial disturbances are taken, the equilibrium state is declared unstable. On the other hand, if the motion remains bounded for initial disturbances below a certain finite measure, no matter how small this measure is, the equilibrium is declared stable. However, Lyapunov’s criterion is hardly ever applied in structural analysis. Far more popular is the much older energy criterion (attributed to Lagrange and Dirichlet), which can be proved to be equivalent to Lyapunov’s criterion, at least when we deal with a conservative mechanical system of finite degrees of freedom. The energy criterion states that if the potential energy of the structure at the equilibium state under consideration is a proper “minimum” (a “well”), no matter how shallow or small it is, the equilibrium is stable. If this property does not exist, the equilibrium state under consideration is unstable. It is noted here that the energy criterion can be interpreted as a geometrical analog of Lyapunov’s dynamical criterion, because it can be seen as a rule that connects the geometrical properties of the potential energy function of the mechanical system at the equilibrium state to the dynamical properties of the system at this state. In more specific terms, the energy criterion states that a given equilibrium state d, which is a solution of eqs. (2.9) for a certain load value h, is stable if and only if the potential energy function Pud; hD satisfies

Pad

+ 6d; hD - Pud; hD > 0

(3.1)

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23

for V6d E RN: 0 < 116dl) < ,z2, where ,z2 can be as small as we please. (The notation 11 11 denotes here a suitable vector norm, for instance: llall = (aTa)'/2.) If the inequality (3.1) is not satisfied, the equilibrium configuration d is unstable. For practical applications, and thus for the inspection of the solutions of (2.9), this form of the criterion does not turn out to be very convenient, and this is the reason that one usually resorts to a weaker form of (3.1). Assuming that the energy function can be differentiated as many times as is needed, one can write

Because d is an equilibrium state, the first term behind the equality sign disappears, so that the role of the leading term in this expansion is taken over by the second term, the second variation:

where as before, Kid; AD = fdud; AD.

(3.4)

It can now be shown that the minimum of P[d; AD and thus stability at d is ensured if and only if the quadratic form (3.3) is positive definite, or lT2[6dD > 0

(3.5)

for VSd E R,. If the quadratic form is indefinite, that is if n2[6dD

P0

(3.6)

where the sign < holds for some Ad, the potential energy is not a minimum at d and the equilibrium is unstable. The intermediate state occurs when the quadratic form is semipositive definite, i.e., when nz@dD ? 0

(3.7)

where the equality sign holds for some 6d # 0. In this case no decision on the existence of the minimum can be obtained from (3.7) (see Koiter, 1945, and Thompson and Hunt, 1973). In the context of our formulation in terms of discrete variables, conditions (3.5) and (3.6) are sufficient for the existence of a proper minimum, or the exclusion of such a minimum, respectively. They are thus sufficient conditions for the existence

24

Eduard Riks

of stability or the absence of stability of the solution d. No verdict is obtained when (3.7) holds. In that case, the potential energy may still be a minimum, but this property can then be verified only by a return to the original form of criterion

(3.1). Condition (3.7) thus determines solutions that are neither definitely stable or definitely unstable. A solution d = d, that satisfies (3.7) is therefore considered to be at the stability boundary, which separates stable from unstable behavior. Such a state is called a critical state and will henceforth be denoted by d = d, or by x = xc. An equilibrium path ].[x that goes through a critical state x, can thus be divided into two parts. If one part is stable, the other is presumably unstable, because x, signifies the stability boundary. Indeed, this separation is often encountered. Traversing the equilibrium curve from the stable part toward xc will then result in a so-called loss of stability when xc is passed. However, exceptions are possible. There are special cases where the equilibrium curve that passes through x, is not divided into stable and unstable parts. An example of this behavior is found in the symmetrical branch of the pitch fork bifurcation point, as will be seen at a later stage of the discussion in Section E.

B. CRITICAL EQUILIBRIUM STATES AS SPECIAL CASES Simple critical equilibrium states in the sense of the stability theory are thus marked (see condition (3.7)) by a semipositive definite quadratic form (the second variation) l72[6dD. This means (from linear algebra) that the Jacobian K has the following property:

fdux,] = K[xcD is singular (with one-dimensional null space), V ~ K [ X , ] V > 0, VV: a'v = 0,

(3.8)

where a is the null vector of K(lxcD.In contrast, the simple bifurcation points and limit points that we considered in Section I1 were connected with the condition that the Jacobian K has the property

fdux,] = K[x,] V'K[X,]V

# 0,

is singular (with one-dimensional null space), VV:

a'v = o

(3.9)

(see Section 1I.C). It is thus observed that the condition of loss of stability (3.7) or (3.8) is a special case of the condition for singular behavior of the solutions that are given by (3.9). This special case occurs in (3.9) when the quadratic form v'Kv, under the side condition a'v = 0, remains strictly positive. Only in this particular case is a

Buckling Analysis of Elastic Structures: A Computational Approach

25

“singular point” in the geometrical sense also a “singular point” in terms of the concept of stability. Points at which loss of stability occurs are thus special members of the family of singular points that are part of the solution set of equations (2.9). Solution branches of equations (2.9) that are stable are thus also special, in view of the circumstancethat unstable branches are the rule rather than the exception (see also (3.6)). Of course, solutions that are unstable do not have much practical meaning in the assessment of the load-carrying capacity of a structure, and therefore they can usually be left out of consideration.

c. THENOTIONOF ATTRACTIONAND REPULSION For what follows it will be helpful to expand our perception of the energy criterion by introducing a mechanical interpretation of the notion of stability. For this purpose we will consider an equilibrium state d = dl at some (fixed) value of the load intensity hl . The potential energy change that occurs if we perturb the state d (by artificial means) is then defined as

hl =constant where y E IWN is any perturbation from dl. The equilibrium equations in this notation follow from

~ ~ U Y D=~ 0Y

(3.11)

f[yD = 0.

(3.12)

which with fly] = ny[yDTgives

These equations are thus a shorthand notation for eqs. (2.9) if we take into account the shift d = dl y and leave out the reference to A. Please note that

+

(3.13) The equilibrium state dl under consideration is thus defined by y = 0, so that f[OD = 0. With the energy criterion, it is the geometrical concept of the shape of the energy surface P[dl + yD in the neighborhood of dl that determines the existence or the absence of stability of this state. It is now useful to investigate

26

Eduard Riks

whether it is possible to connect this geometrical concept to a mechanical concept of stability that is explained in terms of forces. The energy criterion (3.1) in its general form is a necessary and sufficient condition for stability. To determine whether a minimum of P exists at dl ,it is possible to consider the following scenario. We introduce a closed and convex surface around the point dl in RN that can be expanded or shrunk at will and determine the minimum of n[yD on this surface. Once the minimum n* is determined, we let this surface shrink and make it as small as we please. If this minimum, for an arbitrarily small but finite distance from dl, is still positive, the potential energy function P must be a proper minimum at d ~However, . if n*is negative, the potential energy is no longer a minimum at dl . The formulation of this analysis can be based on the introduction of the convex surface

where the matrix T E RN x IWN is symmetric, positive definite, but otherwise arbitrary, and r determines the “volume” of fi. To find the minimum of P (or, equivalently, on this surface, we introduce the modified potential

n)

n* = n[yD - 21 ~ [ y ~ -T r2] y -

(3.15)

where K E Rl is the Lagrange multiplier that enforces the constraint (3.14). Here the minus sign before the additional term is chosen for convenience. The condition for the minimum of n[yD on fi[y; D r is then given by the variational equations

[n,[yD - ~ y ~ T 1 G-y[yTTy - r 2 1 8 = ~0

(3.16)

or by the set of ordinary equations

fUyD - K T =~ 0, YTv - r 2 = 0 .

(3.17)

If it is possible to find a solution y* of this problem that satisfies Vy # y*: n[y*D < n[yD, then the value of n[y*D determines the minimum of l 7 on Q[rD. Stability of the configuration dl is ensured if it is possible to find an open interval for r: 0 < r < E , where E may be arbitrarily small, in which n[y*[rDD is positive and monotonically increasing with r. On the other hand, if the minimum l lBy*(rDD is negative, no matter how small E is chosen to be, stability of the equilibrium state dl does not exist.

Buckling Analysis of Elastic Structures: A Computational Approach

27

It is now useful to point out that problem (3.17) corresponds to the formulation of a virtual experiment that is applied to our structural model. The experiment consists of a perturbation of the original equilibrium state dl , by forcing the perturbations y to be on the surface S2[y; rD. The enforcement of this kinematical constraint is “frictionless,” so that the structure is able to seek new equilibrium states on the surface a.These equilibrium states correspond to stationary values of the potential n*. Consequently, eqs. (3.17) represent the equilibrium equations of the structure under an additional loading given by K T ~which , is the force exerted on the structure by the frictionless surface S2 on which the configuration y is forced to stay. At the equilibrium states determined by eqs. (3.17), this force is in equilibrium with -f[yD, which is the force that the structure exerts on the frictionless surface S2 in return. It is now noted that the vector n = ‘Q is normal to the surface if y is on a:yT‘Q - r 2 = 0. Thus, according to eqs. (3.17), at the equilibrium states of the perturbed model the reaction force R = -f(y*D is parallel to this normal. Because S2 is convex, it can also be concluded that R has a component that points = -y*Tf[y*D is negative, and in the opposite to the center y = 0 when Y * ~ R direction when Y * ~ isRpositive. This observation can, of course, be rephrased by saying that the restoring force R = -fly*) is pointing at the interior of S2 when y*Tf[y*D > 0 and pointing to the exterior when y*Tf(y*D < 0. In the following we will call the reaction force R a force of attraction if it points in the direction of the interior as defined above. If R points toward the exterior, it is called a force of repulsion. It can now be shown that when the equilbrium state of the unperturbed structure dl is stable, and not critical, the reaction forces induced by the constraint i2 are always attractive for 0 < r < E where E + 0, whereas this property is lost when dl becomes unstable. This observation also holds for perturbations that are constrained by i2 but do not necessarily satisfy eqs. (3.17). In other words, it also holds when the surface Q[rD has friction to the extent that no motion along it is tolerated. To show that this assertion is correct, it is sufficient to consider the measure

(3.18) If G > 0, the force R is attractive, and if G < 0, it is repulsive. It is useful to introduce y = ru, where u is arbitrary under the restriction that it lies on i2[r = 1): uTTv - 1 = 0, and r is always positive: r > 0.

Eduard Riks

28 Expansion of uTf[ruD yields

+

uTf[rvD = uT[f[OD rfd[o]u

+ S[ruD]

(3.19)

where S[rnD = r 2 p [ u ,rD denotes the tail (remainder) of the expansion. Note that the leading term in p [ u ; rD is of order 2 in u and independent of r . With (3.19) it follows that

+

(3.20)

r-'G = uTfd[ODu rA[u; rD where

This expression provides the estimate

where

Cur] = Max(lA[u; rDI) vv

(the existence of this bound is assumed)

The value ml is here the smallest eigenvalue of K = fd[OD, defined by

[K - mlT]x

0.

1

(3.2 1b)

If the configuration dl = 0 is stable, mi > 0. This means that if we choose r so small that r < E , where E: &CUED= ml, (3.22) regardless of the direction of the perturbation y = ru. Consequently, at a stable, but noncritical equilibrium state, the reaction forces R = -fly) are guaranteed to be forces of attraction as long as y remains in Q (E):y T ' Q - c2 = 0. As mentioned, most solutions of the equilibrium equations (2.9) are unstable. What can be said about the reaction forces to arbitrary perturbations when dl is unstable? It follows from previous considerations that in this case there must be at least one particular direction u of the perturbation y = ru for which the reaction forces R are repellent. This follows because the Jacobian K = fd[OD has at least one eigenvalue ml < 0. Let the corresponding eigenvector be denoted by a, again with the normalization aTTa = 1. The value of the measure H in the direction

Buckling Analysis of Elastic Structures: A ComputationalApproach

29

v = a is then

so that

GI [ml

+ rlA[a; plllr.

(3.23)

This result shows that if r is chosen small enough, we can make sure that G < 0, and this, in turn, implies that a small perturbation in the direction n = a induces a reaction force that pulls the configuration y away from the equilibrium state y = 0, irrespective of the sign of a. It is thus clearly a reaction that will lead to an escape motion, and therefore it is associated with unstable behavior of the system.

D.

STABILITY AT T H E CRITICAL STATES

The test for the stability of the solutions of the equilibrium equations, in numerical simulations for example, can thus be carried out by examining the condition of the Jacobian K = fd[x[sDD. If K is positive definite, stability is ensured. If K is indefinite, the equilibrium is unstable. Only in the case of an encounter with a critical point, where K is semipositive definite, can the decision on the stability not immediately be provided. In these special cases it is necessary to return to the general criterion (3.1). It turns out that the investigation into the stability of the critical points is of considerable interest for the numerical treatment of the problems that we discuss in this paper. It was Koiter (1945), in his dissertation (see also Koiter, 1963), who studied this problem for the first time. He showed how the stability or instability of the critical points was indicative of the character of the behavior of the structure in the neighborhood of these points. His results also make it possible to classify the critical points as stable or unstable by simply examining the shape of the solutions in the neighborhood of these points. The investigation of the stability of the branches of a critical state x, (away from x,) can be carried out on the basis of the quadratic form

+

+

A2P = [aTfd[xDa]Ap2 [aTfd[xD]AvAp AvTfd[xDAv where

(3.24)

represents the solutions of eqs. (2.46), i.e., they represent the branches connected with x,, and Ap, Av are arbitrary variations of p and V, whereby aTTAv = 0.

Eduard Riks

30

The sign of A2P for 0 < (pl < EO, where EO can be arbitrarily small, determines the stability of the solutions connected with xc. It turns out that if one is interested only in the solutions in the immediate neighborhood of xc,i.e., when EO + 0, the analysis of (3.24) can be replaced by inspection of the sign of (3.25) where gup, V[pD, k[pDD is the reduced form (2.53) that is derived in the reduction process in Section 1I.D. The proof can be constructed by first considering the minimum of

l7* = n*[ApD =

Min

VAv: A k = f x e d

{[aTfd[x)]AvAp

+ AvTfd[xDAv + KaTTAv}.

(3.26)

This problem leads to the set of equations (3.27) which is compatible for reasons discussed before. The solution can be written as Av = Apzo; K = A ~ K oIntroduction . into (3.26) yields

A 2 P = [aTfd[X]a - z~fd[x)zo]Ap2.

(3.28)

It is now not difficult to see that when EO -+ 0 and thus 1pl + 0; Ak -+ 0, the above expression comes arbitrarily close to (3.25). This result is classical and can already be found in Koiter (1945,1963). To complete the discussion, we will now turn to the stability of the critical points themselves. In agreement with our expectations and following from inspection, at such points the reduced form A2P disappears. In this case it is thus necessary to go back to the general criterion (3.1), i.e., at x, it is necessary to inspect the sign of

~ [ Y D = P[dc + Y; &D

- P[d;

LD,

(3.29)

A, = constant for arbitrary variations y = Ad. To do this, it is again advantageous to look at the minimum of l 7 on the ball: !&: yTTy - r 2 = 0. But this time we will also introduce the change of basis that proved to be so useful in the determination of the branches of xc:

y = pa

+ v,

a T Tv = 0.

(3.30)

Buckling Analysis of Elastic Structures: A ComputationalApproach

31

To determine the minimum of

n* = n[yD - -21 ~ [ y ~ T r2] y

(3.31)

in this setting we have to consider the minimum of the modified potential: 1

IT** = n[pa + vD - 5 K[(pa + v)TT(pa+ v) - r2] + uaTTv

(3.32)

which is determined by

+ vDTa - KaTT(pa+ v)]6p + [f[pa + v] KT(pa + v) + uTaIT6v 1 - - &[(pa + v)TT(pa+ v) - r2] + 6uaTTv = 0 2

[fupa

-

(3.33)

for arbitrary variations 6p, 6v, 6 v , and J K . Using aTTa = 1, the resulting equations are written as

+ vD - ~p = 0, fapa + VD KT(pa + v) + vTa = 0, a T f[pa

(3.34a) (3.34b)

-

a T Tv = (pa

0,

(3.34c)

+ v)TT(,ua+ v) - r 2 = 0.

(3.34d)

These equations determine the minimum of n on a closed surface S2 (r) around the state y = 0. It is natural to consider the solutions of this set to be parameterized by r, the radius of S2[r), but we have the freedom to change this at will and replace r by any other freedom. The parametrizationin terms of p has a distinct advantage because in that case, r follows simply from r 2 = (pa v)TT(pa v). Another simplification follows by observing that the Lagrange multiplier u = 0 (which can be seen by projecting (3.34b) on a and comparing the result with (3.34a)). The equations that interest us most are thus contained in

+

f[pa

+

+ vD - KTV- KpTa = 0,

(3.35a)

aTTv = 0.

(3.35b)

Solution of these equations is again sought in terms of v = Vup);K = K [ p ) ,and this is possible because these equations are compatible even at p = 0, i.e., the Jacobian J:

J=

[

fd

aTT

71

is nonsingular

32

Eduard Riks

Once the solution is determined, the value of ll attained by this solution satisfies n,[rD = n[pUrD, V[w[rDDD < n[p-,v-D, where [p-, v-I # [p[rD, VUp[rDI is any combination of p and v that lies on Q[rD. It further follows that if ll, [rD > 0, stability is ensured, but in contrast, if n, < 0, stability is lost. We will now determine the solution of (3.35) for values of Ipl + 0 by assuming that the solution can be written in a Taylor series:

Repeated differentiation of (3.35) with respect to p, and evaluation of the resulting expressions at p = 0, yields the sequence of sets:

fd[ODy’ - KTV’- ETa = 0, aTTy’ = 0,

(3.37a)

The underscore ( _ ) again indicates that the variables are evaluated at x,; thus: y’ = v’[OD, g = ~ ( 0 1etc. , It follows immediately that the first set of equations yields = 0; y’ = 0, so that (b) can be reduced to

fd[ODf’ - 2 ~ ’ T a= -fdd[ODaa, aTT$’ = 0.

(3.38)

In the following we write the solution y” of (3.38) as: x” = 2w20 and note that w20 becomes completely identical to the solution w20 of the system (2.52a) for ( i j ) = (20) in Section 1I.D if we take T = I (I is the identity matrix). The solution Y = p[rDa+ p[rD2w20 Our3)of the problem (3.34) determines the location of a point on the surface Q[rD at which Il is a minimum with respect to all other points y on Q[rD. It defines a curve for values of r: 0 < r < E , where E is some small positive number. Along this curve the potential energy can be evaluated as a function of r or p. If, for vanishingly small values of r or p, this special function stays positive, the potential energy is also positive for all perturbations in the neighborhood Q[rD. In that case, the potential energy is still a minimum at y = 0 and the equilibrium state xc is stable. If the potential energy is negative along this curve for vanishingly small r , no minimum exists and the equilibrium of the critical state must be unstable.

+

Buckling Analysis of Elastic Structures: A Computational Approach

33

Introduction of the notation ( )" = d / d r , n[OD = lT"Q0) = no0[OD= 0 at x,, the expansion of n[Y[r)Dat r = 0 gives

1 1 n=nooo[ODr3+ noo[ODr4+ . . . 3! 4! 0"

-

(3.39)

or equivalently, in terms of p:

1 n = -1 n ( 3 ) [ 0 ~+~3 n ( 4 ) 4 0 ~+ ~4 ... 3!

4!

(3.40)

where ( )(i) = d' / d p u " . For the purpose of determining the sign of l 7 in the critical case, (3.39) and (3.40) are equally applicable. According to our solution (3.37a and b), po = f l ; p"" = 0, and with this we arrive at ~ O O O [ O D

= n(3)~0~(~0)3,

00

I-IOO~OI)

W3)[oD = aTfddaa;

= n(4)~0~(~0)4,

(3.41)

~ I ( ~ ) [=o [aTGddaaa D - 12w0T2~wo21.

Please note that the coefficients (1/3!)II(3)QOD,(1/4!)n(4)[ODare equal to the coefficients A3, A:, etc. in (2.53). It now follows that

~I'~'[OD = aTfddaa# 0 j the critical state xc is unstable

(3.42)

because in that case there is one direction that yields a negative value for the leading term of (3.39) or (3.40). In the case that II(~)[OD = 0, the stability of d, is determined by the sign of ll(4)[OD, so that

I I ( ~ ) [ O D= [arfdddaaa- 1 2 ~ ~ ~ 2 f d w>o oz l j the

~I(~)[oD

critical state x, is stable;

= [aTbddaaaj the

I~W&&,WOZI <

O

(3.43)

critical state xc is unstable.

Of course, when ~I(~)QOD = ~ I ( ~ ) [ O D= 0, the analysis should be continued beyond the terms taken into account here but we will not consider this further. The preceeding results are due to Koiter (1945), who derived them for a general elastic continuum. Koiter obtained these by considering a sequence of minimization problems associated with a potential energy functional defined at the stability limit, i.e., at the critical state where the potential energy functional has a semipositive definite second variation. This derivation is in essence similar to the one preceding.

34

Eduard Riks

Having established the true nature of the critical points, the analysis can be extended by using (3.25) to establish the stability or instability of the equilibrium states that branch off from these points. This part of the analysis is straightforward, so we do not have to go into detail. The results are pictured in Figure 5. Please note that stable solutions are denoted by heavy lines, unstable solutions by dotted lines.

(b)

skew symmetricbifurcation

I

I

I

2.

1'

symmetric bifurcation unstable

symmetric bifurcation stable

(4

(b) F I G . 5. Various forms of loss of stability

Buckling Analysis of Elastic Structures: A Computational Approach

35

The specification of these special points can now be given by Limit points (unstable) (a and b):

A’, ( 0 ,

A3 ( 0 ,

(3.44a)

A’, < O ,

A3 > O .

(3.44b)

Skew-symmetrical bifurcation point (unstable) (a and b):

A{ = 0 ,

A; < 0 ,

A’, = 0 ,

A; ( 0 ,

A3 < 0 , A3 > O .

(3.45a) (3.45b)

Symmetrical bifurcation point (unstable) (a):

A; = 0 ,

A; < 0 ,

A3 = 0 ,

A: < O .

(3.46a)

Symmetrical bifurcation point (stable) (b):

A; = 0 ,

A; ( 0 ,

A3 = 0 ,

A; > 0 ,

(3.46b)

where the coefficients A’,, A;, etc., are given by

Strictly speaking, these results are only valid for critical points in the sense discussed before, i.e., they are points that mark the occurrence of loss of stability and they are therefore always connected with at least one stable branch (here defined as the primary branch 1). If this condition is not met, all branches connected with the singular points are unstable. It also follows from the analysis given above that the occurrence of a stable critical point is rather exceptional from a mathematical point of view. Nevertheless, in structural engineering, the stable critical point is very well known, because plates and stiffened compression panels often behave in a way that is governed by a symmetrical, stable bifurcation point. It can be further noted that the difference between the two limit points given here is trivial from a pure geometrical point of view (as is the difference between the two skew-symmetrical points (3.45) (a) and (b)). It turns out, however, that during the analysis of a particular problem, both types of limit points can be encountered. For example, in buckling experiments under end-shortening control, snap-through at a limit point (3.44a) may lead to a stable postcollapse state. Unloading from this

36

Eduard Riks

state will then result in a snap-back to the original postcollapse primary state at a point that is defined by (3.44b).

E. REACTIVE FORCES AT THE CRITICAL STATES It was already established that a stable equilibrium state x acts like a point attractor in the sense that the reactive forces induced by small forced perturbations from this state tend to restore equilibrium. It was also shown that when an equilibrium state x is unstable, there exists at least one perturbation y that induces a reaction force that tries to pull the state away from the equilibrium point. But what is still uncertain is what happens to the forces of reaction around and at the critical equilibrium states themselves. The function to be investigated is given by (3.18):

R = -f(yD is here the reaction force for the perturbation y from d. At and around the critical states it is again advantageous to try perturbations in the form y = pa v; a'Tv = 0. It can quickly be verified that at a critical state, perturbations y = v lead to forces R(vD that are still attractive, because in that case the leading term of

+

(3.48) is positive. More interesting are the perturbations from d, in the directions that minimize (3.15), i.e., y = A p a Ap'w20 for small lAp1. Introduction into G delivers, after evaluation,

+

G=

3A3Ap3

+ 4AzAp' + O(Ap5)

rn

(3.49)

where the cofficients A3 and A: are given by (3.47). It is thus seen that for a small perturbation of the type y = A p a Ap2w20 at a skew-symmetrical bifurcation point with Ag < 0, the reaction force is repellent for A p > 0 and attractive for A p < 0. In the case in which we deal with a symmetrical bifurcation, i.e., points of the type A3 = 0; A: # 0, the forces are repellent when A t < 0 and attractive when A: > 0 (see Figure 6). In the case of a proper limit point, we have A3 < 0, and

+

Buckling Analysis of Elastic Structures: A Computational Approach

+

37

T: skew symmetric b i b t i o n

Limit point

+ +:+ h

11

symmetric bifurcation unstable

symmetric bifurcationstable

FIG.6. Perturbation forces.

the result is similar to that of the skew-symmetrical bifurcation point. Note that (3.49) can be written as G = Sign(ApDg(Ap; OD

(3.50)

where g[Ap.; OD = g ( A p ; AhDlah=o is the reduced form of (2.53) evaluated at Ah = 0. Thus the sign of ApguApL; OD determines whether the perturbations represented by & A p are attractive. To complete the picture of the perturbation forces, we should also investigate perturbations from the equilibrium states connected with the critical states, i.e., along the branches represented by y = 0; Ah # 0 + Adup) = d - d, = pa p2w20 . . . at Ahgp) = h [ p ]- hc. In this case it is sufficient to look at

+

+

Eduard Riks

38 perturbations

and determine the sign of

G=

GTf[Ad

+ 6; A@))

(3.52)

11611

It turns out that for small IApI, this expression can be reduced to

G = Sign[ApDg[p

+ A p ; Ah[p]D.

(3.53)

The force diagram of the branches of solutions around and at the critical states x, can thus be investigated by looking at the sign of G defined in (3.53). The result of this investigation is pictured in the force diagrams of Figure 6.

F. INCIPIENT MOTIONAT UNSTABLE POINTS Because one of the principal objectives of this paper is to consider the computation of the transient behavior of a structure after loss of stability has occurred, it is of interest to study the initial motion of a structure when it is perturbed from an unstable critical state. To keep the discussion as simple as possible, we will focus on a system that is truly conservative, so that there is no damping present. In that case the equations of motion are given by

MZ

+ f[d; hD = 0

(3.54)

where M is the mass matrix of the system and ( ) denotes differentiation with respect to the time t . We will now suppose that the structure is first loaded up to the critical point = [d,; h,], and after that it is forcefully kept in a position that = [d, z; A,]. corresponds to the critical state x, plus a small perturbation: The perturbation z is given by

XT

+

z = Ea

+

& 2 w20

(3.55)

where E is an arbitrary small number and a and w20 are the ingredients of the solution of the minimum problem (3.31), see pages 21-32. In this disturbed state at t = 0, the structure is suddenly released. For the solution of the motion that now follows, we have the following initial conditions:

d[OD = Z; d[OD = 0.

(3.56)

Buckling Analysis of Elastic Structures: A Computational Approach

39

Let the solution be denoted by Q[tD = dut, ED, so that Q[tD satisfies (3.54) identically. Thus Q represents a curve in the N-dimensional space RN parameterized by the time t. This parameter choice is natural, but for what follows it is advantageous to introduce also the geometrical path parameter o that we introduced earlier and then let o be a function of the time t , thus: a = out) and Q = Q[o[tDD. If (.)’ denotes differentiationwith respect to the path parameters and, as before, ( ) denotes differentiation with respect to the time t , it is then possible to write the acceleration $ in the form

.. =

Q

Q’f?

+ Q”2.

(3.57)

It is now noted that because of the initial condition introduced at (3.56), the velocity 6 along the curve Q[aD at the very beginning of the motion ( t > 0) will will even be smaller. Consequently, the centrifugal term be small, and thus (c?)~ in (3.57) can be neglected with respect to the term that represents the acceleration along Q[aD during the initial stage of the motion. Thus, for small t the curve Quo) is approximated by the solution of the system:

(aTMd’[tD - 1 ) d t = 0;

~ [ o=)f?

(3.58)

where the second equation defines the path parameter o.It can now be demonstrated, that the particular solution of (3.58) for small excursions o from the critical state in the direction (3.55), is identical in form to the solution of the equations that determine the curve of the steepest descent or slowest ascent of the potential energy surface, pages 30-31. (If we choose T = M, assuming M is symmetric and positive definite). In other words, the path that the structure will follow upon a disturbance (3.55) from the critical state is initially of the form: Q = o a + o 2 w20

(3.59)

where a is the buckling mode and 2w20 = 1’’is given by (3.38). Having established this correspondence, it is now possible to use these observations in a simple characterization of initial motion in terms of the gain in the kinetic energy just after t = 0. The law of the conservation of energy states that the sum of the kinetic and potential energy is invariable, thus: T2[c$

+ P[dD = C = Constant

where 1 *T T2 = - d Md = the kinetic energy of the structure.

2

(3.60)

40

Eduard Riks

As argued, the path of the motion for t > 0 is approximately given by (3.59), and substitution in (3.60) gives T2 = -Pupa

+ p2w20D + C .

According to the initial conditions (see (3.56)), at t = 0, T2 = 0, so that C = PUEa E ~ w ~and o ] this , gives for the variation of T2 when t > 0,

+

T2 = -Pupa

+ p2w20D + P[Ea + E ~ W ~ O D

or (3.61) for p: I E J 5 IpI. Please note that this particular solution is only meaningful in the cases (i) A3 < 0; p > E > 0 or A3 > 0; p 5 E < 0 and (ii) A3 = 0; A: < 0. Thus it is possible to conclude from this construction that an arbitrarily small perturbation E from an unstable critical state, applied in the proper direction (3.59), induces a motion with a lunetic energy gain T2 in the early stages of the motion, which is described by (3.61). This gain is proportional to A p 2 or A p 3 (depending on whether A3 # 0), where A p = p - E is the distance traveled from the point at which the motion started at t = 0 (see (3.61)).

IV. Computations A. LOCALAND GLOBAL ANALYSIS The need to understand how a structure behaves under the loads for which it is designed and, in particular, how and at what intensity of the load it will fail is the primary motivation for conducting a stability analysis. Usually the question of the load-carrying capacity is not focused on one particular configuration of the structure alone, and it is almost never the case that only one particular set of loads must be considered. In general, the analysis must take into account a whole array of possibilities where variations in the eqs. (2.9) are thus also dependent on external parameters other than the load, and there can be many. Suppose for simplicity that there is only one design parameter v in addition to the load intensity A. The equations of equilibrium are then written as

fud; A;

UD

= 0.

(4.1)

Buckling Analysis of Elastic Structures: A Computational Approach

41

This could be a characteristic length or anything that influences the design and therefore the properties of the structure. In this particular case we can picture the type of analysis that is required in a three-dimensional diagram (see Figure 7). Once the solutions of the equations are obtained, their characteristics can be described by plotting one of the components di of d against the values of h and v, as is done in the figure. A general representation of solutions in the case of the two external parameters h and v is

(4.2)

where p and t are some suitably chosen surface coordinates of this twodimensional equilibrium surface in R N + ~The . stability analysis in the practical situation can now be seen as the calculation of certain patches of this surface. For example, in Figure 7, this equilibrium surface is thought to belong to a structure, which for the design parameter v = 0 has a linear load deflection response I that is intersected by a bifurcating branch of equilibrium states I1 in A . The intersection point in the plane v = 0 is the bifurcation point. At this point the structure will become unstable; i.e., in the case drawn, it will buckle violently, a phenomenon called snap buckling. For values of the design parameter v > 0, the snap-buckling behavior at a bifurcation point is changed to a snap-buckling behavior at a limit point ( B , C ) , but the load at which this occurs is different, usually lower than in the case v = 0. Thus the influence of changes in the design on the structural response behavior is often an important part of the analysis, and it is natural make this analysis by computation of the responses, for example, of several traces of (4.2), as is given by

d = d[cj,

~ ( y ] ,

i = l , 2 , 3 , 4,...,

v,D,

h = h[uj,

(4.3)

~ ! = 1 , 2 ,,3. . .

The analyses mentioned earlier (Young and Rankin, 1996; Vandepitte and Riks, 1992) are based on these types of calculations. Other situations do present themselves, however. For example, if v is a measure of damage, like the length of a crack in a fuselage shell, one may want to compute the response of the structure under a stationary load but increasing length of the crack. In this way the surface is traced according to

d = d[v,D,

h = constant,

Q!

= 1 , 2 , 3 , .. .

(4.4)

42

Eduard Riks

Applications of this type can be found in (Rankin et al. 1993; and h o p s and Riks, 1994). There are situations where the calculation of the static solutions is only part of the complete analysis. This occurs when we are interested in computing the dynamic response of the structure after the static equilibrium is lost when h is about to exceed A,. In Figure 7 this occurs at the ridge of the hill that emanates from the bifurcation point h, = h,[v = OD. In that case, the transient behavior of the structure is computed from the equations of motion (3.54),augmented with some damping term. This process will lead to a change of configuration from d, to an end-state dnew (the existence of which will be assumed), which will then be stable. The new equilibrium state d,,, is in general associated with a far-field solution of (4.1) in the sense that Jld,- d,,, 11 is finite and usually large.

“t

FIG. 7. Global

analysis.

Buckling Analysis of Elastic Structures: A Computational Approach

43

An analysis that is conducted by computing finite stretches of the equilibrium surface in Rn+2, or by computing a transient trajectory in this space with the time as path parameter, concerns global equilibrium states or global transient states that are computed point after point. This can be referred to as global analysis. Global analysis is typical for most of the finite-element analyses that are done in the nonlinear domain. But in addition to the global approach, it is also possible to use a local approach in which the solutions are sought in terms of a power series expansion that involves only local information belonging to a single solution point of eqs. (4.1). This type of solution presents an approximation of the equilibrium surface in the neighborhood of the point of which the series expansion is developed. It is a much older method, known as the perturbation method, asymptotic method, or the method of successive linearizations. In this paper we will refer to this type of method as a local approximation method. The theory described by Budiansky (1974) typically concerned the state of the art in local analysis methods, because it was exclusively concerned with the perturbation solution of bifurcation problems. Global methods often make use of local approximations, as predictors, for example. On the other hand, local methods of stability analysis sometimes rely on the use of global techniques. The perturbation method applied to the case of a compound bifurcation point generates multidimensional (reduced) equations of the type (2.59) (see, for example, Carnoy, 1980; Arbocz, 1987; Lanzo and Garcea, 1996), which are then easily solved by a global path-following technique. In this paper we will not dwell extensively on the further development and finite-element adaptations of the local approach that took place after 1974, because this would carry us to far from our main objective. However, we will use some of these techniques whenever this turns out to be an advantage. A local approximation technique that will be helpful here is the so-called linearized buckling analysis, by which estimates of the location of the critical state can be obtained in relation to the global state in which this method is used. Our main interest is, however, the global approach, and to introduce it properly we must start with Newton’s method. B. PERTURBATION VERSUS PATH-FOLLOWING METHODS The difference between local methods and global methods can best be explained by considering the solution of the response of a structure under the influence of a load system that is varied through a single parameter A. As before, we consider the equilibrium equations augmented with the equations that define the path parameter

F[x;

OD

= 0,

E RN+1

(4.5)

Eduard Riks

44 where

Suppose that a solution of (4.3, x = X I , is known beforehand at a = 01, and that Fx[xlD = nonsingular. In that case we can attempt to compute the Taylor series that we encountered earlier:

where the local quantities, the configurationxi and the path derivativesx', , x:, defined by

. ..,

are determined by a sequence of derivatives defined by (2.23). The construction of this solution x = E[oD is straightforward once the derivative terms F,,x',x;, Fxxxx',x~x',, etc., developed at xi, are obtained, because in that case, the solution of the sequence (4.7a, b, c, . . .) entails only one factoring of the matrix F, followed by a number of back-substitutions equal to the number of terms of that one wants to take into account in (4.6). However, as far as the range of validity of the solution (4.6) is concerned, nothing can be said in advance, and the outcome will depend on the type of problem at hand. The global way to construct the same solution is to develop this solution in terms of a number of points xi along the path defined by (4.1) for fixed values of the parameter oi: a1 < a2 < 0 3 < . . . . The way this is done is by using a predictor-corrector scheme that is referred to as the path-following method. Again, if x1 is known beforehand, we could use eqs. (4.7) to compute the derivative x', . With this information, it is possible to construct the approximation <(')[azD = X I X; ( 0 2 - a])for the step 01-+ o2.To obtain the true value of x(Ia2D,we can, at this stage of the computations, use a corrector process:

+

c(i)= W["'-')D

for i = 1 , 2 , 3 , . . .

(4.8)

which means a process whereby the function W[((i-l)D is successively evaluated and which is designed to yield E(i) + x[a2D for i (= the so-called iteration count) large enough. If the iterate does yield the desired solution x[a2D, which can be checked by computing di) = F($(')Dand checking whether di) -+ 0, a new estimate c(O)[o3D = x2 xh(o3 - 0 2 ) can be constructed, and the corrector process described above can be repeated to yield x3, and so on. The path-following procedure that emerges on the basis of these operations is usually equipped with

c(i)

+

Buckling Analysis of Elastic Structures: A Computational Approach

45

a formula that determines the step size A a = ai - ai-1 for each new step and a number of other features that are convenient for evaluating the solutions obtained (Riks, 1984a; Seydel, 1989). One of the crucial factors in a path-following procedure is the selection of the corrector process, i.e., the iteration function W, because this function is in many ways determinate for the efficiency of the computations. There are various possible choices, but the most popular ones can, in some way or another, be linked to Newton's method. In particular, when stability analysis is the main motivation for using the path-following approach, Newton's method is of great importance for reasons that will become clear in this discussion. In the previous considerations we started the computation of the new solution x2 from the predicted solution t ( O ) . To obtain an improvement to this predicted value, one can consider the expansion of equations around t ( O ) : 1 F[<(O'D F,[<(')D(x~- tco))5 Fxx[$(O)D(x2- t(O')(x2 - t"))

+

+

+ o(x2 - t('))3 = 0.

(4.9)

By neglecting higher order terms beyond 0 (l),this gives

~ ~ [ t ( O ) ~-({ (tO() )l )= - F [ ~ ( ~ ) D

(4.10)

where ( ( l ) is (it is hoped) a better solution to (4.1) for CT = a2 than t ( O ) . We can also write $ ( I ) = ,$(O)

-

[Fx[<(")]]-'F[t(')].

(4.1 1)

Further improvements can be obtained by repeated computation of t(i)= t(i-1)

- [Fx[((i-1)DI-l F[t (i-111,

(4.12)

i = 2, 3, . . . , and we see that the iteration function W in (4.8) in this case is given by W =t

-

[Fx[tD]-lF[tD.

(4.13)

With (4.13) as iteration function, the method (4.8) is called the method of Newton-Raphson (Raphson's name is connected with it because Raphson, a friend of Newton, formulated the method in the operational form we now know and use (see BiCaniC and Johnson, 1979). Probably more is written about Newton's method than any other iteration method, and the knowledge of its properties is extensive (see, for example, the classic monograph by Ortega and Rheinboldt, 1970).

Eduard Riks

46

For the present discussion one property is very important. This concerns its overall convergence characteristic. If the Jacobian F, in (4.1) is nonsinguhr at and in some neighborhood around the solution point x, it is possible to find a neighborhood a:IIx - t1I2 < 6' around x, for which the following holds. A starting value <('Ithat lies in this neighborhood will produce iterates t(i)that stay in this neigborhood and that will eventually converge to x (Ortega and Rheinboldt, 1970). Thus if $(o)(a2D= X I +xi (a2-01) is "close enough" to x2 in the procedure described above, the process (4.12) will eventually yield x2. Although it is not possible to know beforehand how small or large the domain i2 is, it is still possible to exploit this characteristic by taking the prediction step Aa = ( ~ -01) 2 so small that it is possible to satisfy (4.14) on a trial and (sometimes) error basis. Another pleasant property of Newton's method is that if convergence takes place, this occurs at high speed, i.e., quadratically:

I x2

-

pi)1 < p l )) I x 2

-, p l )

112,

) 0. where c ( ~ - ' >

(4.15)

Newton's method, however, is very expensive in terms of numerical operations. This follows because the Jacobian F, is factored in every iteration, and this process is very laborious, even when the bandwith of F, is small in comparison with the dimension ( N 1). For that reason, Newton's method is often simplified by changing the corrector process:

+

t(;)= t(i-1)

- [F,ut(~)D]-'Fut(;-')D

(4.16a)

to ((i)

= t( i- 1 )

-

[F,ut(O)D]-'FUt('-1)D

(4.16b)

or (4.16~) so that factoring is limited to one time per step Aa. The simplification (4.16b, c) of Newton's method, whereby the argument of F, is kept unaltered during the iterations, is known as the modified method of Newton. In (4.16b, c) it is formulated at either the prediction t(') or on the previous solution X I . Other variants, for example, keeping the factored F, unaltered during a number of continuation steps Aa, are also possible. The convergence properties of the modification are similar to that of the original method, but the rate of convergence is no longer quadratic and for t is smaller.

Buckling Analysis of Elastic Structures: A Computational Approach

47

An attractive feature of Newton’s method is that it operates on the Jacobian

Fx, which contains (implicitly) essential information about the condition of the iterate [ ( i ) , a state that is approaching the actual solution x2. It turns out that this information can be wrested from the factoring process during the iterations. In this way it is possible to detect when a bifurcation point or limit point is near. It is also possible to guide the path-following procedure to find these points with some prescribed precision, as we will describe shortly (for more details, see Riks, 1978,1984a; Riks and Rankin, 1990; Seydel, 1989). The calculation of the static equilibrium path x(a), starting from some known solution XI,can thus be carried out (i) by using a local approximation developed on the basis of a power series expansion (4.6), or (ii) on the basis of a pathfollowing scenario (see Figure 8 for an illustration). At first sight, the perturbation approach seems very attractive, because the scale of the operations appears to be considerably smaller that of the path-following technique. The comparison becomes interesting when we set the regular perturbation around X I versus the

(A)

(B)

FIG.8. Local approximation (A) versus global solution (B)

48

Eduard Riks

path-following procedure, with the modified Newton method as corrector. In that case we have for the first method

XI"' = [F,[X~D]-'R(~),

a = 1 , 2 , 3 , .. . , M ,

(4.17)

where the superscript ( a )means the ath-order derivative terms with respect to the arclength s (defined at (4.7)). For the second method in the step from x1 to x 2 the operations are

A((') = ((i)- ((i-l) = -[Fx[xlD]-'Fl(('-'); i = l , 2 , 3 ,..., K .

g2),

(4.18)

We observe that the numerical operations for the two methods are similar. However, the evaluation of the right-side R@) in (4.17) is more difficult than the evaluation of F[c('-'), 0 2 ) in (4.18) because R@)are combinations of terms that represent directional derivatives of F ((see Mackens, 1987), for the way these derivatives can be computed). It is true that in many cases, more steps of the second procedure (4.18) are required to cover the same range for which expansion (4.6) is used, so that it appears that the perturbation solution is to be preferred in terms of expenditure of operations. There is one difficulty, however. Without further computation (i.e., without monitoring the measure e2[aD = IIF[E[aDD 112) there is no way to ascertain the range of a, 01 5 (T 5 a2 for which the expansion can be used without losing too much accuracy. Moreover, there is still the question of how XI,which is supposed to be a solution of (4. l), should be obtained. Only in the case of A = 0 is the solution d = 0 (the undeformed state) available without computation. In all other cases x1 must still be determined from (4. l), and if x1 is part of a true nonlinear solution path, this can only be done with an all-out iteration scheme. The perturbation method is often used for the solution of problems in which the primary path XI[.) (connecting the undeformed state with x,) is linear or approximately linear. In this particular situation, the primary path XI = aX1 and the critical point that is part of it, xc = a,X1, can easily be determined.The expansion (4.6) is then applied to determine the equilibrium states XII[CT] branching from x,. In the general case, however, the primary solution is nonlinear, so that XI[DD must first be represented by a solution of the type (4.6) or by a set of points obtained by a continuation method. This means that when the primary path is nonlinear, the difficulties with the perturbation approach multiply, and it is then no longer clear whether this method is really competitivewith the continuation approach. Leaving aside the question of the expenditure of computer time, there can be no doubt that path-following methods are more generally applicable and therefore more powerful than perturbation methods, if we compare the two approaches for

Buckling Analysis of Elastic Structures: A Computational Approach

49

the solution of the problems discussed here. It is for this reason that in the following we will consider only path following as a basic computational tool for the global analysis of the static solution branches of (4.1).

C. LINEARIZED BUCKLING ANALYSIS There is a local approximation method that is very useful in the type of calculations that are described here. This is the so-called linearized buckling analysis mentioned above. It is a method that makes it possible to determine the approximate location of a critical point measured with respect to any point xk that is computed by the path-following method described earlier. In general, the pathfollowing procedure computes the response of the structure in terms of a sequence of points:

i = 0, 1, 2, 3, . . . ,

xi = x[qD,

ai-1

< ai < q + l .

(4.19)

In most cases this process is started from the undeformed state,

xo = 0

(4.20)

the only solution of (4.1) that is known before any calculations are carried out. With the linearized buckling feature it is possible to develop at each new point xi the local (linear) approximation to the equilibrium path at that point:

y = xi

+ (a - ai)x;

(4.21)

where xi is the current solution along the path just determined, and xi is the first path derivative of x[aD at xi. The derivative is computed at the end of the iteration process that leads to xi, using

xi = F,[xiD- 1e,+l

(4.22)

and is thus easily computed. The representation y = y[cD in (4.21) is tangent to x[aD at X I and approximates x[aD more accurately the smaller (a - al)becomes. Suppose the equilibrium states xi computed thus far are stable, i.e., all xi satisfy the condition that K[qD = K[xiD = positive definite. Loss of stability occurs when for some value of the parameter a = a, > ai : K[x[a,DD becomes semipositive definite, or when x[acD satisfies

aTa = 1 , K[x[a,DDa = 0, v ~ K [ ~ [ >~ 0,~ D DVV:~ vTa = 0, see also Section 1II.B.

(4.23)

Eduard Riks

50 A necessary condition is

Det{K[x[ccDD} = 0.

(4.24)

We note at this point that a distinction between a bifurcation point and a limit point can be made by observing that at a bifurcation point F,[cT,)must also be singular (see Section 11),whereas at a limit point Fx[acDis still regular (in general). Ahead of xi, the solution x[aD is not yet known, but we have the approximation ~ [ C T ] , and thus it is possible to define an approximation to the critical state x, by setting

This is a nonlinear eigenvalue problem that can be solved by using Newton’s method, for example. It is easier, though, to use straightforward linearization, i.e.,

(4.26a) where (4.26b) The solution of this problem, the smallest eigenvalue ACT*= CT* - 01 and corresponding eigenvector a*,then presents an approximation to the values that belong to the still unknown critical state x,. The estimate of the latter is thus simply given by X*

= xi

+ AD;X~

(4.27)

+

ACT:^^. which includes, of course, the estimate of the critical load h* = hi Applied at the undeformed state xT = (dT,h ) = (0, O), the method coincides with the classical linearization, which assumes that the unbuckled state is given by dI = Ado, where do is the solution of K[ODdo

+ f h = 0.

(4.28)

Many practical structural designs that are optimized with respect to their weight (stiffened panels, for example) behave in this way, exactly or approximately. In these cases, the linearization process provides accurate solutions to the buckling load of these structures. Thus the (local) approximation method defined by (4.26) and (4.27) makes it possible to find estimates of the location of the critical state x, (which is part of

Buckling Analysis of Elastic Structures: A Computational Approuch

51

the curve x[aD) ahead of the known solutions xi ( i = 1 , 2 , 3 , . . . , k ) . From here it is now only a small step to design a procedure that automatically zooms in to the critical point x, (when such a point is anticipated). Several such approaches to this effect are possible (see, for example, Riks, 1973, 1978, 1984a; Seydel, 1989). However, even without an automatic search procedure, the simple feature described at (4.26) is already very useful to have at hand. Methods that are designed to compute the critical states of the solutions of the equilibrium equations are often divided in two categories, called “indirect” and “direct.” Direct methods are formulated in such a way that the solution of the critical state is obtained directly without use of the equilibrium path that is connected with this point (see, for example, Wriggers et al., 1988). An indirect method, on the other hand, is a method that makes use of the equilibrium path that is leading to this point x,. In practice, the distinction is not very significant (although this is not always realized), in particular because there are almost no differences in the type of operations that are required. In this paper we will restrict the discussion to a sketch of the indirect approach, because the steps of this method blend more naturally with the context of the analysis described here. An indirect method of calculating a critical point, starting from some point xi, can be constructed by observing that the distance An: obtained in (4.26) and (4.27) can immediately be used to compute the new step (point) xi+l = x[ai +Aa:) along x(a), using the standard continuation method discussed earlier.

I1 FIG.9. Computation of the critical state.

52

Eduard Riks

Because this new point xi+l is likely to be closer to x, than xi is, the new estimate xi*+1for x, computed from xi+l is also expected to be better than the previous estimate xi* (see Figure 9 for an illustration). The process can be repeated over and over again, with the result that one can find a sequence Xi+k, k = 1 , 2 , 3 , . . . , xi*+K,so that llxr,, - x,ll < E for K large enough. (In many practical situations, K = 2 or 3 is already sufficient to yield an acceptable result, depending the location of the starting point xi. See, for example, Rheinboldt (198 1)and Riks (1978)).

D. BUCKLING AND POSTBUCKLING ANALYSIS We are thus in the position to compute the quasi-static response of the structural model by using the path-following method up to and beyond the point at which loss of stability occurs. As indicated in the previous section, it is also possible to determine the critical state x, to some degree of accuracy. The critical state is a limit point if the component kQaDof the branch through x, is descending after A, is reached. Otherwise, x, is a bifurcation point. In either case, it makes little sense to compute the path x[aD far beyond the state x,, because for a > a,, x[aD is unstable. In the case of the limit point, the static response of the structure can be considered to be completed because there is no more information to be gained by further computation. Only when x, is a bifurcation point might it be of interest to compute a stretch of the intersecting branch. In this way, it is possible to identify the bifurcation point without computing the derivative terms (3.47) that determine its classification. The computation of the branch of a simple bifurcation point by continuation is just as difficult or easy (depending on one’s point of view) as the computation of the primary branch, provided the proper initialization can be provided. As explained, accurate estimates of the critical state x, can be obtained with the methods discussed earlier. The initialization of the path-following procedure for the computation of the branch 11, with x, as the starting point, can easily be carried out if the tangent to XII[CTD at a = a, is also known at this point. The procedure that is necessary for this type of computation is called brunch switching, because it switches the computations from one branch to the other. Thus it seems completely natural to use a predictor for branch I1 given by (4.29) noting that at the same time, direction associated with this step must be introduced into the auxiliary equation of (4. l), so that

Buckling Analysis of Elastic Structures: A Computational Approach h(d; h ) - o = x : . ~ ~ ~ (x,x) - c = 0.

53 (4.30)

This idea, which is illustrated in Figure 10, works well in the case that we have studied so far, i.e., the simple bifurcation point. During the calculation of x,, it is always possible to obtain a good estimate of the buckling mode a and the tangent xi to the primary path XI (see, for example, Riks, 1984a; Riks et al., 1990). The desired direction vector xLIIis then a linear combination of these two vectors:

xiII= PX:.~

+ pa.

(4.3 1)

The two scalars p and fi can be determined from the theory and depend on the factors aTfddaa,aTfdha.The problem here is the computation of these factors, because the higher order derivative terms fdd, etc., are not automatically available in a finite-element program. A possible way to circumvent this difficulty is to use instead of (4.31) the modified predictor: ["= X,

+ Aob,

g(d, h ) = bT(x- x,) - ACT= 0

(4.32a)

where b is given by

b = .xiI

+ pa,

bTXiI = 0,

bTb = 1.

See Figure 11 for an illustration.

bmlch X n ( 0 ) FIG. 10. Branch switch, the natural approach

(4.32b)

54

Eduard Riks

XdO)

FIG.1 1, Branch switch, a simplification.

The aforementioned description of the way switching of direction at a bifurcation point can be accomplished during the computations of the branching diagram concerns only mo examples of a large number of variants. In the computer program that is used here, a rather different method is implemented which is due to Thurston (Thurston et al., 1985),and which is essentially a Newton-Raphson iteration scheme applied to the transformed set of eqs. (2.53) (see also Riks, 1984b). This so-called equivalence transformation method is more difficult to implement than the simpler methods discussed above, but it has turned out to be a very robust method that can also be used for the analysis of compound bifurcation points (a phenomenon not studied in this paper) if the multiplicity of these points is not too large.

E. TRANSIENT BEHAVIOR The branching diagrams that can be computed by the methods described above enable us to deduce the extent to which we can load the structure before loss of stability takes place. This evaluation follows from the location of the critical points encountered and the shape of the solutions in their immediate surroundings. Although it cannot always be known beforehand, in many cases, loading beyond an unstable critical point will cause damage to the structure. Damage is inevitable when the gain of kinetic energy during the buckling process is so large that the structural system is no longer able to convert it properly. If this occurs, the motion will end in a state in which the system is no longer serviceable. A well-known example of a structure that will be destroyed after becoming unstable is the thin-walled cylindrical shell in compression, whereby the load system is of the dead-weight type.

Buckling Analysis of Elastic Structures: A Computational Approach

55

On the other hand, the possibility also exists that loss of stability does not end in destruction. This takes place when the kinetic energy build-up during the motion remains relatively small (in comparison to the accumulated elastic energy of the structure, for example), and the motion ends in a new stable equilibrium state without accompanying damage (see Figure 12). The structure is then still serviceable in this state and in fact can be loaded even further. Examples of mechanical systems that continue to function after the first unstable critical point is passed can be found among certain stiffened panel configurations (see, for example, Stein, 1959a, b). In these cases, a loss of stability manifests itself as a sudden change in the buckling pattern a phenomenon like the load is further increased that can recur. The phenomenon of repeated mode changes that take place at certain instances while the load on the structure is steadily increased is called mode jumping. As mentioned in the Introduction, to be able to deal with these problems, we must take into account the transient nature of the jump or jumps. It should again be emphasized that the main theme of this chapter is the analysis of the behavior of a conservative structure under a load that is slowly varying. In

destruction

case a

case b

FIG. 12. Destruction dependencing on the amount of energy freed

56

Eduard Riks

the first stage of the loading program, the deformation of the structure will follow the single and stable equilibrium branch that passes through the undeformed state. Because the equilibrium along this path is stable, this slowly varying load factor implies that the response of the structure d = d[hD is also slowly varying, so that the velocity i and acceleration d can be neglected. The time scale during which this process takes place is thus very large. In contrast, when the equilibrium becomes critical and unstable, snap buckling will occur. This is an uncontrollable motion that starts from the neighborhood of the critical state and ends at some new stable equilibrium state. During this motion the load is still slowly varying in accord with our assumptions. However, the duration of the buckling motion now turns out to be very small for the cases to be considered here. For example, for the problems still to be discussed in Chapter 5, the time interval of the complete motion is seldom in excess of 40 milliseconds. The change in the load is thus negligible during the time the transient buckling process takes place, and it is this simplificationthat we will adopt in the remainder of this paper.

F. TRANSIENT ANALYSIS The transient change of deformation at buckling is governed by the equation of motion that we now introduce in its complete form, i.e., including a damping term:

Md + C i + f [ d ;AD = 0

(4.33a)

with the initial conditions t = 0:

d [ t = OD = Z,

hut = OD = VO.

(4.33b)

As before, M is here the mass matrix that represents the inertia of the structural model under consideration. For our purpose, it is sufficient to use viscous damping contained in the term C i . The damping term is necessary to simulate the dissipation of the kinetic energy that becomes available during the transient change of state. In this way it is possible to let the motion end at a new stable state of eq~ilibrium.~ We are thus faced with the problem of integrating this large system of equations of motion. This is a subject that received considerable attention in the field of 3H0w the amount of damping is determined in a particular analysis is discussed by Riks et al. (1996).

Buckling Analysis of Elastic Structures: A Computational Approach

57

computational mechanics (see, for example, Belytschko and Hughes, 1983, and the text of Argyris and Mlejnek, 1991). Because the literature on these methods is extensive, we will only briefly comment on the type of method that we will be used here. Suppose the structure is in motion and that at the time t = tl the configuration dl = d[tlD and the velocity i~ = d(tlD are known. In that case, the acceleration ;[ti) = i l is also known through the equations of motion (4.33). To compute the state of the motion at the time t2 = tl At2, it can be assumed that the acceleration 8[tD between the time steps tl and t2 is reasonably well represented by the interpolation

+

(4.34) where a is the still unknown acceleration at (t2):

..

a = d(tD

(4.35)

and \yl and q 2 are interpolation functions, for example,

which must satisfy (4.36) The assumption (4.34)-(4.36) allows us to make use of the integrals

(4.37)

where it is noted that the integrals rn and w are explicit expressions in t and the still unknown vector a. The acceleration vector a can now be computed by requiring that a should satisfy (4.33a), thus:

This is a system of nonlinear equations in the unknown vector a , which can be solved by Newton's method, for example. Once a is computed, the process of integration can be repeated for the new step t2 -+ t3, and so on.

58

Eduard Riks

The example of the transient method given above belongs to the so-called Newmark family of methods. The method is called “implicit” because it requires the solution of the system (4.38), involving the nonlinear function f[0@2; a); h[t2DD, where a appears implicitly. Thus this is an iterative solution process comparable to the corrector operations of the path-following method. On the other hand, explicit methods, which we will not consider here, do not require such an elaborate process. These methods can be derived from the above scheme by replacing a in the argument o f f by an extrapolation based on the values of d, I and 8 in the previous step or steps. In this way an iterative solution of eq. (4.38) can be avoided. The method sketched in the foregoing makes use of the configuration d[tl D and its first and second time derivatives at t l . It is also possible to use other steps d[tojj, d[t-lD, etc., in the interpolation (4.36) that were computed before d[tlD. In that case, the method is called a multistep method. Multistep methods, such as the method of Park (1975) (see also Argyris and Mlejnek, 1991), which will be used here, thus use information of the past for the future, and in this way have a built-in tendency to dampen the motion, particularly the high frequencies of the motion. Implicit methods are numerically more stable than explicit methods, by which it is meant that implicit methods allow for larger time steps Ati to be taken before divergence of the method takes place. For a precise discussion of the concepts of numerical stability and accuracy of these methods we refer to Belytschko and Hughes (1983).

G . TRANSIENT ANALYSIS AFTERLOSS

OF STABILITY

To supplement a static analysis by computing the actual buckling process, we must be able to apply these transient integrators mentioned above, starting from the equilibrium points at which loss of stability occurs. In this way, the equilibrium solutions that are obtained by static analysis are used as an initialization for the transient analysis of the buckling process. It is possible, at least in principle, to use the scenario of a slowly increasing load, h = hut), starting from h = hut = OD = 0, and then study the passage (in time) through the points of loss of stability (see Marke, 1995). In view of the static methods of analysis that are available, it seems more practical, however, to use a perturbed equilibrium state in the neighborhood of the critical points in the initial conditions of the buckling motion. It is at this point that the question arises of how one should proceed, i.e., in what way should the static solution process be matched to the static part, or equivalently, how should the initial conditions (4.33b) for the buckling motion be formulated?

Buckling Analysis of Elastic Structures: A Computational Approach

59

As can be concluded from the analysis in the foregoing sections, the unstable equilibrium states in the neighborhood of the critical points are actually degenerated attractors from which a perturbed configuration will be repelled if the perturbation is chosen in the proper direction, i.e., the direction for which the loss of stability takes place. We can deduce this from the force diagrams in Figure 6. For example, the (perturbed) configurations [d,.+ Ad; A, Ah] presented in Figure 13 by (A), (B), and (C) are appropriate for this purpose. The recipe for this type of initialization can thus be described as follows. Take the solution point nearest the critical state on the unstable secondary branch of the critical state that represents the point of loss of stability (B), (C). If no secondary branch exists, take the nearest point beyond the limit point (A). Use this configuration as the starting value of the transient procedure and apply a slight increase to the load. Thus if the nearest point is given by d = d,+, the initial conditions for the computation of the transient buckling motion are

+

(4.39) Please notice that in Figure 13, A-C, the configurations [d,+; A,+] are indicated by a shaded bullet and the jump configurations [d,+; A,+ Ah] by a blot. By studying the sign and modulus of the asymptotic form of the test function G in (3.53), it is not difficult to see why these choices will lead to the desired result. The configurations x,+ = [d,+; A,+] are unstable solutions of (4.5) close to the critical state. If the load is raised to h, at d,+, this configuration represents the particular perturbation that we encountered in Section III.E, a perturbation that induces a reactive force on x* = [d,+; A,] that is repellent. Raising the load just above the buckling load h, will only amplify this effect. The foregoing discussion is restricted to the cases of unstable critical points. If the point of loss of stability itself is stable, the secondary branches of this point are also stable and no jump will occur when the structure is loaded up to this point. Instead, the structure will follow one of the two rising paths 2 (case D). The computation of the rising paths 2 is possible with the path-following method discussed earlier, using a switch of direction at x, = [d,; A,]. But it is of interest to note that the transient method can also be used to switch branches if one wishes to do so. The steps that must be carried out in that case are pictured in Figure 13(D). The trajectory the time-stepping procedure is following is finite in length, because during this motion the damping that is present in the model will eventually destroy the kinetic energy build-up that occurred after loss of stability took place. The motion thus subsides and the dynamic configuration of the structure at low

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60

-

stable unstable

I-I * Limit point unstable

Skew-symmetric bifurcation unstable

AS 1:

Symmetric bifurcation stable

Symmetric bifurcation unstable

FIG.13. The initialization of the buckling motion.

‘i

velocity can then be captured by a point of attraction that stands in the way of the motion. At least this is the way that we can interpret the outcome of this dynamic event. It is thus expected that when the kinetic energy T2 becomes smaller and smaller after some time, the configuration of the structure will move closer and closer to a new stable equilibrium state, so that eventually it will be possible to use the dynamic configuration ‘d@D at the step M : t = fM (where T 2 U f $ ~ ] ] < E * ) , as a starting value for the path-following procedure, and compute the new equilibrium point at A, Ah. The necessary condition for convergence to take place in this case is again that the configuration d[tMD should be close enough to the equilibrium solution, and this can be enforced by requiring E* to be small enough. It follows from experience that this initialization does lead to the expected effect, although it is not always possible to know how precise the test T2[‘h[t~)D < E* should be made.

+

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V. Examples and Conclusion A. SHELLMODELING The theory of thin-walled shells plays an important role in structural stability analysis because structural components made of shells are the first to encounter instability phenomena. At the time of Budiansky’s paper, the shell formulations were already well established within the framework of the assumptions of small strains and moderate rotations. The main thrust in the development of the theory before that time had been toward the simplest possible formulation of the theory, to facilitate the solution of the resulting equations. For example, for the analysis of bifurcation problems in shell structures, the Von Karman-Donne11 equations were very popular (and still are; see the exposition in Budiansky, 1974). These equations are the outcome of one of the simplest possible formulations that still take the essential part of the geometrical nonlinearity of the shell behavior into account. They are capable of producing accurate results in many practical situations. With reference to the restrictions of the classical perturbation theory in elastic stability, Koiter (19674 developed shell equations specially suitable for the bifurcation analysis of shell structures. Like the Von Karman-Donne11 equations, these equations are also relatively simple in structure, but do not suffer from the typical deficiencies of the former in a number of situations. With the introduction of the computer, the development of the shell models by finite elements took a rather different turn. At first, attention was still directed at the implementation of existing theories. This implied, for example, the implementation of the Kirchhoff-Love assumptions and a strict adherence to the simplifications that had been so helpful in the development of the equations in the past. It was soon discovered, however, that the development of shell finite elements on the basis of the Kirchhoff-Love assumptions is very difficult and can be replaced by an approach that is based on an assumption that (superficially) looks like the introduction of shear strain effects through the thickness of the shell. This departure from the classical formulation, often called the Reissner-Mindlin assumptions (Reissner, 1945; Mindlin, 195l), facilitates the search for trial functions that satisfy interelement compatibility. A second departure from the classical approach in the formulation concerned the form in which the equations are derived. In the classical theory, the governing equations are almost always presented in terms of differential equations in their simplest possible form, using as many approximations as can be tolerated. In the current shell finite-element theory, these approximations are no longer necessary, so that the “exact” expressions can be retained. Moreover, the formulation is now no longer directed toward the development of

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differential equations, but directly toward the development of ordinary nonlinear equations that can be seen as the discrete analog of the continuum equations. In this way, but also through fewer simplifications, the shell finite-element models that are currently available have a range of validity that surpasses that of the older nonlinear shell theories. Actually, the range of applicability of these models is only restricted by the condition that the strains in the shell should remain small and that the state of stress is approximately a state of plane stress. For example, the shell models developed by Bathe and Bolourchi (1988), Simo and Fox (1989a, b), Simo et al. (1989a, b), Sansour and Bufler (1992), IbrahimbegoviC and Frey (1994), Ramm and Matzenmiller (1988), and Biichter (1992) belong to the Reissner-Mindlin type of formulations. Recent examples of elaborations in terms of the classical Kirchhoff assumptions are given by Bout and van Keulen (1990) and van Keulen (1993). The shell finite-element model that is used in this paper can also be reckoned to fit into the classification of “small strains but arbitrarily large displacements and rotations.” It can be found in the STAGS code (Rankin et al., 1988). This code (structural analysis general shells), originally founded by Almroth and Brogan (Almroth, 1972; Almroth et al.; 1977), is in continuous development at Lockheed Martin and is sponsored by NASA. STAGS is a general-purpose finite-element program that is designed specifically for the stability analysis of shells, although it now has also other features. The shell model that is used here was originally based on shallow shell assumptions, the same assumptions that are the basis of the Von Karman-Donne11 equations mentioned earlier. However, this initial formulation was later extended to the large displacement and large rotation domain by a corotational framework developed by Rankin (see Rankin and Brogan, 1984; Rankin and Nour Omid, 1988). With this extension, the STAGS code is now capable of producing shell models that can be compared directly with the nonclassical developments mentioned above, and consequently they represent the state of art in this field. The development of the discrete modeling of shells has thus come a long way since its beginnings at the start of this century, and we will gratefully make use of its remarkable advances.

B. MODEJUMPINGOF A PLATE STRIP Stiffened panels under compressive loads can exhibit mode-jumping phenomena in their load deflection response diagram. Even the simplest example of this type of structure, the plate strip in axial compression, can show this behavior. Mode jumping is a phenomenon that can be explained on the basis of a con-

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densation of bifurcation points (see Figure 14) in the neighborhood of the (first) buckling load, and the way the branches of these points interact. The analytical treatment of this type of problem poses considerable difficulties. In 1943, a constructive (approximate) solution to the plate strip problem was given by Koiter (1943).4 In this work, Koiter considered the case of an infinitely long plate strip in compression. In this idealized case, the mode changes are gradual so that the shape of the buckling mode can be taken as a continuous function of the applied load. The solution for the infinite plate that he obtained can serve as an approximate solution for a plate whose length-to-width ratio is considerably larger than 1. A number of years later in 1959, M. Stein also discussed these phenomena, which he observed in the course of a panel buckling test program. Since then, several authors have contributed to the analysis of the mechanism of this phenomenon. We can mention Supple (1970), Nakamura and Uetani (1979), Schaeffer and Golubitsky (1979), Golubitsky and Schaeffer (1985), and Suchy et al. (1983, who explained the jump behavior by analyzing the static branching diagram in the neighborhood of the first and second bifurcation points by using perturbation theory5 (see also Damil and Potier-Ferry, 1986).

F I G . 14. Perfect plate, clustered bifurcations

'There is no explicit reference to mode jumping in this report, but it is obvious from the way the problem is treated that the solution given, i.e., the load end-shortening diagram, is the approximate solution for a plate that jumps from one mode to another during loading. 'Golubitsky and Sheaffer took Stein's test article as an example.

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Perturbation theory can explain why a structure under load will suddenly change its mode shape, but it does not offer the means to determine the load deformation diagram when several jumps occur in succession. As far as is known, Koiter’s solution6 of the plate strip remains the only example of an (approximate) analytical solution that provides this relation. In the general case, the discretization method in space and time, as it has been developed in the last 20 years, is at present the only technique available that is capable of computing this relation. The mode-jump problem of Stein (Figure 15) is a striking example of the capabilities of the tools of analysis discussed so far. A particular solution for an imperfect plate is presented by Riks et al. (1996). Here we will present another, similar solution of this problem. The plate strip (width 2b, length I ) is modeled by using symmetry with respect to a plane through the center perpendicular to the transverse direction y . The loaded edges at x = f1/21 are clamped but can move in the x direction. The longitudinal edge that is supported in this model is subject to simple support conditions. For the dimensions b, 1 and the thickness t that are chosen, we refer to the cited reference.

simple support

A \

FIG.15. Stein’s mode-jumping problem

6This solution is restricted to infinitely long plate strips in pure axial compression, with all kinds of longitudinal boundary conditions. The theory was later extended to shear loading as well (Koiter, 1946).

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The solution of this problem is dependent on the initial state of the panel. If no impe$ections are taken into account, loading will result in bifurcation at the load intensity h, = 1 (the load factor is normalized with respect to the first buckling load). The critical state at h, = 1 turns out to be stable (as is common for plates). At a slightly higher value of the load, another bifurcation point exists along the basic state XI, and when the load is further increased other bifurcation points are encountered. We will now first describe what happens if the plate is perfect. The actual physical states that the perfect plate will follow during loading are the stable states. This means that at at a load value h slightly higher than h,, the structure will buckle in a stable manner along a branch XII with an initial mode shape that resembles the buckling mode computed at h,. This phenomenon can be compared to the equilibrium point moving from the basic state XI to the branch XII.Further loading, however, soon passes through an unstable critical point along the branch XII,and at that instant a mode jump occurs. The jump ends in a new stable state with different mode shape. For the plate configuration studied here, the branch XII exhibits five ‘‘half‘’-waves in the axial direction. The new state XIII,which is reached after the first jump has occurred, is marked by seven half-waves. Further loading will result in a second jump to XIV with nine half-waves, and so on. Thus when the panel is perfect (i.e., no imperfections are involved), the jumps only occur in uneven wave numbers. This behavior, which we do not present here in the form of illustrations, can be explained on the basis of the symmetry properties of the numerical model of the panel (see the discussion by Riks et al., 1996). For an imperfect plate, i.e., a plate that has initial imperfections, the behavior changes somewhat in that it is now no longer necessary that the deformations remain symmetrical (in the sense discussed above) as in the perfect case. The particular results that we present here in Figures 16, 18, Plate 1, correspond to a solution for a panel with geometrical imperfections. In this case, an arbitrary ensemble of buckling modes (the first four modes) that belong to the successive bifurcation points along the basic state XI of the perfect case are added to the structure to change its geometry slightly. Thus, imperfections are introduced by adding a small initial displacement wo to the original configuration. They were taken in the form wo = 0.01[al a2 a3 a4], where ai are the first four buckling modes computed along the basic state of the perfect plate. The result for this imperfect panel, the load deflection behavior, is given in Figure 16. There are in this case four jumps that occur at h = 1.38,4.50, 8.30, 11.83. A phase-plane portrait of one of the jumps is given in Figure 17. The changes in the deformation pattern during the transient phase can be judged from the frames (h = 0.01) + (h = 1.38) + (h = 4.5) + (h = 8.3) + ( h = 11.83) in Plate 1. The

+ + +

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6

10

end-shortening F I G . 16. Load end-shortening plate.

first picture (1) shows the plate strip in its initial loading stage, which gradually goes over to the mode ( 2 ) . But the changes that then follow occur suddenly at the values of the load indicated above. The frames (2-5) show the states of the panel just before these jumps takes place. During the loading process the changes in wave form start with a change from 5 half-waves in the basic state Xf to 6 in the state XrI, from 6 to 8 from Xr, to the state X&, followed by the jump from XfII to Xfv, changing 8 into 10 half-waves and from Xfv to X$ with a change from 10 to 12. It is noted here that this particular outcome is different from that reported by Riks et al. (1996), because the combination of buckling modes that is used to represent the imperfections differs here with that of the ones taken in this reference. The initial geometry of the structure thus has a noted influence on the load at which the jumps take place and on the type of the jumps that occur.

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FIG.17. A jump in the phase plane.

However, this is not surprising, because with this type of problem, the branching diagram, i.e., the stable static as well as the transient trajectory the structure will follow, is strongly influenced by the initial imperfections of the structure.

C. THEESSLINCER CYLINDER BUCKLING EXPERIMENT In Riks et al. (1996) we presented an example concerning a buckling experiment on carbon composite cylindrical shells conducted at NASA (Rankin et al., 1994). The agreement between the visually observed changes of deformation during the actual test and those produced by the numerical simulation were very

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satisfactory in this case. In particular, the agreement between the actual and the computed shapes of the postcollapse state turned out to be very good. The NASA experiments were not monitored by a high-speed movie camera to register the transient part of the collapse process. This is not uncommon, because visual recording of the transient part of the buckling process is a very difficult undertaking and thus is seldom considered. However, there are a few examples of compression tests on cylindrical shells, where the transient part of the experiment was filmed. Such film experiments were carried out by Almroth (1963) and Esslinger (1970). On both occasions, the experiments were carried out in such a way that the tests on each specimen could be repeated over and over again. This made it possible to predict the moment at which the collapse motion would start, so that the operation of the high-speed camera (which is needed for this experiment) could be triggered at the appropriate time. It is not known whether the films Almroth made are still available, but Esslinger’s films are. In fact, they are available on video (Esslinger et al., 1977). The Esslinger experiments therefore offer a very suitable reference for numerical experiments of the kind considered here, and it is for this reason that we selected one case from the series recorded by Esslinger et al. (1977) and took this as a test case for the mode-jump procedure. The cylinder specimens were made of Mylar with dimensions radius R = 100 mm, thickness t = 0.254 mm, length L = 225 mm. The material was homogeneous and isotropic, with the following specifications: Young’s modulus E = 5500 N/m2, Poisson’s ratio u = 0.3, specific mass p = 1.3 x lop6kg/mm3. The shell edges were potted in some kind of epoxy material and were subject to a combination of axial compression, external pressure, and shear. In the numerical experiment that we present here, only one loading case is considered. This is the case of pure axial compression, which is the most common type of loading in tests conducted on cylindrical shells. To be able to reproduce the results, axial compression is induced by forcing one of the end plates to move inward (see Figure 18). The loading thus corresponds to displacement loading. In the testing machine, displacement control is never completely attainable, because the test fixtures absorb elastic energy, which is released when collapse sets in, thus disturbing the control mechanism that controls the position of the plate. It is an effect that can be simulated in the numerical model if we wish, but it is ignored here. The results we will show are thus obtained for the idealized case of a perfect end-shortening application. It is of interest to note that in the actual experiments the end shortening was enforced with a velocity of 1 m d m i n , which is in agreement with the notion of a quasi-static application of the load. For the finite-element model that emerged on the basis of these assumptions, a uniform mesh is used: 63 x 121 in axial and circumferential directions. For the

Buckling Analysis of Elastic Structures: A Computational Approach

4

69

Controled displacement

R = 100 mm R/t = 393.7 t = ,254 mm

L = 225 mm

FIG. 18. The Esslinger experiment.

boundary conditions at the loaded ends, clamping is assumed, so that the edges do not deform in the axial direction and cannot rotate around the director’s tangent to the edge. The analysis begins with the determination of the critical load h,, which corresponds to the critical state of the basic solution XI = [dr (AD;h ] .This solution is most conveniently computed with the standard path-following method available in the STAGS code, together with the bifurcation prediction method (4.26). After this initial computation, the base load is adjusted so that the load factor h becomes h, = 1 at the critical state.7 As is well known (see, for example, Koiter, 1945), the cylindrical shell, with an R l t ratio as large as this one, is governed by clustered bifurcations with many nearly simultaneous modes for which the tools of analysis discussed here are not entirely suitable. This means that we did not attempt to compute the branches of the bifurcation first point. It also explains why the code had difficulties in ob7This load corresponds to the well-known formula of the buckling load of a long cylindrical shell:

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taining accurate solutions for the eigen modes that belong to these bifurcations, although it produced estimates that are still useful in the construction of suitable initial imperfections in the second part of the analysis. In the actual Esslinger experiments, collapse of the specimens occurred at loads varying from A, = 0.8 to A, = 0.6, depending on the (unknown) imperfections of the shell and the precise nature of the boundary conditions that were applied. To provide a means of distinguishing between the two extreme cases, it was decided to conduct one simulation on the perfect geometry of the shell model and one on the imperfect model using the computed eigen modes a; mentioned above as geometrical initial imperfections. We will thus present two different cases that represent the extremes of the experimental outcome to some degree.

1. The Perject Case The static part of the analysis comprised 10 continuation steps along the basic equilibrium state of the shell in this case. At that point the load was hlo = 1.08, that is, 8% above the critical value h, = 1. This point, as a starting point for transient analysis, is rather far past the critical state, but in this way a rapid departure from the unstable state can be forced. The transient motion is triggered by an inevitable error in the solution [d[hloD; hlo],because the basic state is computed with the predictor corrector procedure, and thus fudlo; hlo) = E # 0. The computation of the transient motion can be speeded up somewhat if the buckling modes ai are used as initial perturbations (see Section IV.G), but we did not make use of this possibility here. The snap-buckling motion that started from this unstable state Plate 1 is pictured in Plate (2-6). The scale factor of the displacements displayed is 1, and the colors here indicate the magnitude of the displacement components u and w, i.e., the displacement component tangential to the circumference and the component in the direction of the normal to the shell middle surface, respectively. The time steps that the transient procedure takes varies between at the beginning of the motion and lop4 at the end.' The time that elapsed between the beginning of the motion and the state that was accepted as the postcollapse was At = 0.03 s. 2. The Imperject Case For the imperfect cylinder model, the first eight buckling modes were selected to serve as imperfections; the distribution of these modes was taken as

w = [ u , u , wIT = x a i a ; [ x . yD, 8The time integration procedure in STAGS has a step length control algorithm (Rankin el ul., 1988).

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with q (i = 1, . . . , 8) arbitrarily chosen as cq: [0.04,0.02,0.04,0.02,0.04, 0.02,0.04,0.02]. The analysis begins with the computation of the imperfect basic state XI: [dr[sD; Ar(sD]. It took 15 steps to reach the collapse point (limit point) for this case at A, = 0.534. This is the deformation state shown in Plate 3.1. The jump was initiated by taking the deformation state one step beyond this point at the load value of A = 0.54 as the initial condition for the transient procedure, in accordance with the recipe for such initialization discussed in Section 1V.G. Snapshots of the ensuing motion are given in Plate 3.2-6.

D. DISCUSSION AND CONCLUSION The successive solutions that are obtained during computations of this kind can be displayed in sequence, as in a slow motion picture. These motion pictures of the analyses, which, unfortunately, cannot be shown here, display a striking similarity with the sequence of events recorded in the Esslinger experiments. In particular, the postcollapse state that is reached after the motion has died out compares with the states recorded in the experiment. For the slightly imperfect specimens, Esslinger found a postcollapse state characterized by a skew-symmetrical wave in the axial direction and nine waves in circumferential direction (see Plate 20, whereas for the case of larger imperfections (and a much lower collapse load), this postcollapse state is symmetrical in the axial direction, with eight waves in the circumferential direction (Plate 3f). It is, of course, tempting to speculate on the reason for the difference, but we skip this question here. In the case of the larger imperfections in the actual experiment, the shell could be loaded further, upon which further changes in the state of deformation of the shell occur (Esslinger et al., 1977). Unloading in the postcollapse state leads to snap-back to the initial basic state XI. It is true that the computations are very laborious. In particular, the transient parts of the analyses that we presented here take much computer time and are bulky in storage. At the present time routine calculations are not yet feasible on large models, but this situation is continually changing for the better. The model of the cylinder here had about 40,000 degrees of freedom, but we were able to obtain the results on a present-day workstation. The computer time for a complete simulation as presented here is on the order of 24 h on such a machine. Mode jumping plays a role in the design of stiffened panels in aerospace engineering, and therefore the combination of static and transient procedures will prove useful, now that they have become available. For example, there is an im-

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portant problem for which these techniques will be welcomed as a tool of analysis. This is the problem of the residual strength of delaminated composite compression panels. Preliminary investigations have shown that the behavior of such panels is governed by mode-jump mechanisms caused by the delaminations, i.e., the delaminated areas can pop open or inversely implode during the loading sequence. In the computerized analysis of this phenomenon, the techniques described here will then become indispensible. We feel, therefore, that the techniques that we have presented in this chapter will find their practical applications in the near future.

References Almroth, B. 0. (1972). Collapse analysis for shells of general shape, Val. I. Tech. Rep. AFFDL TR-71-8. Almroth, B. O., Holmes, A. M. C., and Brush, D. 0. (1963). An experimental study of the buckling of cylinders under axial compression. Rep. 6-90-63-104, Lockheed Missiles and Space Company, Palo Alto, CA. Almroth, B. O., Stern, P., and Brogan, F. A. (1977). Future trends in nonlinear structural analysis. Comput. & Structures 10, 369-374. Arbocz, J. (1987). Post-buckling of structures, numerical techniques for more complicated structures. In: Buckling and post buckling: Four lectures in experimental, numerical and theoretical solid mechanics, Lecture Notes in Physics 288 (H. Araki, J. Ehlers, K. Hepp, R. Kippenhahn, H. A. Heidemuller, J. Wess, and J. Zittard, eds.). Springer-Verlag, Berlin. Arbocz, J., and Hal, J. M. A. M. (1990). Koiter’s stability theory in a computer-aided engineering environment. Internat. J. Solids Structures 26(9/10), 945-975. Argyris, J., and Mlejnek, H. P. (1991). In: Dynamics of structures: Texts on computational nieclzanics (J. Argyris, ed.), Vol. 5. North-Holland, Amsterdam. Azrar, L., Cochelin, B., Damil, N., and Potier-Ferry, M. (1993). An asymptotic-numerical method to compute the post-buckling behaviour of elastic plates and shells. Internat. J. Numei: Methods Engrg. 36, 1251-1277. Bathe, K. J., and Bolourchi, S. (1988). A geometric and material nonlinear plate and shell element. Comput. & Structures 1 1 , 2 3 4 3 . Belytschko, T., and Hughes, T. J. R., eds. (1983). Computational methods for transient analysis, Vol. I . Series of handbooks in Mechanics and Mathematical Methods. North-Holland, Amsterdam. Bidanid, N., and Johnson, K. H. (1979). Who was Raphson?, Short communication. Internat. J. Numer. Methods Engrg. 1, 148-152. Bout, A,, and van Keulen, F. (1990). A mixed geometrically nonlinear shell element, In: Theory and applications in applied mechanics (J. F. Dijkstra and F. T. M. Nieuwstadt, eds.). Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 269-276. Biichter, N., and Ramm, E. (1992). Shell theory versus degeneration-A comparison on large roattion finite element analysis. Int. J. Num. Methods Engrg. 34, 39-59. Budiansky, B. (1974). Theory of buckling and postbuckling of elastic structures. In: Advances in applied mechanics (C. S. Yih, ed.), Vol. 14. Academic Press, New York. Carnoy, E. (1980). Post-buckling analysis of elastic structures by the finite element method. Comput. Methods Appl. Mech. Engrg. 23, 143-174.

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Casciaro, R., Salemo, G., and Lanzo, A. D. (1992). Finite element asymptotic analysis of slender elastic structures: A simple approach. Internat. J. Numer: Methods. Engrg. 35, 1397-1426. Crisfield, M. A. (1991). Non-linear finite element analysis of solids and structures, Vol. 1. Wiley, Chichester, England. Damil, N. (1992). De la thkorie de la bifurcation au calcul des structures. Doctoral thesis, University of Hassan 11, Faculty of Science 11, Casablanca, Morocco. Damil, N., and Potier-Ferry, M. (1986). Wavelength selection in the postbuckling of a long rectangular plate. Internat. Solids Structures 22(5), 5 11-526. Dvorkin, E. N., and Bathe, K. J. (1984). A continuum mechanics based four-node shell element for general nonlinear analysis. Engrg. Compur. 1, 77-88. Esslinger, M. (1970). Hochgeschwindigkeitaufnamen von Beulvorgang Dunwandiger, Axial Belasteter Zylinder, der Stahlbau, 31,73-76. Esslinger, M., Hall, R., and Klein, H. (1977). Beulen und Nachbeulen dunwandiger Schalen-Axial Belastung isotroper Kreiszylinder. Filme E2191 des IWF, Gottingen. M. Esslinger, Publ. Wiss. Film., Sekt. Techn. Wiss./Naturw., Ser. 3, Nr. 4E2191. (English spoken version available.) Golubitsky, M., and Schaeffer, D. (1985). Singularities and groups in bifurcation theory, Vol. 1. Applied Mathematical Sciences. Springer-Verlag. New York, Heidelberg, Tokyo. Haftka R. T., Mallet, R. H., and Nachbar, W. (1971). Adaptation of Koiter’s method to finite element analysis of snap through buckling behavior. Int. J. Solids and Structures 7, 1427-1447. IbrahimbegoviC, A. (1994). Stress resultant geometrically nonlinear shell theory with drilling rotations. Part I. A consistent formulation. Comput. Methods Appl. Mech. Engrg. 118(34),265-284. IbrahimbegoviC, A,, and Frey, F. (1994). Stress resultant geometrically nonlinear shell theory with drilling rotations. Part I. Computational aspects. Comput. Methods Appl. Mech. Engrg. llS(3-4). 285-309. Knops, H. A. J., and Riks, E. (1994). Mode-injection for the analysis of through cracks in pressurized fuselages. In: Advances in nonlinearjinite element methods (B. H. V. Topping and M. Papadrakakis, eds.). CIVIL-COMP Press. Koiter, W. T. (1943). De meedragende breedte bij grote overschrijdingen van de knikspanning voor verschillende inklemmingen van de plaatranden. (The equivalent width at loads far above the buckling load for various boundary conditions along the plate edges.) NLL Rep. 287. National Aerospace Laboratory, Amsterdam, The Netherlands. Koiter, W. T. (1945). On the stability of elastic equilibrium. H. J. Paris Publishers, Amsterdam. English translation: Rep. AFFDL-TR-70-25. Air Force Flight Dynamics Laboratory, Wright-Patterson AFB, OH, 1970. Koiter, W. T. (1946). Het schuifplooiveld by grote ovcrschrijdingen van de knikspanning (The shear buckling mode at loads far above the critical value), Report X295. National Aerospace Laboratory, Amsterdam, The Netherlands. Koiter, W. T. (1963). Elastic stability and post-buckling behavior. In: Proceedings of the Symposium on Nonlinear Problems (R. E. Langer, ed.). University of Wisconsin Press, p. 257. Koiter, W. T. (1965). On the instability of elastic equilibrium in the absence of a minimum of the potential energy. Proc. Kon. Ned. Ak. v. Wetensch. (Proceedings of the Royal Netherlands Society of Arts and Sciences), Series B68. Koiter, W. T. (1967a). General equations of elastic stability for thin shells. Proceedings of the Symposium on the Theory of Shells, in Honour of Loyd Hamilton Donnell. University of Houston, Houston, TX. Koiter, W. T. (1967b). A sufficient condition for the stability of shallow shells. Proc. Kon. Ned. Ak.v. Wetensch. (Proceedings of the Royal Netherlands Society of Arts and Sciences), Series B, 70, No. 4. Kouhia, R. (1992). On the solution of nonlinear finite element equations. Comput. & Structures 44, 243-254.

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Lanzo, A. D., and Garcea, G. (1994). Koiter’s analysis of thin walled structures by the finite element approach. Int. J. Num. Methods Engrg. 39, 3007-303 1. Mackens, W. (1987). Numerical differentiation of implicitly defined space curves, Bericht no. 45. Institut fur Geometrie und Praktische Mathematik, RWTH Aachen, Germany, March. Marie, J. (199.5). Sudden change in second order nonlinear systems, slow passage through b$urcation. Ph.D. thesis, University of Wageningen. Mindlin, R. D. (1951). Influence of rotatory inertia and shear on flexural motions of isotropic, elastic plates. J. Appl. Mech. 18, 31-38. Nakamura, T., and Uetani, K. (1979). The secondary buckling and post-buckling behaviours of rectangular plates. Internat. J. Mech. Sci., 265-286. Nemeth, M. P., Britt, V., Collin, T. J., and Stames, J. H. (1996). Nonlinear analysis of the space shuttle super light weight external fuel tank. A I M Pap. 96-1552-CP, 37th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 15-17, Salt Lake City, UT. Collection of Technical Papers. Ortega, J. M., and Rheinboldt, W. C. (1970). Iterative solution of nonlinear equations in several variables. Academic Press, New York. Park, K. C. (1975). Evaluating time integration methods for nonlinear dynamic analysis. In: Finite element analysis for transient nonlinear behavior (T. Belytschko, J. R. Osias, and P. V. Marcal, eds.). Applied Mechanics Symposia Series. ASME, New York. Ramm, E., and Matzenmiller, A. (1988). Consistent linearization in elasto-plastic shell analysis. Eng. Comput. 5,289-298. Rankin, C. C. et al. (1988). The STAGS User’s Manual, NASA Contractor Report. Rankin, C. C., and Brogan, F. A. (1984). An element independent corotational procedure for the treatment of large rotations. In: Collapse analysis of structures (L. H Sobel and K. Thomas, eds.). ASME, New York. Rankin, C. C., and Nour Omid, B. (1988). The use of projectors to improve finite element performance. Comput. & Structures 10( 1-2), 257-267. Rankin, C. C., Brogan, F. A,, and Riks, E. (1993). Some computational toolsfor the analysis of through cracks in stifened fuselage shells. Computational Mechanics, Springer Inetmational, 13, Nr. 3, December 1993, pp. 143-156. Rankin, C. C., Riks, E., Stames, J. H., and Waters, W. A,, Jr. (1994). An experimental and numerical verification of the postbuckling behavior of a composite cylinder in compression. Euromed 3 17, LIVERPOOL, ENGLAND. (publication pending) Reissner, E. (1945). The effects of transverse shcar deformation on the bending of elastic plates. J. Appl. Mech. 12, 69-77. Rheinboldt, W. C. (1977). Numerical continuation methods for finite element applications. In: Formulations and computational algorithms injnite element analysis (K. J. Bathe, J. T. Oden, and W. Wunderlich, eds.). MIT Press, Cambridge, MA, pp. 599-631. Rheinboldt, W. C. (1981). Numerical analysis of continuation methods for nonlinear structural problems. Comput. & Strucrures 13, 103-1 13. Rheinboldt, W. C. (1982). The computation of critical boundaries on equilibrium manifolds. SIAM J. Numer. Anal. 19(3). Riks, E. (1970). On the numerical solution of snapping problems in the theory of elastic stability, SUDAAR No. 401. Stanford University, Stanford, CA. Riks, E. (1972). The application of Newton’s method to the problem of elastic stability. J. Appl. Mech. 39. Riks, E. (1973). The incremental solution of some basic problems in elastic stability. NLR Rep. TR 74005 U. National Aerospace Laboratory.

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Riks, E. (1978). A unified method for the computation of critical equilibrium states of nonlinear elastic systems. Acta Tech. Actid. Sci. Hung. 87(1-2), 121-141 (also as NLR MP 77041 U, National Aerospace Laboratory, The Netherlands, 1978. Riks, E. ( I 984a). Some computational aspects of the stability analysis of nonlinear structures, Comput. Methods Appl. Mech. Engrg. 47, 2 19-259. Riks, E. (1984b). Bifurcation and stability, a numerical approach. NLR MP 84078 U, National Aerospace Laboratory, The Netherlands, 1984. (Also In: Innovative methods f o r nonlinear problems (W. K. Liu, T. Belytschko, K. C. Park, eds.). Pineridge Press, Swansea). Riks, E., and Rankin, C. C. (1997). Computer simulation of the buckling behavior of thin shells under quasi static loads. Arch. Coniput. Methods Engrg. In press. Riks, E., Rankin, C. C., and Brogan, F. A. (1990). Aspects of the stability analysis of shells, International Conference of Computational Engineering Science, April 10-14, 1988, Atlanta, GA. In: Static and dynamic stabiliv of shells (W. B. KrXtzig and E. Ofiate, eds.). Springer Series in Computational Mechanics, Springer-Verlag, Heidelberg. Riks, E., Rankin, C. C., and Brogan, F. A. (1992). The numerical simulation of the collapse process of axially compressed cylindrical shells with measured imperfections. Report LR-705. Faculty of Aerospace Engineering, Delft University of Technology, Delft, The Netherlands. Riks, E., Rankin, C. C., and Brogan, F. A. (1996). On the solution of modejump phenomena in thin walled shell structures. Internat. J. Comput. Methods Appl. Mech. Engrg. 136. Sansour, C., and Bufler, H. (1992). An exact finite rotation shell theory, its mized variational formulation and its finite element implementation. Int. J. Num. Methods Engrg. 34, 73-1 15. Schaeffer, D., and Golubitsky, M. (1979). Boundary conditions and mode jumping in the buckling of a rectangular plate. Comm. Math. Phys. 69, 209-236. Seydel, R. ( 1 989). From equilibrium to chaos: Practical stabiliq analysis. Elsevier, New York, Amsterdam, London. Simo, J. C., and Fox, D. D. (1989a). On a stress resultant geometrically exact shell model. Part I. Formulation and optimal parametrization. Cornput. Methods Appl. Mech. Engrg. 72, 267-304. Simo, J . C., and Fox, D. D. (1989b). On a stress resultant geometrically exact shell model. Part 11. The linear theory; computational aspects. Comput. Methods Appl. Mech. Engrg. 73, 53-92. Simo, J. C., Fox, D. D., and Rifai, M. S. (1989a). On a stress resultant geometrically exact shell model. Part 111. Computational aspects of the nonlinear theory. Comput. Methods. Appl. Mech. Engrg. 79,21-70. Simo, J. C., Fox, D. D., and Rifai, M. S. (1989b). On a stress resultant geometrically exact shell model. Part VI. Variable thickness shells with through-the-thickness stretching. Comput. Meth0d.s. Appl. Mech. Engrg. 79. 21-70. Stein, M. (1959a). Loads and deformations of buckled rectangular plates. NASA Tech. Rep. R-40. National Aeronautics and Space Administration. Stein, M. (1959b). The phenomenon of change of buckling patterns in elastic structures. NASA Tech. Rep. R-39. National Aeronautics and Space Administration. Suchy. H., Troger, H., and Weiss, R. (1985). A numerical study of mode jumping of rectangular plates. Z. Angew Math. Mech. 65(2), 71-78. Supple, W. J. (1970). Changes of waveform of plates in the post-buckling range. Internat. J. Solids Structures 1243-1258. Thompson, J. M. T., and Hunt, G . W. (1973). A general theory ofelustic stability. Wiley, New York. Thurston, G. A,, Brogan, F. A,, and Stehlin, P. (1985). Postbuckling analysis using a general purpose code. AIAA Pap. 85-0719-CP. Presented at the AIAA/ASME/AHS 26th Structures, Structural Dynamics, and Materials Conference, Orlando, FL, April 15-17. Vandepitte, D., and Riks, E. (1992). Nonlinear analysis of Ariane 5 engine frame. Report LR 678. Faculty of Aerospace Engineering, Delft University of Technology, Delft, The Netherlands.

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van Keulen, F. (1993). A geometrical nonlinear curved shell element with constant stress resultants. Comput. Methods Appl. Mech. Engrg. 106, 3 15-352. Wriggers, P., Wagner, W., and Miehe, C. (1988). A quadratically convergent procedure for the calculation of stability points in finite analysis, Comput. Methods A&. Mech. Engrg. 70, 329-347. Young, R. D., and Rankin, C. C. (1996). Modeling and nonlinear analysis of large scale launch vehicle under combined thermal and mechanical loads. AIAA Pup. 96-1554-CP. 37th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 15-17, Salt Lake City, UT. Collection of Technical Papers.

ADVANCES IN APPLIED MECHANICS. VOLUME 34

Computational Mechanics for Metal Deformation Processes Using Polycrystal Plasticity PAUL R . DAWSON and ESTEBAN B . MARIN* Sibley School of Mechanical and Aerospace Engineering Cornell University Ithaca. New York

I . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

78

I1. Orientations and Orientation Distributions . . . . . . . . . . . . . . . . . . . . A . Crystal Orientations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B . Crystal Symmetries and Fundamental Regions . . . . . . . . . . . . . . . C . Crystal Orientation Distributions . . . . . . . . . . . . . . . . . . . . . . .

81 81 84 86

.

I11. Evolution of Texture and Strength . . . . . . . . . . . . . . . . . . . . . . . . . A . Single-Crystal Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . B . Orientation Distribution Conservation Equations . . . . . . . . . . . . . . . C. Evolving the Orientation Distribution by Using the Finite-Element Method D. Evolving Discrete Orientation Representations . . . . . . . . . . . . . . . . E . Texture Evolution during Homogeneous Deformations . . . . . . . . . . .

88 89 93 94 96 96

1V. Field Equations for Deformation . . . . . . . . . . . . . . . . . . . . . . . . . A . Macroscopic Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . B . Single-Crystal Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . C . Viscoplastic Approximation . . . . . . . . . . . . . . . . . . . . . . . . . . D . Microscopic and Macroscopic Scales . . . . . . . . . . . . . . . . . . . . . E . Texture Comparisons for Several Partitioning Rules . . . . . . . . . . . . .

99 100 102 105

106 112

V . Computing the Deformation by Using the Finite-Element Method . . . . . A . Elastoviscoplastic Formulation . . . . . . . . . . . . . . . . . . . . . . . . . B . Viscoplastic Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . 113

VI . Application to Forming Processes . . . . . . . . . . . . . . . . . . . . . . . . . A . Sheet Formability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B . Rolling of Polycrystalline Metals . . . . . . . . . . . . . . . . . . . . . . .

121 121 126

114 118

*Present address: Beam Technologies. Inc., Ithaca. NY

I1 ISBN 0-12-(X)2034-3

ADVANCES I N APPLIED MECHANICS. VOL. 34 Copyright 0 199R by Acadernrc Press. All rights of reproduction in any form reserved . 0065-2165198$25.00

Paul R. Dawson and Esteban B. Murin

78

VII. Studies of Microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Aggregate Size Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Hybrid Element Polycrystal Simulations . . . . . . . . . . . . . . . . .

133 134 . . 140

VIII. Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

152

IX. Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. GreekSymbols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

157 160 161

X. Appendix: Matrix Representations . . . . . . . . . . . . . . . . . . . . . . . . .

161

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

162

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

163

I. Introduction The mechanical properties of a polycrystalline metal depend on many attributes of its microstructure. A metal’s strength and formability are intimately connected to its crystalline structure, especially in terms of the slip systems that operate during plastic flow and the orientations of crystals that comprise the metal. Polycrystal plasticity theory embodies both of these features of the microstructure in a constitutive framework that can be incorporated in numerical formulations for analyzing deformation processes. In polycrystal plasticity, the actual movement of dislocations that results in the relative shift of crystallographic planes is idealized by the activity of a discrete number of slip systems. Each slip system contributes to one shearing mode of a crystal’s deformation. Various types of crystals exhibit different combinations of slip system geometry and resistance to slip, allowing for discrimination among metals and regimes in their behaviors. Polycrystal plasticity also provides a representation of the distribution of the crystal lattice orientations, referred to as the crystallographic texture. The slip systems and the crystallographic texture impart directionality to the microstructure. Mechanical properties at the macroscopic level, obtained from averaged microscopic responses, reflect this directionality in their anisotropy. A principal motivation for incorporating polycrystal plasticity in simulations of metal deformations is to benefit from the explicit link between anisotropic flow and its origins in the metal’s crystallographic structure. Asaro [ 3 ] reviewed experimental observations dating back to the turn of the century that document the nature of crystallographic slip in single crystals, as well as the theoretical developments that serve as the basis for modem polycrystal plasticity theory. The present paper summarizes developments in the effort to utilize this theory as the constitutive representation for

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large strain deformation of polycrystal solids, in essence addressing one of the outstanding challenges identified by Asaro. The use of polycrystal plasticity theory in deformation process simulation may be viewed as an example of applying state variable models for the constitutive description of the material. The texture, together with the strengths of the slip systems, acts as a characterization of the material state. The full constitutive theory also includes equations of the kinetics at fixed state, from which the relation between stress and deformation is obtained. Evolution of the state is accomplished with equations that prescribe the reorientation of crystal lattices and the changes in slip system strength induced by deformation. A link must be established between the macroscopic properties and the crystals that define the microstructure. It is the set of assumptions used in making this link that introduces many of the complexities of this approach, but provides much of the richness of behaviors as well. Applications of polycrystal plasticity with finite element formulations fall into two broad categories. One category includes those simulations that have a single orientation within each finite element. Elements represent crystals or portions of crystals. The second category includes simulations in which every element contains an approximation to the crystal orientation distribution. The orientations in each element may number as few as only tens of crystals, or may be in the thousands. The distinction between these categories principally consists of whether it is necessary to invoke an assumption for partitioning the deformation, given by the finite-element trial functions, among a population of orientations. For the first category, no such assumption is required because the elements are discretizing the volume within a single crystal. For the second category the elements each discretize volumes that contain large numbers of crystals. In this article we focus on the second category of formulations, with the intended application being macroscopic forming processes. However, we also discuss analyses that utilize a single orientation per element to illuminate how to better partition the macroscopic deformation among the crystals associated with that deformation. The earliest work combining finite elements and polycrystal plasticity fits within the first category. Gotoh [44] reported on the simulation of 125 facecentered cubic (FCC) crystals in a planar deformation as early as 1978. Needleman et d . [96] implemented rate-dependent single-crystal behavior in an elastoplastic formulation and studied the localization of thin strips under planar slip. Other examples include the studies reported by Harren and Asaro [46], Becker [ 161, Kaladindi et al. [64], Teodosiu et al. [127], Beaudoin et al. [14], Young et al. [ 1421, and Beaudoin et al. [ 151, all of whom have examined the issue of deformation heterogeneity over polycrystals with various implementations of crystal equa-

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tions in finite-elementformulations. Havelicek et al. [52],Yao and Wagoner [ 1361, and Miller and Dawson [90] investigated issues of slip system activity. An important consideration in these implementations is the integration of the elastoplastic constitutive equations over an increment of deformation. Several methods have been reported, including approaches suggested by Peirce et al. [ 1131, Cuitiiio and Ortiz [32], Maniatty et al. [81], Rashid and Nemat-Nasser [115], Kalidindi et al. [65], and Steinmann and Stein [124]. These differ in the configurations in which the equations are written and the algorithms for performing the integrations. Simulations in the second category, ones that incorporate a full orientation distribution within every element, are more limited. Mathur and co-workers [85-871 reported on the use of Taylor and relaxed constraints assumptions in Eulerian simulations of rolling and drawing of FCC metals. Van Bael et al. [133] also examined rolling, but of body-centered cubic (BCC) metals, using a series expansion of the Taylor factors to compute the anisotropic stiffness. Chaste1 et al. [28] used a lower bound model to predict mineral behavior in simulations of the Earth’s mantle; Kalidindi et al. [65] simulated forging processes with a Taylor assumption; Beaudoin et al. [ 13, 371 examined three-dimensional sheet-forming applications. This brief list is not comprehensive, but rather indicates that applications to date have focused on two main areas: processes involving large strain deformations and deformations of materials that inherit texture from a prior process. Both of these applications require the capability to address heterogeneous deformations, provided by the finite-element method, and the description of anisotropic behavior, given by polycrystal plasticity theory. In this article we present a methodology for utilizing polycrystal plasticity as the constitutive description in simulations of large-strain metal-forming processes. We begin with a treatment of the description of crystal orientations and orientation distributions. We take this as a starting point because of the central role that texture plays in the quantification of state. It is most often either the feature we wish to predict or a feature that strongly influences the outcome of a process. We include a discussion of alternative formulations for the computation of texture evolution that stem directly from the choice of the representation of texture. This is followed by a summary of the field equations for the motion of a polycrystalline metal body. We present first an elastoviscoplastic formulation based on a polycrystal plasticity theory, followed by the assumptions used in arriving at a viscoplastic approximation. At this point it is instructive to detail some of the macro-to-micro linking assumptions that are possible. We next summarize the finite-element formulations for both the elastoviscoplastic and viscoplastic formulations. Here we deal with the computation of material stiffness for each of the linking assumptions.

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In the second half of the article, several examples of these numerical formulations for forming applications are presented. Both sheet forming (stretching) and bulk forming (rolling) are discussed. The intent is to illustrate the preceding theory and numerical implementation with problems that bring to light some of the important issues that arise. We concentrate on simulations of metals of hexagonal close-packed (HCP) crystal structure because the high degree of single crystal anisotropy present in these metals forces us to confront those issues. Simulations of similar applications for FCC or BCC metals are cited. Finally, we present the results of two studies on the behavior of polycrystals and discuss the impact these have on the choices we must make in applying polycrystal plasticity as the constitutive description.

11. Orientations and Orientation Distributions A. CRYSTAL ORIENTATIONS Central to the mathematical quantification of crystallographic texture are the orientations of individual crystals. An unstressed crystal lattice always retains the same internal arrangement of crystal planes and directions regardless of the level of plastic strain. A crystal's orientation is simply that rotation needed to align a set of axes fixed to its lattice with a reference frame (or, inversely, to align the reference frame with the axes fixed to the lattice). The orientations of crystal lattices are discussed in terms of these rotations and the different parameterizations of such a rotation. The rotation tensor is a second-order quantity with nine components, but only three independent parameters. Most frequently in crystallographic computations, Euler angles are chosen to specify these parameters. By using Euler angles, the rotation is decomposed into a sequence of rotations, each about a prescribed axis'

There is not a unique set of axes el, e2, and e3 that permits this decomposition, and over the years many have been employed. The values of parameters @',$*, and @3 depend on the choice of rotation axes [21, 137, 139,721. While Euler angle parameterizations have been widely used, they possess a number of notable shortcomings. These are of two types: the difficulty in visualizing a crystal's orientation given the angles, and the poor quality of mathematical properties of the orientation space these parameters define [ 17,41,97,98,53,48]. ' A complete list of variables appears at the end of the article.

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For most purposes in the crystallographic analyses, any of the Euler angle parameterizations serve adequately. As discussed in later sections of the paper, the fact that the metric of the orientation space may be singular makes this representation of crystal orientations unsuitable for certain techniques used in the simulation of texture evolution. For this reason we utilize an alternative method for representing orientations based on the invariants of rotation. The natural invariants of a rotation are its axis, n, and the angle of rotation about that axis, 4. The rotation necessary to define an orientation then can be written as

R($m) = n @n

+ cos@(I

-

n @ n)

+ sin4(1 x n).

(2)

This representation has been examined for describing orientations of individual crystals, as well as for the misorientation between two crystals [53]. The angle/ axis parameterization of crystal orientations may be viewed as the projection of a four-dimensional quaternion parameterization onto a three-dimensional volume given by the angle/axis representation of the general form r = r(4, n), where r is a vector in orientation space. This connection has been discussed elsewhere [77,96,75]; here we proceed directly to properties of the angle/axis spaces. In general, orientation spaces exhibit measures of length, area, and volume that are distorted owing to the non-Euclidean character of the space. Of particular concern is the distortion of the space as reflected through variations in the metric tensor determinant, as it scales the differential volume in all integrations performed over regions of orientation space. However, there are additional consequences of a space possessing a non-Euclidean metric that bear on the evolution of texture [94, 38, 751. In particular, calculation of the gradients of the reorientation velocity appears in the orientation distribution evolution equations, and these gradients depend not only on the physical attributes of plasticity, but also on the properties of the space in which the velocity is computed. A number of useful neo-Eulerian parameterizations have been proposed [41] in which the axis vector is scaled by a function of the angle of rotation (Figure 1). These may generally be written as

The function f(4)that scales n influences the mathematical properties of the orientation space, and is specified with certain properties in mind. To avoid a singularity at the origin of the space, two restrictions are imposed: lim

@+O

f(4)= 0

and

lim

@+O

f’(4)> 0,

(4)

83

Mechanics of Metal Deformation Processes

X

Z

Z

Z

Z

Z

Z

Y

X

Y

FIG.1 . Anglehxis representation of orientations. Rotated cubes show orientations associated with corresponding r (qualitatively). Left column shows increasing rotation about [ n ]= [ 1 0 01. Right column shows rotation about [ n ]= [ I 2 21.

where f ' denotes the derivative of f (4) with respect to 4. Another criterion considered in the selection of f ( 4 )is the metric properties it endows the space. The metric, g, for the orientation space is associated with the measure of the distance between two rotations [94],

(ds')* = gij dr' d r j .

(5)

From this, the volumetric scaling can be written as

dv' = J d e t g d r ' d r 2 d r 3 . We employ a function f ( 4 )that defines a space having variable metric, but with the attractive feature that crystal symmetries will provide bounding surfaces that

Paul R. Dawson and Esteban B. Marin

84

are planes. This particular parameterization is the Rodrigues space [41] defined by

and having

and

where I". are the connexion coefficients, as needed for differentiation of quanti!k ties in orientation space.

B. CRYSTAL SYMMETRIES A N D FUNDAMENTAL REGIONS Crystals exhibit sets of orientations that are indistinguishable, and which define the symmetries that the crystals possess. With respect to the plastic deformation of crystals, equivalent orientations must exhibit both the identical geometric arrangement of atoms and identical strengths in the associated deformation modes (slip systems). This latter criterion places restrictions on the slip system strain hardening if orientational equivalency is to be preserved throughout a deformation. Granting that these restrictions are observed later when the mechanical response is considered, here we focus only on the geometric aspects of the symmetry. If we take H(@) to be a symmetry rotation, then an orientation equivalent to R can be written as

The existence of symmetrically equivalent orientations implies that there are subsets of orientation space that are adequate to define arbitrary crystal orientations. The smallest subset required to uniquely specify any possible orientation is referred to as a fundamental region. A fundamental region is determined by selecting one and only one orientation among the symmetrically equivalent orientations. For the angle/axis representation [53], a logical choice is to pick the orientation that lies closest to the origin of the parameter space (minimum I$). Considering

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values of 4 and n associated with the symmetry operations delivers a set of surfaces given by

-

f r n 5 tan(4/4)

(1 1)

that are bounding planes for the fundamental region. This applies to every (4, n) for which the crystal symmetry exists, giving bounding planes that number in correspondence with the number of symmetries. The fundamental region R* is defined by the inner envelope of all bounding planes. In some instances, this means that planes generated by certain symmetries are inert, as they lie entirely outside the volume defined by planes generated by other symmetries. Such is the case for FCC crystals, where the fundamental region is depicted in Figure 2. Here only planes originating from the symmetries about the families of (100) and (111) crystal axes appear as facets of the fundamental region [41, 39, 511. The (110) axis symmetries lie at too great a distance from the origin to contribute to the definition of the fundamental region. For HCP crystal geometries, fewer symmetries exist than for FCC crystals. There are symmetries about the (0001) crystal axis (c-axis) as well as about the (1000) family of axes [77]. This gives a prismatic volume with 12 lateral facets, as shown in Figure 3. The bounding planes that form the surface of the fundamental region may be grouped into pairs, with the planes of each pair being equivalent under a symmetry operation. One plane of each pair is assigned to the portion and the other plane to the portion aR:, with U 872; = aR*.

an;,

A

F I G .2. Fundamental region for FCC crystals using Rodrigues parameterization.

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Paul R. Dawson and Esteban B. Marin

X

FIG.3 , Fundamental region for HCP crystals using Rodrigues parameterization.

C. CRYSTAL ORIENTATION DISTRIBUTIONS A specimen of a polycrystalline metal that is large enough to be representative of the metal typically would contain thousands of crystals. The crystals in such a specimen would have a variety of orientations, reflecting the crystallographic texture of the metal sampled. An independent specimen taken from the same metal (same in the sense that it exhibits the same texture) would contain different crystals, each having its own lattice orientation. Although the two specimens would have different populations of crystals, they would be equivalent in a statistical sense if they were sufficiently large. In an ideal sense, the population of crystal orientations in any particular specimen might be thought of as having been selected from an orientation distribution. In simulations of textured materials, it is possible to work directly with the orientation distribution or to construct a sample of crystals from it that is faithful to its statistical features. We frequently refer to orientations as crystals, using the two terms interchangeably in much of the discussion of the mechanical properties derived from polycrystal plasticity theory. In this paper we discuss examples of both approaches, starting first with the orientation distribution.

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Formally, the orientation distribution is a probability density, A ( r ) , describing the distribution of crystal orientations. Because A ( r ) is known, the volume fraction of crystals in a portion of orientation space, 6R*, can be evaluated [59, 1381 as

Here the texture specified by A ( r ) applies to one instant (fixed state); over a deformation, A ( r ) evolves in time. For textured metals, A ( r ) is often quite complex, and various techniques are used to approximate it. Series expansions based on spherical harmonics [67, 138,117] have been used extensively in quantitative texture analysis for the construction of A ( r ) from experimental data. More recently, expansions formed with tensorial basis functions [IOO, 110, 144, 1191 have been proposed. Here we approximate A ( r )with piecewise interpolation used in finiteelement formulations [76,75], defined over R*,

A h ( r )= N f ( r ) A j ,

(13)

where Ah (r) is the discretized approximation to A ( r ) ,Nj"( r )represents the interpolation functions, and A j represents the nodal point parameters (summation over j implied). Local interpolation offers the same advantages in representing A ( r ) as in the representation of field variables throughout finite-element applications: employing finite-element trial functions for the approximation of A ( r )makes accurate characterization of A ( r ) possible, even when it exhibits sharp gradients. We point out only that in contrast to using a discrete sample (discussed next), representing the orientation distribution itself retains information concerning the density of crystals at all points in orientation space. Representing the texture with a discrete number of orientations has been widely used in texture analyses, especially in modeling texture evolution (see, e.g., [66,22,23]). In some respects, it is most similar to a physical specimen that has a finite number of crystals. There are a number of ways in which the use of discrete sets of orientations expedites the simulation of the deformation of polycrystalline solids. Averaging to obtain the mechanical properties may be performed by simple summations. Evolution of texture may be computed by independently rotating each orientation in the discrete sample. The many independent computations that result from having a collection of individual orientations can be exploited with parallel computing architectures to allow for the use of large numbers of orientations at many points in a body [ 12, 131. Using a set of orientations as a means of approximating the orientation distribution is equivalent to partitioning orientation space into subregions equal in number

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Paul R. Dawson and Esteban B. Marin

to the number of orientations. According to the magnitude of the probability density, we require that IJ f in eq. (12) be the reciprocal of the total number of crystals. This forces the volume of SR*to be small in regions where A(r) is high, and to be large in regions where A(r) is low. Thus many crystals are clustered together in an orientation space where the value of A(r) is high, as their respective volumes, SR*, are small. In regions characterized by low A(r), crystals are sparse because the corresponding volumes are large. Alternatively,it is possible to assign weights to orientations while keeping their corresponding volumes constant [73]. The weights themselves approximate the value of I J in ~ a region about the orientation of the crystal. This may reduce the number of crystals needed to accurately evaluate an orientational average, but can at the same time reduce the ability of the discrete orientation set to represent textures with many weak features (in contrast to a texture with a smaller number of strong components).

111. Evolution of Texture and Strength The inelastic response of a metal to an applied loading may involve one or more deformation mechanisms [43,5], such as crystallographic slip, diffusional creep, and twinning. The dominant mechanism at any instant depends on the regime of temperature and strain rate (or stress), as well as the microstructural condition of the material. Here we restrict our attention to conditions of moderate strain rates to lo3 s-'), cold to warm forming conditions (0.3 5 T / T m 5 0.8, where T is the absolute temperature and T, is the temperature at melt), and moderate grain sizes (lo@ 5 i 3 5 lop3 m, where L 3 is a characteristic grain dimension). In this regime, the inelastic strains are dominated by crystallographic slip [43, 711. Important for slip within a crystal are the orientations of its active slip systems relative to the applied stress, as well as the strength of these slip systems. The slip process itself alters the slip system strength through the accumulation of dislocations that act as an impediment to continued slip. The reorientation of the lattice of a deforming crystal, and with it the slip systems, is an integral part of the slip deformation mechanism. Lattice reorientation is a direct consequence of there being only a discrete number of deformation modes in a crystal having a limited number of slip systems. This immediately implies that the orientation distribution for a material is altered by the deformation, usually driving the material toward a highly textured and mechanically anisotropic condition. In this section we focus on the evolution of the crystallographic texture and the slip system strength. These are taken to be the relevant descriptors of the material state, which must be updated with deformation according to prescribed constitu-

Mechanics of Metal Deformation Processes

89

tive equations. We begin by summarizing those equations and follow with alternative approaches for integrating them in correspondence with particular texture representations (as discussed in Section 1I.II.C).

A. SINGLE-CRYSTAL EQUATIONS Even though the full mechanical response includes both elastic and inelastic contributions, the evolution of crystallographic texture is a consequence of the inelastic deformations. Treatment of the combined elastoplastic response is delayed until Section 1V.B. For now, we note that assuming the elastic strains are small implies that the current and unloaded configurations are nearly identical. Consequently, for the sake of simplicity in discussing texture evolution, we do not discriminate between these configurations in this section. Rather, we proceed by considering only the viscoplastic response, whether or not any elastic deformations ultimately are considered. The slip-system orientations are fully described by the normal to the slip plane, ma, and the direction of slip on the plane, b", where a indicates a specific slip system [54, 137,3]. The Schmid tensor is constructed from these as Ta = b" @ ma. For the inelastic portion of the deformation alone, the crystal velocity gradient, L", is written as

L" = LP + Q*,

(14)

where

The slip-system shearing rates are denoted by Pa,and Q* is the lattice spin that brings Lc and LP into coincidence. L" is assumed for now to be prescribed externally for all crystal orientations, but does not have to be identical for all orientations. Discussion of the various relationships between Lc and the macroscopic average of Lc is deferred until Section 1V.D. As given by eq. (14), the lattice spin is the difference between the crystal and plastic velocity gradients, and is required to determine the rate at which the crystal lattice reorients. However, i2* cannot be computed directly by using eqs. (14) and (15) unless the slip-system shear rates, Ya,are known. To determine the slip-system shear rates, first the deviatoric crystal stress, t'",is determined by using a combination of several relations. The geometry of the slip systems is used to define the resolved shear stress, t",

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Paul R. Dawson and Esteban B. Marin

A constitutive relationship relating slip [58, 102, 113,241

tffand

FLYis introduced from the hnetics of

where 1;" and m are material parameters and 2" is the strength of the slip system. Finally, the crystal deviatoric deformation rate, D", is a linear combination of the strain rates on the slip systems

where P" is the symmetric portion of T a .These equations, when combined, give a relationship between the (assumed) known crystal deformation rate and the crystal stress:

where SP is the crystal viscoplastic stiffness [ 5 8 , 8 5 ] :

and MP is the crystal viscoplastic compliance. Equation (19) is a nonlinear equation for the crystal stress in terms of a prescribed deformation rate and crystal state (orientation and strength), and is solved by using a Newton-Raphson procedure that includes a line search method [84,85]. Because the components of the crystal stress are known, the values for 1;" are determined from eqs. (16) and (17). The lattice spin is then available for computing the evolution of texture. The second aspect of the state that is essential for modeling plastic flow by slip is the strength of the slip systems. In eq. (17) the strength of each slip system was introduced as 2". Physical arguments regarding the mechanisms of strengthening (increases in 2") from the interactions of dislocations support the possibility that each slip system has a distinct 2* once plastic deformations have elevated the dislocation density [69, 31. From practical limitations of measuring distinct strength values in a polycrystal (for the purpose of initializing the state or verifying the model predictions), we restrict the slip-system strengths to being equal on all families of slip systems within a crystal. In fact, for crystals that have only one family of slip systems assuming a single 2 for all slip systems of all crystals within a complete aggregate makes little difference to the computed stress-strain

91

Mechanics of Metal Deformation Processes

response [90]. The evolution equation is assumed to be of a generalized Voce form [135,68]:

where

ts

= 4, Ys o (")"I

and O,, to,t s 0Ysc1, , and rn' are material parameters. Equation (21) is integrated by a simple Euler method, which is adequate, given that the strain increment remains sufficiently small. Throughout this article we concentrate on HCP titanium to illustrate the application of the methods presented to polycrystalline metals. The predominant slipsystems, shown in Figure 4, are the basal systems, prismatic systems, and one family of pyramidal systems [101, 56, 131, 1381. Slip-system normals and slip directions are indicated in the conventional indices for HCP systems. Typically, the pyramidal slip systems are stronger than either the basal or prismatic systems, and in this paper we consider cases of initial strength ratios with factors of 5 and 10 [ 1371. In some cases, the pyramidal strength is assumed to be sufficiently high to disable the systems entirely. The slip-system hardening parameters in eq. (21) have been estimated from experimental data [7], for the w x m compression of commercial purity titanium at three strain rates. The data and model curves are shown in Figure 5. Only the basal and prismatic slip systems were activated in determining the model parameters given in Tables 1 and 2. C

C

a2

Pyramidal m = (1071) b = <1123>

C

a2

Basal rn = {OOOl) b = <11.?0>

a2

Prismatic m = {ioio) b =

F I G . 4. Pyramidal, basal, and prismatic slip systems used in titanium simulations.

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Paul R. Dawson and Esteban B. Marin

CP Titanium Grade 3 Temperature = 675 "C A

} Experimentaldata

Effective strain (E) FIG.5 . Compression data and model computation for commercial purity titanium at 675OC. Model parameters determined using constrained hybrid assumption.

TABLE1 ELASTICITY PARAMETERS (HCP)

44.0 GPa

114.5 GPa

TABLE 2 VISCOPLASTICITY PARAMETERS (HCP)

0.06

1.0 s-'

370 MPa

31.3 MPa

75.8 MPa

0.005

5 x 10" s-'

Mechanics of Metal Deformation Processes

93

B. ORIENTATION DISTRIBUTION CONSERVATION EQUATIONS The rotation of individual crystals during deformation modifies the orientation distribution of crystals that comprise the material. The probability density, A (r), introduced in Section II.II.C, is written for some particular fixed-state condition, while recognizing that deformation alters the state. Now we allow A to depend on time, t , in addition to the orientation, r, and express the texturing of the metal in terms of the evolution of A . The integral of the probability density over a fundamental region must be unity to guarantee that all crystal orientations do reside within the fundamental region [3I, 761,

1,.

A(r, t ) dv' = 1.

This constraint must be true at all times, and in rate form [31, 116, 110, 33, 1341 becomes at

')

+ V(A(r, t)v(r, t ) ) = 0,

where v(r, t ) is the reorientation velocity of a crystal located at position r at time t . The relationship of the reorientation velocity to the crystal spin depends on the particular parameterization of orientation. For an angle/axis representation [75] as given by eq. (3), we have for v,

v = fn

+ f'in,

(26)

where $=n.w, n=2

(27)

1 sin $ nxwxn+-wxn 2 (1 - cos $)

and

w = vect(Q*).

(29)

A prescribed crystal velocity gradient enters the evolution of the orientation distribution through the dependence of the reorientation velocity v(r, t ) on the lattice spin Q*. The method employed to integrate the evolution equation for the orientation distribution depends on the choice made for its representation. Here we present two approaches stemming from the finite-element discretization of the probability density and the discrete set of orientations.

Paul R. Dawson and Esteban B. Marin

94

c. EVOLVINGTHE ORIENTATION DISTRIBUTION BY USING THE FINITE-ELEMENT METHOD

A direct approach to formulating the finite element discretization of the probability density conservation equation (eq. (25)) [29] is first to form a residual over the fundamental region as

-+v*VA+AV.V

+

where is a weighting function. Solving this system is made difficult by the presence of the convective term and by the tendency for extremely strong peaks to develop. The difficulty introduced by the convective term is common to many physical systems that are governed by hyperbolic conservation laws. In eq. (30), the divergence of the reorientation velocity (V v) may approach a jump discontinuity in the limit of vanishing rate sensitivity in the slip system kinetic expression (eq. (17)). Although the rate sensitivity is always nonzero, when it is small there are sharp gradients in the divergence of the reorientation velocity, and numerical oscillations in the computed values of A can easily arise. Artificial diffusion and shock-capturing techniques [57,61,62] have been developed that enable accurate solutions for systems with these characteristics, and have been employed for integrating eq. (30) [76]. Instead of attempting to integrate the evolution equation in its Eulerian form, it may be cast first in a Lagrangian form. This has the advantage of eliminating the problematic convective term, but introduces the complexity that the original fundamental region itself convects, and becomes highly distorted if the texturing is pronounced (which is usually the case). Compromises between the Eulerian and Lagrangian approaches exist; here we employ an updated Lagrangian system in which the current reference frame convects with the crystal trajectories. This may be formulated with an incremental approach [63, 47, 771 that permits the direct computation of the Eulerian probability density as

-

/

R* ( A ( A - A ) + A V . v ) + d v r

-/,*V.(tVA)11.dvr

=0,

(31)

where 2 is the value of A projected upstream along the characteristic over the step At , as given by

A = A(r - v a t , t - Ar).

(32)

The second integral of eq. (3 1) is an artificial diffusion modification in which the diffusivity E is based on the element size, h, and local residual, R A , E

=c,h"R~;

R A = /(A - A)/At

+ AV * v I .

(33)

Mechanics of Metal Deformation Processes

95

This updated Lagrangian formulation avoids the problem of a highly distorted reference region (and finite-element meshes) by employing the incremental convection scheme built into the computation of ( A - i ) / A t . We proceed to develop the finite-element discretization of eq. (3 1) by introducing piecewise interpolants for the trial functions and weight functions. As given in Section ILC, the approximation to A by finite-element discretization is

A h(r,t ) = N f ( r ) A j( t ) ,

(34)

and, employing a Bubnov-Galerkin approach,

W-,f)

= Nf(r)llrj(t).

(35)

In the computations presented in this paper, four node tetrahedral elements are prescribed. Requiring that the residual, J A , vanish gives a matrix equation for nodal values of A ,

[ K A ] { A l= { F A ) , where elemental contributions to [ K A ]and ( F A ) respectively, , are

and

where

gives the covariant derivative of the reorientation velocity field. The symmetry relations for the boundaries of the fundamental region must be preserved [41,94,75] as the texture evolves. This may be stated as

A @ , t ) = A ( R ( r ) ,t )

(40)

where R(r)specifies the symmetry operation for the crystal on aR:. This condition may be explicitly enforced by equating the nodal values of A to the values at the corresponding symmetrical points of the boundary, or by enforcing eq. (40) in a weak sense over the boundary [ A ( r ,t ) - A ( R ( r ) ,t)]~,b~da' = 0.

(41)

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Paul R. Dawson and Esteban B. Marin

The explicit approach given by eq. (40) necessitates constraints on the construction and numbering of the finite-element mesh. These constraints are not necessary with eq. (41), but are removed at the expense of introducing a constraint condition in the matrix equation for A via either a penalty or Lagrange multiplier approach.

D. EVOLVING DISCRETE ORIENTATION REPRESENTATIONS The task of updating a discrete set of crystal orientations is straightforward. The crystal reorientation velocities are simply integrated over time, as given by

In general, all orientations in the set experience lattice rotations during deformation. Throughout the reorientation process, however, each orientation continues to constitute the same volume fraction of the crystal population. It is common for orientations to exit the fundamental region, in which case they may be repositioned at the symmetrically equivalent location within the fundamental region. Actually, it is not necessary to relocate a crystal that is outside the fundamental region unless some operations are performed explicitly over the fundamental region (such as plotting of the texture). Quantities used in determining the averaged responses of all crystals in the set typically are not influenced by whether the crystal is within the fundamental region or at a symmetrically equivalent location outside the fundamental region. Instead of updating the parameterization of the crystal orientation, such as the n and $J values in the angle/axis representation, it is possible to update the rotation R (eq. (1) or (2)) directly, if the lattice spin is known [ 8 5 ] :

R=Q*.R.

(43)

This has the advantage of working directly with the rotation throughout a deformation history, which eliminates the need to compute the rotation from the orientation parameters except at the initial time. However, it increases the number of parameters that must be updated and introduces the need to use an integration scheme that ensures that the lattice axes remain orthogonal [123].

E. TEXTURE EVOLUTION D U R I N G HOMOGENEOUS DEFORMATIONS Two commonly studied deformation modes are compression under uniaxial stress (called uniaxial compression) and plane strain compression (the ideal defor-

Mechanics of Metal Deformation Processes

97

mation path of a flat rolling process). These two modes of deformation allow large strains, since stability limits are not encountered, and failure mechanisms, such as void growth and coalescence, are suppressed. Strains of approximately unity are often obtained experimentally under deformation conditions that are very close to homogeneous. Even larger deformations can be reached experimentally, as is well known for rolling, but confidence that the deformations always remain close to ideal is not high. Nevertheless, these deformation modes are an extremely important link between theory and experiment. Considering first plane strain compression, the velocity gradient is given by

LP = L o

(

1.0 0.0 0.0 sym 0.0 0.0 -1.0

)

s-1,

(44)

where, for the example shown, Lo is unity. Here we consider only the Taylor assumption (discussed in Section 1V.D) using an initial pyramidal slip system strength five times the basal and prismatic strengths. This gives a strength difference of 125.2 MPa, which is maintained throughout the deformation. The initial orientation distribution corresponds to uniform A (no preferred texture). The deformation continues until an effective strain of unity is reached ( i , f f = 4(2/3)Tr(D D) ). Texture develops monotonically throughout the deformation. When the Taylor assumption is used together with a single slip system hardness, the reorientation velocity field does not depend on the texture itself, but only on the deformation mode and the single crystal properties. Thus the reorientation velocity field does not vary in time for constant velocity gradient. The magnitude of the velocity, shown in Figure 6, has a number of equilibrium points where the velocity vanishes. However, not all of these are stable equilibria, which is required for a texture component to persist. The texture evolution is computed both by using the finite-element formulation for the probability density and by tracking the histories of a discrete set of 1000 orientations. The textures, presented in Figures 7 and 8, respectively, are qualitatively similar and exhibit strong peaks at the stable equilibrium points as expected. The most noticeable difference is in the greater smoothness of the finiteelement distribution, which stems in large measure from the quality of the initial distributions. Each is intended to represent an initially uniform distribution. The finite-element discretization does this exactly; the discrete aggregate does not. It should be noted that the orientations of the discrete aggregate are probably not optimal, so the conclusion is not that the discrete aggregate is incapable of representing a uniform distribution, but rather that it is not simple to choose the

98

Paul R. Dawson and Esteban B. Marin

0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00

-

__

-

FIG.6 . Magnitude of the reorientation velocity field for plane strain compression shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value indicated to the right of the plane. Taylor assumption; pyramidal slip system strength 5 times basal strength.

orientations that represent a uniform distribution well. New methods are currently being tested that sample randomly from a space defined by a homochoric scaling [391 of an angle/axis representation (rather than from Euler angle representation used to generate this sample) and offer greater potential for rendering high-quality samples [89]. Next we consider uniaxial compression. The crystal velocity gradient is imposed as

LC= L"

(

0.5 0.0 0.0 sym 0.5 !)loo)

s-l,

(45)

and again the texture evolution is computed for an L , of unity. The texture components develop at stable equilibrium point locations evident in the reorientation velocity field shown in Figure 9. The finite-element and discrete aggregate methods predict similar textures in terms of the locations and strengths of texture components Figures (10 and 11). These are contrasted later with the predictions made by using other modeling assumptions.

99

Mechanics of Metal Deformation Processes

A 16.0 14.2 12.4 10.7 8.9 7.1 5.3 3.6 1.8 0.0

FIG. 7. Finite-element orientation distribution A for plane strain compression at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value indicated to the right of the plane. Taylor assumption; pyramidal strength 5 times basal strength. Peak value = 15.5.

IV. Field Equations for Deformation The intended application for the simulation tools described in this article is to predict the motion (deformations) of a polycrystalline solid and the concurrent evolution of its microstructural state under loadings that induce large strains. The previous two sections of the article concentrate on the characterization and evolution of the state in terms of the orientations of constituent crystals and the strengths of slip systems in the crystals. For the evolution of state, the motion experienced by the crystals is assumed to be known. In this section we focus on the systems of equations needed to compute the motion. We make use of equations of equilibrium at the macroscopic level, rules for computing macroscopic averages over the orientation distribution of crystals, and relations for single crystal behaviors, especially assumed kinematics. The methodology for solving the set of equations for the motion with a finite-element discretization is presented in Section V. We proceed initially by allowing for combined elastic and viscoplastic responses; the simplifications arising from neglecting elasticity are presented following the

100

Paul R. Dawson and Esteban B. Marin

FI G .8. Discrete aggregate orientation distribution A for plane strain compression at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Taylor assumption; pyramidal strength 5 times basal strength. Peak value = 17.7.

more general case. Some applications make use of the purely viscoplastic approximation, whereas others utilize the full elastoviscoplastic development.

A. MACROSCOPIC RELATIONSHIPS We limit the analyses to quasi-static motions and to isothermal conditions, although the latter restriction is easily removed by solving for a changing temperature distribution concurrently with the motion. The field equations of interest for the isothermal, quasi-static case are those of equilibrium and the associated boundary conditions [45],

V.a=O -

in B ~ - a = t on aB, U=U on aB,. Here the body forces are neglected and the Cauchy stress is taken to be symmetric.

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Mechanics of Metal Deformation Processes

0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00

L 4 FIG.9. Magnitude of the reorientation velocity field for uniaxial compression shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Taylor assumption; pyramidal slip system strength 5 times basal strength.

In addition to the equilibrium requirement placed on the stress distribution at the macroscopic scale, we also require that the stress at any macroscopic position be consistent with the average of the associated crystal stresses, with the distribution of crystals coincident with that macroscopic position

Similarly, the macroscopic motion at any point in the body is the averaged response of the crystals in the orientation distribution. For the deformation gradient, this condition is written as

F = (F') =

IR

or in rate form for the velocity gradient as

*

F'Adv',

(48)

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Paul R. Dawson and Esteban B. Marin

A

FIG.10. Finite-element orientation distribution A for uniaxial compression at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3 . Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Taylor assumption; pyramidal strength 5 times basal strength. Peak value = 13.1.

The dependencies of c C , F Cand , Lc on the orientation are discussed in Section 1V.D as part of the task of defining rules that partition the macroscopic deformations to individual crystals.

B.

sINGLE-CRY STAL RELATIONSHIPS

The complete response of a single crystal to an imposed loading includes both elastic and inelastic strains. We assume that the elastic strains are associated with stretching of the crystal lattice and the inelastic strains are associated with crystallographic slip (see Figure 12). The deformation gradient is the combination of these responses, plus a rotation, and can be written in multiplicative form [80,4, 128,82, 181 as FC

= V* .R*.FP = v*.@p.

(50)

103

Mechanics of Metal Deformation Processes

A

FIG. 1 1 . Discrete aggregate orientation distribution A for uniaxial compression at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Taylor assumption; pyramidal strength 5 times basal strength. Peak value = 32.7.

R' FIG. 12. Configurations of a body undergoing plastic deformation by crystallographic slip, a rotation, and elastic stretching.

Paul R. Dawson and Esteban B. Marin

104

Fp is all of FC,except the elastic stretching, and defines the relaxed configuration B obtained by elastically unloading a differential volume within a crystal from the current configuration B to a stress-free condition without rotation. Using eq. (.SO), we can write the crystal velocity gradient as =V*.v*-l + v * . L p . v * - ' ,

[email protected]'

(51)

where LP

=FP

.F P - '

R .R*T + R* .F P .FP-'

=

.R*7

= R .R*T +cFb@ lY ma.

(52)

lY

The dyadic Pa @ ma defines the orientation of the crystal slip system at B. Equation (52) can also be written as

8P --( F P \;vp

= (Fp

-

.$-I)

.$-'),

S -

=*

C,,(bff

@ma)s

(53)

ff

.R*T +cl;lY((i;lY @ma)* (54) (Y

where the subscripts S and A denote the symmetric and antisymmetric parts of a second-order tensor. We assume that the elastic strains are always small in comparison to unity, which is reasonable for most metals, since the yield stress is several orders of magnitude smaller than the elastic shear modulus. Using the small strain assumption, we write V* as [lo, 391

v*= I + € * ,

l€*l << 1,

(55)

and hence,

i.*

v*-l = I - e*.

=(*,

(56)

After substituting eqs. (55) and (56) into eqs. (51), (53), and (54), using Lc = DC We, and neglecting higher order terms in €*, we can write the deformation rate as

+

Tr(DC)= Tr(i*) D/C = (* + DP + €*' \;vP - \;vP I

.

"

(57)

.e*'

(58)

and the spin as wc = \;vP

+ c*'

.D P - D P .

€*'

-

f(g*' .e*'

- €*'

.(*').

(59)

The multiplicative decomposition into the elastic and inelastic parts must be done

Mechanics of Metal Deformation Processes

105

in a manner that is consistent with the crystal stress. The Kirchhoff stress first is written in terms of the Cauchy stress, tC= det(I+

c*)d.

(60)

The Kirchhoff stress determines both the elastic strains from t" = S" : E*

(61)

and the plastic deformation rate (eq. (19)) T'C

= SP : D P .

The plastic deformations are assumed to be isochoric, so Tr(DP) = 0; any volumetric strains are elastic. The methodology for satisfying these conditions simultaneously is discussed in Section V. Furthermore, we limit the elastic response to isotropic behavior so that the elastic moduli can be specified using p, the shear modulus, and K,the bulk modulus.

C. VISCOPLASTIC APPROXIMATION In many instances it is acceptable to neglect the elastic response and treat the deformation as entirely viscoplastic. The inclusion of the elastic strains makes little difference in the computation of the texture evolution during rolling; computing the residual stresses in a rolled sheet is not possible without including the elastic response in the analysis. The detriment of neglecting the elastic response is that it is an ever-present part of a solid's response, and its existence, albeit small, may be critical to correctly predicting the phenomenon being modeled. On the other hand, the benefit of neglecting the elastic response is in the simplicity of the governing equations when the behavior is purely viscoplastic in comparison to the more complete elastoviscoplastic behavior. The viscoplastic approximation requires that

I<'*\ << IDPI

(62)

throughout a deformation. Assuming this always to be the case enables the following kinematic simplifications:

v* = I F" = FP = R* . F P D'C = D P = DP W" = Wp = WP Tr(DC) = 0

+R

. R*T = WP + a*

(63) (64) (65) (66) (67)

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Paul R. Dawson and Esteban B. Marin

F

b”

___)

FIG. 13. Configurations of a body undergoing plastic deformation by crystallographic slip and a Cotdtion.

and, because the current configuration and the unloaded configuration are identical (see Figure 13), the Kirchhoff and Cauchy stresses are indistinguishable: tC= a‘.

(68)

Note that quantities written with respect to the relaxed configuration B are now expressed with respect to the current configuration B . As is discussed in Section V.B, this assumption greatly simplifies the numerical treatment as well.

D. MICROSCOPIC AND MACROSCOPIC SCALES The orientational averages specified in eqs. (47), (48), and (49) place restrictions on the relations between stress and motion at the microscopic scale and the corresponding quantities at the macroscopic scale. However, they do not call out a unique prescription for determining the crystal-level quantities for a particular macroscopic average. Rather, additional constitutive assumptions are necessary to partition the macroscopic deformations among the crystals of a distribution, or aggregate. Such assumptions are motivated by the behaviors of the individual crystals and by the morphology and topology of the aggregates. The degree of the anisotropy of the single-crystal yield surface, the shape of grains, the relative strength of crystals in polyphase systems, and the extent of strain hardening all strongly influence the appropriate specification of partitioning assumptions. A great deal of the literature in polycrystal plasticity deals with the assessment of these assumptions [66,22,23]. As this topic is so central to polycrystal plasticity, we emphasize its importance through the presentation of several sets of assumptions. No one set of assumptions is “best”; each can be found to be deficient in

Mechanics of Metal Deformation Processes

107

many respects. Some have proved more useful than others, however, principally because they are more faithful to the physics of the plastic flow. The partitioning assumptions are integral parts of polycrystal plasticity constitutive models. The models we present do not constitute an exhaustive list. Rather, we focus only on the deviatoric plastic response and those models with which we have experience. Other models, most notably the self-consistent approaches [91, 79, 140, 251, offer viable alternatives that in some instances give better results. However, it is our objective here to discuss the implementation of the models in finite-element simulations of deformation processes and to demonstrate their usefulness in several applications. For these purposes, the models we present illustrate the methodologies associated with different partitioning assumptions and raise some of the important issues regarding their performance. We discuss partitioning assumptions from the perspective of computational algorithms for the deformation of the metal. That is, we assume that at some point in a simulation, an estimate of the motion (velocity field) is available, and it can be used with the constitutive equations to evaluate the mechanical properties of an aggregate of crystals. In this sense the algorithms are “deformation driven.” It does not matter if the boundary value problem involves applied tractions or velocities; the simulation proceeds with iterations on the motion until convergence is reached that satisfies all of the governing equations. Thus the macroscopic motion is assumed to be “known” and the average stress (and mechanical properties) is computed from the crystal stresses once the crystal deformations are determined.

1. Uniform Strain (Taylor)Assumption The Taylor assumption is the most widely used partitioning rule, as well as being perhaps the simplest. This hypothesis stems from Taylor’s experiments on aluminum [ 1261, which motivated the assumption that all crystals experience identical straining equal to the macroscopic strain. In the rate form this assumption is expressed as

D’‘ = D’.

(69)

The extended form of the Taylor assumption also imposes the same condition on the spin,

wc = w.

(70)

The stress varies from crystal to crystal, owing to the single crystal anisotropy. The macroscopic deviatoric stress as determined from eq. (47) is an upper bound of the exact stress [58].

108

Paul R. Dawson and Esteban B. Marin 2. Uniform Stress Assumption

A number of models are based on having one or more components of the stress identical in all crystals in lieu of imposing identical deformation rates [27, 1, 111, 1431. This may be attractive if by enforcing compatibility the stress becomes unbounded. In the limit that all components are equal,

u’ = U ’ C ,

(71)

and from the symmetric portion of eq. (49),

D’ = /R*D”A dv‘. The model seeks the macroscopic stress that, when imposed on each crystal, will result in a distribution of deformation rates whose orientational average equals the macroscopic deformation rate. In essence, there are five unknown components of the macroscopic deviatoric Cauchy stress, and five constraints stemming from eq. (72). So for a “known” D’, a single stress may be determined that produces a set of unequal crystal deformation rates. These conditions guarantee that the stress is a lower bound, but require nothing of compatibility beyond eq. (72). Requiring that the deviatoric stress be identical from crystal to crystal is not equivalent to requiring that the deviatoric stress directions align for all crystals, as is imposed with a Sachs assumption [118].

3 . Mixed Stress and Strain Assumption Partitioning rules have been proposed that have a mix of components with identical stress or deformation rate. The relaxed constraints assumption [55, 114,70, 861, for example, seeks to enforce the same combination of traction and strain continuity that exists across a flat interface: continuity of tractions across the interface and compatibility of strains in the interface plane. The orientation of the interface is chosen to coincide with the boundaries between flattened grains, and in the limit of infinitely flat grains, the assumption is exact. The relaxed constraints assumption may be stated by first specifying the plane of the interface by the unit normal vector 7R. Let 6’ and p2 be two unit vectors in that plane such that = 0 (the three vectors v g , 5 and form a rectangular Cartesian system). For the relaxed constraints condition, we obtain

e ’ e2 and

e2

Mechanics of Metal Deformation Processes

109

These equations are used together with eqs. (47)-(49) to determine the aggregate response. Typically, the relaxed constraints assumption is activated only when the grains are flattened [86, 1141.

4. Projection Operators A generalization of the Taylor assumption is to think of the partioning rule as being a mapping that takes the macroscopic deformation rate to the crystal deformation rate by a projection operation. For the Taylor assumption, the projection operator is merely the identity tensor for all crystal orientations. Other operators have been proposed with particular objectives in mind for the properties of the projection. The constrained hybrid [ 1031 and neighborhood constraint [ 1211 assumptions give two such approaches for modeling different types of polycrystalline materials. The constrained hybrid assumption [ 103,1121 was developed for aggregates of crystals composed of single crystals that themselves are physically incapable of certain deformation modes. In particular, when only the basal and prismatic slip systems are potentially active in HCP crystals, there is no means for an individual crystal to extend along its own c-axis (Figure 4). The Taylor assumption cannot be applied to such crystals because of their inability to accommodate arbitrarily oriented deformation rates. The constrained hybrid assumption defines a projection that eliminates c-axis extension in the deformation rate applied to each crystal, yet preserves the requirement that the average of the crystal deformation rates equals the macroscopic value. The projection operation takes the form

D'C = PC : D

(75)

C'" = c=@ c" - 1 3 I.

(78)

where

and

( Fdenotes ) an orientational average, and cc is a unit vector aligned with the crystal c-axis. The component of crystal stress corresponding to the inextensible deformation mode is left unspecified. This component is equated to the corresponding component of stress in the averaged response. The mapping given by eqs. (75)-(78)

110

Paul R. Dawson and Esteban B. Marin

is the "closest" [ 1031 projection to the crystal strain rate given by the Taylor assumption. The model permits the analysis of HCP polycrystal deformations, even though the yield surface for a single crystal is open along the stress axis corresponding to c-axis extension. The dependence of the crystal deformation rates on texture enters through the computation of D , using the orientational average of the projection operator P'. In the above example, the Taylor assumption is not physically plausible because the constituent crystals lack the minimum five independent slip systems required for an arbitrary deformation, and a model that does not demand this must be applied. However, there are instances when the individual crystals do possess adequate slip systems, and yet the Taylor assumption does not render sufficiently accurate results. In single-phase systems, a high degree of yield surface anisotropy at the single-crystal level can produce considerable strain heterogeneity within an aggregate. In polyphase systems, the different phases may exhibit distinctly different strengths, causing one phase to deform more than the others. Even for a polycrystal composed of a crystal type that is not strongly anisotropic, the desire to compute features of the texture with better fidelity can motivate the use of alternatives to the Taylor assumption. An example is the neighborhood compliance assumption [121], which proposes an algorithm to adjust each crystal's deformation rate from the Taylor assumption value toward a value that favors equilibrium with its local neighborhood. As with the constrained hybrid assumption, a projection operator is constructed to cast the macroscopic deformation rate onto individual crystals. We begin by averaging the crystal responses over a cluster of crystals (indicated by a ( ))>

a(D") = u ( M P: u " ) ,

(79)

and require uniform stress for the cluster, typically numbering between about 6 and 20 crystals. Setting the cluster deformation rate equal to the macroscopic value gives

u" = [ a ( M P ) ] - l : a(D") = [a(MP)]-' : D',

(80)

resulting in the partitioning rule,

D" = MP : [a(MP)]-' : D'.

(81)

The compliance of each crystal depends on its own deformation rate, making eq. (81) nonlinear in D". The compliance can be estimated for each crystal, however, by assuming that the slip system shearing rates are approximated reasonably well by using the macroscopic deformation rate in each crystal instead of the

Mechanics of Metal Deformation Processes

111

crystal's own value. The average of these compliances over a cluster is given by a(MP(D'))A . final normalization is performed to ensure that the average of the crystal deformation rates strictly satisfies the requirement that it match the macroscopic deformation rate. The partitioning rule then is given by

D'C = p

Pc= MP

D'

(82)

: ( a ( M P ) ) - ' : ((MP: ( a ( M P ) ) - ' ) ) - ' ,

(83)

c

where in this case MP is evaluated by using D' instead of D". The neighborhood compliance assumption was motivated by the variations of deformation rate computed in numerical simulations of FCC polycrystals [ 14, 1201 in which each element was a single crystal. These simulations show that variations in deformation rate arise in all components of the deformation, that the variations are normally distributed about the mean, and that the standard deviation is on the order of 0.20 of the second invariant of deformation rate. Although the magnitude of the deformation rate is dependent on the crystal orientation, there is a stronger dependence on the relative stiffness (or compliance) of the crystals in close proximity.

5 . Spin Assumptions Only for the extended Taylor assumption have we specified how the macroscopic and microscopic spins are related; all of the other sets of assumptions deal with the deformation rates alone. The relaxed constraints assumption, when motivated by the modeling of highly flattened grains, suggests a basis for relating the spins of the crystals: namely, that the principal axes of the grain axes should rotate in unison [74]. This is expressed in terms of the spin of Eulerian axes [99], QE" = Q E .

(84)

For the constrained hybrid and uniform stress assumptions, the crystal spins are equated to the macroscopic spin. If the grains do become quite flat, it is reasonable to equate the Eulerian spins, as was suggested for the relaxed constraints assumption. The neighborhood compliance assumption attempts to promote some variation in crystal spins, just as was done for the deformation rate [ 1211. The rule that was proposed assumes that the spin could be greater or less than the macroscopic value, with the magnitude of the variation about the mean being comparable to the magnitude of the deformation rate variations. The task of partitioning the spin is much less studied than partitioning of the deformation rate. However, the spin is as important as the deformation rate in determining texture, and the issue of its partitioning merits greater study.

112

Paul R. Dawson and Esteban B. Marin E. TEXTURE COMPARISONS FOR SEVERAL PARTITIONING RULES

As stated previously, the motivation for making various linking hypotheses is to distribute the macroscopic velocity gradient among the constituent crystals in a physically realistic manner (usually in comparison to that given by the Taylor assumption). The intent may be to improve the estimation of stress or compliance, or to obtain more accurate texture predictions. Here we illustrate the former: introduction of assumptions that eliminate the need to invoke pyramidal slip or twinning to accommodate the macroscopic deformation in every crystal. This is accomplished in the uniform stress (equilibrium-based) assumption by allowing each crystal to strain independently, and thus to activate only the most favorably oriented slip systems over the entire aggregate of crystals. It is part of the construction of the constrained hybrid partitioning rule to explicitly exclude the need for slip along the c-axis. We show the impact of these alternative assumptions on the texture evolution for plane strain compression and uniaxial compression [ I l l ] . An aggregate of 1000 orientations is chosen to approximate a uniform distribution, and the slip system parameters for the HCP titanium crystals (see Table 1) are the same as those used in the Taylor assumption computations (Section 1II.E). Straining again continues under monotonic loading to effective strains of unity. Examining first the case of plane strain compression, the orientations of the c-axes can be seen to be qualitatively different for the various models (Figures 15 and 14). For the constrained hybrid assumption, the c-axes tend to be strongly aligned with the compression (ND) axis, with a tendency for crystals to be rotated 30" about that axis. For the uniform stress assumption, the c-axes are tilted from the compression (ND) axis toward the rolling (RD) axis, and spread in the direction of the transverse (TD) direction. Neither the constrained hybrid nor the uniform stress assumptions give textures that have components identical to the Taylor assumption results. Rather, each displays some similarities and some differences. We note here only the sensitivity of the computed textures to the linking assumptions made and defer until Section VII the discussion of the resemblance of the computed textures to experimental data. For uniaxial compression, once again the constrained hybrid assumption predicts a strong alignment of the c-axes with the compression ( z ) axis (Figure 17). However, no preferred orientation about the c-axis is predicted for this loading. The uniform stress assumption (Figure 16) shows a clustering of c-axes near, but not coincident with, the compression axis. In addition, there is a weaker fiber of the texture associated with c-axes lying perpendicular to the compression axis. It is evident from these two examples that the linking assumption strongly influences

Mechanics of Metal Deformation Processes

113

A 100.0 90.0 80.0 70.0 60.0 50.0 40.0

30.0 20.0 10.0 0.0

lTD

,RD

FIG. 14. Discrete aggregate orientation distribution A for plane strain compression at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Constrained hybrid assumption. Peak value = 245.0.

the texture evolution, and these assumptions, although developed to accomplish the same objective, invoke substantially different textures.

V. Computing the Deformation by Using the Finite-Element Method The finite-element method is well suited for solving the systems of governing equations outlined in the prior section. The equations are nonlinear, have spatially varying coefficients, and apply over irregular domains. In this section we first present a formulation for the full elastoviscoplastic system of equations, followed immediately by the formulation associated with the simplified viscoplastic approximation. Simplifications realized in the theory by making a viscoplastic approximation carry through to the numerical implementation. For both implementations the role of crystal aggregates is in defining the mechanical behavior of the metal, including the characterization of its state via the crystallographic texture.

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Paul R. Dawson and Esteban B. Marin

A

FIG. 15. Discrete aggregate orientation distribution A for plane strain compression at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Uniform stress assumption: pyramidal strength 5 times basal strength. Peak value = 9.8.

A. ELASTOVISCOPLASTIC FORMULATION A weighted residual of the equilibrium equation (eq. (46)) is written over the volume of the body as [60]

s, -

4 (V - u ) d v = 0,

which in weak form is

Here the macroscopic Cauchy stress is split into deviatoric and volumetric parts prior to the introduction of constitutive relations. Considering first the volumetric behavior, a residual is formed on the statement that the elastic volumetric strain

Mechanics of Metal Deformation Processes

115

A 100.0 90.0 80.0 70.0 60.0 50.0 40.0

30.0 20.0 10.0

0.0

F I G . 16. Discrete aggregate orientation distribution A for uniaxial compression at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Constrained hybrid assumption. Peak value = 220.0.

rate constitutes the full volumetric straining [83],

s, s,

(Tr(D')-

Tr(r*) - Tr(Z*) ) ) @ d s = 0, At

(

(87)

where a backward Euler approximation for 2* is employed. Upon introduction of the bulk modulus, Ic, eq. (87) becomes (p

+ Ic At Tr(DC)+

+

where B = det(1 t*). Interpolation functions are used to describe the pressure and velocity distributions over an element

u = ""HU);

p = [NPI{P),

(89)

so that eq. (88) becomes a relation between parameters for the unknown pressure and velocity distributions. This is written as a residual of the form

+

{RE) = [ G e l T { U ) [M'I{PJ

+ {g"),

(90)

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Paul R. Dawson and Esteban B. Marin

A 27.0 24.0 21.o 18.0 15.0 12.0 9.0

6.0 3.0 0.0

FIG. 17. Discrete aggregate orientation distribution A for uniaxial compression at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Uniform stress assumption; pyramidal strength 5 times basal strength. Peak value = 10.5.

where

and

The crystal equations for the deviatoric behavior are introduced directly into the residual (eq. (86)) to eliminate the macroscopic deviatoric Cauchy stress. From the single-crystal equations, eq. (58) in matrix form is 1 {D") = GI.*'}

1 + {iP} + [ + P ] { ~ * (} - -{?*'}. At

(94)

Mechanics of Metal Deformation Processes

117

The matrix entries for the tensorial quantities are explained in the Appendix. Recalling from eqs. (19) and (20) that the inelastic response is

{ &'}

= [MP]{ r"},

(95)

and from eq. (61), that the elastic behavior is

the stress can be written as {o"'}= [ S ' ] ( { D ' )- {h')),

where

[S'I-' = [M'] =

2~ At

[TI + p[MP]

and

{h') = [@PI{.*

i

} - - {1C * At

,

}.

(99)

The macroscopic average quantities are determined from those of the single crystal and the orientation distribution. Here the assumptions that are used to partition the straining among the crystals in an aggregate enter directly. For the remainder of the elastoplastic formulation, we employ the Taylor assumption to link the macroscopic and microscopic responses. Applying this assumption,

where

and

Equation (100) provides the relationship needed to eliminate the deviatoric stress from the weak form of the equilibrium statement. This gives a residual of the form

118

Paul R. Duwson and Esteban B. Marin

where

{ f " }=

1

s

[NL"]TIXIT{H)d~+ [N"lT(I)da,

B'

iIB?

where [XI is a matrix for converting the six-component vector form of the deformation rate to the five-component form used in the constitutive representation (see the Appendix for details). Greater detail of the finite-element implementation is available in [83]. It is important to note that the influence of the crystal aggregates is embodied in [ S ] ,and that the flow law represented by eq. (100) is anisotropic, in general, owing to the anisotropy at the single-crystal level entering through [ M " ]and , the orientation average performed in computing [ S ] The . evaluations of [S]and ( H ) are computationally intensive operations that involve integrating the single-crystal constitutive equations over trial increments of the deformation for each time step until convergence is reached, and the motion and stresses are determined. The presence of the elasticity restricts the size of the time step for accuracy and ease of convergence, even though the implicit algorithm ensures stability [82].The residuals given in eqs. (90) and (103) are for a single element. After assembly and application of the essential boundary conditions, the resulting matrix equations are solved simultaneously for the velocity field and pressure distributions. The solution proceeds incrementally through a full deformation history. The concurrency possible in calculating the elemental matrices, including the quantities obtained from aggregate averages, can be exploited with parallel computing strategies to provide highly efficient implementations.

B. VISCOPLASTIC FORMULATION In making a viscoplastic approximation, the principal computational benefit is that only one configuration is needed to quantify the response, namely, the current configuration. Elastic behavior implies the existence of a second configuration, whose relation to the current defines the elastic deformations. This configuration may never be calculated explicitly, but its existence is essential to any elastoplastic theory. If elasticity is neglected, the unloaded configuration of a body is coincident with the current configuration, which greatly simplifies the development in comparison to the elastoplastic theory. Consequently, an algorithm to decompose an increment of deformation into elastic and plastic parts (or, equivalently, to identify the elastic and plastic parts of the velocity gradient) is unnecessary. According to

Mechanics of Metal Deformation Processes

1I9

the equations of the viscoplastic approximation outlined in Section IV.C, the volumetric response is simply Tr(D) = 0,

( 106)

and, for the deviatoric response,

Assuming plastic deformation by slip without elasticity simplifies the expression for the stress, eq. (97), to

( F }= {dC) = [sp](D'c).

(109)

Upon averaging over the polycrystal, a macroscopic viscoplastic material response is obtained [85, 121 in the form {U'I

(1 10)

= ISl{D'),

where the precise definition of [S]depends on the partitioning rule, as discussed later. The residuals from the weak form of conservation of mass appear as

{R:J = [G'lT{U),

(111)

and for equilibrium as {RtJ = [Kel{U) - [Gelif')

- If'},

(112)

where [Gel and [K'] have the same form as the full elastoplastic formulation, but { f'} simplifies to

The volumetric residual may be appended to the equilibrium residual via a Lagrange multiplier to restrict the possible motions to those that are incompressible. Often this constraint is enforced instead in an approximate manner by using a consistent penalty approach [40, 121, wherein the volumetric residual is

+

{RE}= [G"lT{U) [ M e l { p J , with

[ M e ]= h

(114)

he

[NpIT[Np]dv,

where h is a penalty parameter that is made large with respect to the effective vis-

120

Paul R. Dawson and Esteban B. Marin

cosity [13]. An appropriate choice of the pressure interpolation allows the nodal pressures to be determined in terms of the velocity as

{ P }= -[M"]-'[G"]T{U)

(116)

and used to eliminate the pressure from the residual for equilibrium, {R.fJ = ([Kel

+ [Gel[Mel-'[GelT)(U)- {f").

(117)

This system is used to determine the velocity field subject for a specific set of natural and essential boundary conditions [ 131. Once again, the anisotropy arising from the crystallographic texture enters through [S].The viscoplastic approximation eases the difficulty in averaging the single-crystal responses for various partitioning rules. The partitioning rules in Section 1V.D lead to the macroscopic material stiffness matrices summarized in Table 3. Any of the partitioning rules may be implemented to define the material stiffness, [S].All of them involve orientational averages, and thus are influenced by the texture. As previously mentioned, they may be viewed in a "deformationdriven" framework wherein a trial deformation rate is imposed and the stress is determined. From the computed known stress, the crystal compliances are evaluated, followed by computation of the macroscopic stiffness as specified above for the designated partitioning rule. This is a time-consuming part of a simulation, as the system of equations that relate the crystal stresses to the applied deformation rate is often highly nonlinear. The stiffness enters the residual for equilibrium, completing the system of equations to determine the velocity field, and thus providing a new trial deformation rate. This iteration scheme continues until the full set of field equations is satisfied. TABLE3 MACROSCOPIC S T I F F N E S S FOR

S E V E R A L PARTITIONING A S S U M P T I O N S

Model

is1

References

TdydylOr

IS1 = (LMpI-')= (ISPI) IS1 = [([MPI)I-' IS1 = (iPcl)-l [([MpI-I[~"l)l(LP"l)-'

[58,851 [281 [841 [I211

Uniform stress Constrained hybrid Neighborhood constraint Relaxed constraints

[S] = (IMP]-' "73'1) 1. Compute [ M p ]for each crystal 2. Rearrange [MP]to 12'1 3. Compute ([F]) 4. Rearrange ( [ Z " ]to ) obtain [S]

t861

Mechanics of Metal Deformation Processes

121

VI. Application to Forming Processes A. SHEETFORMABILITY Sheet metals exhibit textures that form during the rolling processes used in their production. Cold working during the final passes of a rolling schedule has the benefit of increasing the flow strength of the material, but may decrease the ductility at the same time. Anisotropy arising from the crystallographic texture also develops during rolling [ 11, 1451 and may affect the ductility for the better or worse [95,20, 1411. It is possible to enhance the stability of a planar deformation mode (such as stretching) with a texture that resists through thickness straining, as has been demonstrated for titanium [51,50,26]. The strength of the directionality in the straining behavior of a sample of sheet metal is quantified with the R-value parameter. The R-value is the ratio of width to thickness strains under tensile loading. Isotropic behavior demonstrates an R-value of unity, whereas for anisotropic responses the R-values deviate significantly from unity, possibly being either greater than or less than unity. Titanium sheets having a texture with "in-sheet'' orientations of the c-axes tend to exhibit low R-values, whereas sheets with "through-thickness'' orientations of the c-axes exhibit high R-values. A high R-value sheet demonstrates much greater elongation prior to failure than does a low R-value sheet [26]. Finite-element simulations have been used to quantify the influence of texture on the through thickness strains in the limiting dome height test [37] and on earing in hydroforming [35]. Here we apply the elastoviscoplastic formulation to the analysis of a tension test to examine the evolution of the R-value with strain. Specimens of rolled titanium are discretized with finite elements, each element having a single orientation and exhibiting the full elastoviscoplastic response summarized in Section 1V.B. The texture of the rolled sheet is taken from the results of the hybrid element polycrystal simulations discussed in Section V1.B. In particular, the texture corresponding to pyramidal slip with strength five times the prismatic strength is assigned to the elements in the specimen. This texture is similar to titanium textures from material rolled in an elevated temperature regime in which twinning is not an important deformation mechanism. The reduction is not great in comparison to typical rolling reductions, however, corresponding to a through-thickness compressive natural strain of only unity. In replicating a set of R-value tests, the specimens are oriented at different angles to the rolling direction (Figure 18). Orientations of 0", 22.5", 45", 67.5", and 90" are considered. The specimen aligned with its tensile axis in the rolling direction corresponds to 0", and the one with the tensile axis in the transverse direction is at 90".

122

Paul R. Dawson and Esteban B. Marin

(a)

Z

'Y

FIG. 18. a) Schematic diagram of an R-value test specimen relative to the sheet; b) finite-element mesh of a portion of the gage section of the specimen.

The specimen is constructed of a prism of 3024 elements, as shown in Figure 18. An inner core of 960 elements is used to evaluate the R-value, leaving an outer layer of elements two thick as a medium to isolate the inner core from the external surfaces. The specimens are stretched in the uniaxial tension, using 40 time steps of 5 s each to reach a total strain of 0.02. The corresponding strain rate was lop4 s-l. The use of a very small time step allows the loading process to be examined in detail. Material parameters for the titanium are listed in Table 1.

Mechanics of Metal Deformation Processes

123

Figure 19 shows the R-value evolution with extension for three of the specimens. Initially, the R-value is unity, because of the assumption of isotropic elastic behavior. In reality, a textured polycrystal would not exhibit an isotropic elastic response, but it is useful here to retain this assumption for the elastic response, to contrast it with the anisotropic plastic response. With a clear contrast it is easier to observe the transition from elastic to elastoplastic behavior. As can be seen in Figure 19, it takes between 1% and 2% strain for the R-values to approach constant values, with greater strain required for orientations with larger R-values. Although the elastic moduli is such that the yield surface would be reached in a single crystal at a strain of only a few tenths of a percent, some crystals do not reach that condition until the specimen strain is an order of magnitude larger. This implies that care must be exercised in making comparisons between measured and computed values in terms of the strain levels at which each is recorded. Computations based on purely viscoplastic behavior are not truly valid until all crystals are deforming plastically. Measurements of the R-value obtained at the first deviations from linearity of the stresshtrain record correspond to some, but not all, of the crystals experiencing plastic deformation. Experimentally measured R-values in this regime reflect elastic anisotropy as much as anisotropy due to the plastic response. R-values corresponding to strains much larger than several percent could be influenced by appreciable changes in texture. The distributions of R-values for specimens for all of the orientations and at various points in the loading are shown in Figure 20. The texture produced by

.

...........................

s

W

f W II

a

i _i

1.5 7

1.0

'*:.- ..*..*....................................

-.

0.5 0.0 0.000

0.005

0.010

0.015

0.020

Macroscopic strain E,

FIG.19. Evolution of R-value with strain for three specimen orientations.

Paul R. Dawson and Esteban B. Marin

124

0.5 l'Ol

o.ot, 0

' '

'

I

15

"

"

'

30

"

'

'

I

45

"

' '

I

60

' ' '

'

'

75

"

'

' j

90

Angle (degrees) FIG.20. Distribution of R-values at several strain levels. The angle 8 is measured from the rolling direction (8 = Oo, rolling; 8 = 90°, transverse).

the plane strain compression deformation results in R-values in excess of unity in all orientations throughout the loading. At 45", the R-value is greatest, having a value above 3 at 2% strain, even though the texture is not strong. Textures with c-axes oriented normal to the sheet tend to resist through-thickness straining, as shown by Chan and Koss [26] and by Hatch [51]. This is particularly true for strong basal textures, ones with the c-axes normal to the sheet or nearly so, where R-values as high as 12 have been reported [26] for tensile specimens over strains in excess of 0.1. For textures with the c-axes tilted toward either the rolling (as is the case here) or transverse directions, R-values typically are not as great as those for basal-textured material. The R-values in these cases typically are between 2 and 4 (again for axial strains exceeding 0.1) for sheets with the c-axes tilted toward the rolling direction. This corresponds well to the values reported here. As mentioned in the previous paragraph, however, one must be cautious not to overstate the agreement, because of the difficulty of ensuring that the strain levels are comparable. What is important is that from measured textures, the trends in the influence of texture on the formability of the sheet can be examined directly with the elastoviscoplastic finite-element formulation. The orientation of a c-axis component of texture continues to influence the deformation of sheet beyond the relatively small strains considered so far (up to about 2%). A material with favorably oriented c-axes can maintain stable deformations to much larger strains than a material with an unfavorably oriented c-axis

Mechanics of Metal Deformation Processes

125

texture component. This was demonstrated by Chan and Koss [26] for materials with through-thickness and in-plane c-axis texture components. Similar tests are repeated numerically here by pulling strips of titanium to 20% strain. One strip (case 1) has a texture with a c-axis component oriented perpendicular to the strip thickness (x-direction); a second strip (case 2) has the c-axis component lying in the plane of the sheet and perpendicular to the loading direction (the c-axis component is directed in the y-direction). The time step is 5.0 s, so that over 400 increments an axial natural strain of 0.20 is achieved. The upper surfaces of the meshes are constrained to move only in the z-direction, at a velocity that gives a constant deformation rate of 1 x s-', so that the shape of the upper surface remains unchanged throughout the deformation. Deformed meshes are shown in Figure 21 from two perspectives. The nonunifonnity of the deformation at the scale of individual crystals (elements) is evident in Figure 21a. The

X

V

FIG.21, Strip deformed to E = 0.20 for two orientations of the texture: Case 1, c-axes normal to sheet; case 2, c-axes in the sheet and perpendicular to loading direction. a) mesh orientation similar to Figure 18b; b) mesh orientation rotated to show cross section.

126

Paul R. Dawson and Esteban B. Marin

centerplanes of both specimens are visible in Figure 21b, showing a distinct difference in the aspect ratios of the cross sections. For case 1, where the c-axes lie in the x-direction, the elongation of the strip is accommodated by contraction in the y-direction, with little straining in the x-direction. For case 2, with the c-axis component oriented along the y-direction, the texture promotes greater throughthickness (x-direction) straining. For sheet material, the resistance to throughthickness straining translates into greater formability. B. ROLLINGOF POLYCRYSTALLINE METALS Production processes for metals often include reduction in gage by rolling. Rolling is an effective technique for accomplishing large thickness reductions, typically imparted by using many passes and through a wide range in temperature. Large thickness reduction translates into large strains, and changes in the microstructure accompany the strain. The alterations in the crystallographic texture are particularly important, as they influence the formability of the rolled metal, as discussed in the preceding section. Flat rolling processes are idealized as plane strain compression (as discussed in Section IILE), but this is valid only if rolling reduces metal through a homogeneous deformation from the starting thickness to the final one. Typically, significant variations in the deformation exist through the zone where reduction occurs (bite), the severity of which can be characterized by the A-factor introduced by Backofen [8]. Consequently, the deformation histories differ between metal at the surface and that at the centerplane (or at points intermediate to these). Different deformation histories imply different textures, and thus also imply a gradient in mechanical properties through the rolled metal thickness. Whether or not the property gradients are significant depends both on the severity of the inhomogeneity and on the character of the metal being rolled. Finite-element modeling provides the means to determine the complex velocity distribution during rolling, and to extract histories of deformation at various positions throughout the thickness of the metal. From these histories, the texture evolution can then be computed throughout the workpiece and used to calculate texture-dependent properties such as the material stiffness defined in Section V. The rolling of aluminum was one of the earliest applications of polycrystal plasticity as the constitutive representation in a finite-element formulation. Texture gradients were computed by using a viscoplastic approximation and compared to data published in the literature [85].Introducing the relaxed constraints assumption has provided better correlations to observed trends for a number of important features of the textures [86]. Texture evolution during the rolling of silicon steel over many passes also has been studied in detail. Initial textures were

127

Mechanics of Metal Deformation Processes

determined from measurements taken from hot-rolled band. Comparisons were made between computed and measured textures at various stages in the multipass process [36]. In both the aluminum and steel applications, through-thickness gradients in texture were appreciable. The strength of gradients in texture has been quantified by using the finite-element representation of texture over orientation space [75] discussed in Sections I1 and 111. The shearing components of the deformation rate tensor near the surface cause significant differences in the surface texture, in contrast to the centerplane, where the deformation is close to ideal. Here we examine the rolling of HCP titanium (see Figure 22a), using the constrained hybrid assumption and the viscoplastic approximation. An Eulerian formulation allows the deformation zone to be discretized with spatially fixed elements that the metal flows through. The characterization of the titanium singlecrystal response described in Section 1I.A is used in these simulations as well with the model parameters given in Tables 1 and 2. The intent of the simulations is to examine the through-thickness texture gradients as a function of the rolling schedule. For the same overall reduction, several sets of passes with partial reductions are examined. The nature of the titanium’s single-crystal behavior provides some interesting contrasts to the results for aluminum or steel rolling. Three sets of simulations are carried out to obtain an overall reduction of 59% in each set: the first set consists of four passes with a 20% reduction per pass, the

Flat Rolling Schematic Diagram

(a)

surface Traction F

Rigid

~

L rolls

d Traction

2

friction roll velocity

X

FIG.22. (a) Schematic of flat rolling process and (b) Eulerian finite-element mesh of the deformation zone.

128

Paul R. Dawson and Esteban B. Marin

second set of two passes with a 36% reduction per pass, and the last set of one pass with a 59% reduction. In all sets, the initial thickness of the entering sheet is 5 mm. The sheet temperature is 675°C and is kept constant during the rolling process. The rolls are assumed to be rigid, with an outer radius of 5 cm. The angular velocity of the rolls is 33.4 rad s-' (tangential velocity of 1.67 ms-' at the roll surface). Sliding friction between the workpiece and the rolls is assumed, based on a velocity difference friction model with a constant friction coefficient of 5.0 x lo8 Pas m-' [34]. With this value, the sheet velocity at the exit ranged from 1.75 m s-l (for a reduction of 20% per pass) to 2.05 m s-' (for a reduction of 59% in one pass). For these conditions, the neutral point (the point at which the roll and workpiece have equal velocity) lies between the first and last points of contact between the workpiece and roll. A typical finite-element mesh used for a rolling pass is presented in Figure 22b. Because of symmetry about the centerline, only the upper half of the workpiece is analyzed. The inlet and outlet lengths of the workpiece are half of the length of the deformation zone under the roll. Each finite-element mesh consists of 260 six-noded triangular elements which, although rather coarse, is adequate to examine trends in the rolling process. The velocity field is approximated by continuous piecewise quadratic interpolation functions, and the pressure distribution over an element is interpolated by using discontinuous piecewise linear functions. The procedures for making a free surface correction upstream of the roll, as well as the technique used for the streamline integrations, is detailed elsewhere [34]. The step length used to define and integrate each streamline is equivalent to 6% of the characteristic length of the smallest element in the mesh. The initial guess for the velocity field that is needed for starting the anisotropic equilibrium iterations comes from the finite-element solution and an isotropic phenomenological constitutive model [49, 391. Two to three additional iterations are required for the anisotropic steady-state solution to converge, using the stiffness defined by eq. (110). The evolution of properties is computed by tracking aggregates of crystals along streamlines of the flow field. Sufficient streamlines are traced through the flow field to resolve the variation in properties through the thickness of the workpiece. Every polycrystalline aggregate is a collection of 500 HCP crystals that are inextensible along their c-axes. The initial crystal orientations are randomly chosen from a uniform distribution. The hardness distribution for all slip systems for each crystal before the first pass is also uniform and equal to to (see Tables 1 and 2). For subsequent passes, the slip system hardnesses and the crystal orientations at the upstream boundary of the mesh are obtained from the values predicted by the simulation at the downstream boundary of the previous pass.

Mechanics of Metal Deformation Processes

129

The rolling direction velocity component and the effective deformation rate are shown on the Eulerian mesh in Figure 23 for a typical pass. The highest deformation rates arise near the initial point of contact between the roll and the workpiece. Closer to the centerplane, the deformation rate reaches peak values further into the deformation zone. The near-surface streamlines experience deformation histories with much larger shear components than do near-centerplane streamlines, owing to the frictional tractions imposed at the surface by the rolls. The ratio of the shear components to the normal component associated with idealized plane strain compression depends on the rolling geometry (including the reduction, roll radius, and frictional characteristics), and can be on the order of unity. This implies that the direction of straining is substantially different for near surface aggregates than for centerplane aggregates. Textures are shown in Figures 24,25, and 26 for the three sets of simulations. Here (0001) pole figures are presented, since the c-axis orientations are of principal interest, and these are easily visualized in the pole figures. Along the centerplane, the textures for all cases are similar and correspond to the plane strain compression textures presented earlier for the constrained hybrid assumption. There is a strong c-axis component of texture oriented toward the normal (ND) direction, with some spread in it toward the transverse (TD) direction. Intensities rise rapidly in the latter stages of reduction for the multipass simulations. The nearsurface textures show a tilt in the c-axes away from the normal direction. The

U 1.79 1.67

1.55 1.44 1.32 1.20

140.0 116.0 92.0

68.0 44.0

20.0 FIG. 2 3 . Velocity (rolling direction component) and effective deformation rate distributions for a typical pass.

Paul R. Duwson and Esteban B. Murin

130

cOOOl> - unidirectional rolling - 59% reduction ND

ND

RD

m a . int. = 62.66 s = 0.02

0.40

ND

RD

RD

m a . int. = 62.37 s = 0.50

max. int. = 65.92 s = 0.98

1.00 2.51 6.32 15.91 40.00

FIG.24. Near-surface (s = 0.98), midheight (s = 0.50). and near-centerplane (s = 0.02) textures computed using constrained hybrid assumption. Total reduction of 59%in one pass. (0001)equal area projection; scale is multiple of random. s is the normalized distance from the centerplane.

tilt is not large in any of the sets of simulations, but the angle does increase in magnitude in going from several lighter reductions to one heavy reduction. Furthermore, the strength of the surface texture relative to the centerplane texture depends on the rolling schedule. When the full reduction is achieved in a single pass, the surface texture has a maximum intensity that exceeds the centerplane texture; for other cases, the intensity of texture is greater at the centerplane than at the surface. The influence of repeated reversals in the shears near the surface with multiple passes has the effect of producing a less intense texture. Overall, the influence of through-thickness gradients in the deformation rate is to produce a tilt in the c-axes that corresponds to a shift toward a pure shear or simple shear texture. With fewer passes to obtain the same reduction, there is both larger tilt of the c-axes toward the pure shear orientation and an increase in intensity. The textures predicted using the constrained hybrid assumption are extremely strong and, as discussed in Section VII, tend to have the crystal c-axes aligned with the compression (ND) direction to a far greater extent than do other models. For this reason, it is useful to compare the trends concerning texture gradients obtained with the constrained hybrid assumption to those generated using a different partitioning assumption. From such a comparison we can determine whether the predicted trends are peculiar to the specific modeling assumptions. The uniform stress assumption is also capable of handling HCP crystals and is used for comparison with the constrained hybrid assumption.

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131

<0001> - unidirectional rolling - 36% reduction/pass pass 1 -total reduction 36% ND ND ND

RD

RD

max. int. = 8.02

max. int. = 7.56

max. int. = 8.77

ND

Dass 2 -total reduction 59% ND

ND

RD

max. int. = 62.29 s = 0.02 0.40

max. int. = 53.13 s = 0.50 1.00

2.51

RD

max. int. = 56.35 s = 0.98

6.32 15.91 40.00

FIG. 25. Near-surface (s = 0.98), midheight (s = 0.50),and near-centerplane ( s = 0.02) textures computed using constrained hybrid assumption. Total reduction of 59% in two passes. (0001) equal area projection; scale is multiple of random. s is the normalized distance from the centerplane.

We evolve texture along the streamlines at s = 0.02, 0.5, and 0.98, using the velocity gradient histories from the simulations performed using the constrained hybrid assumption. By using the same velocity gradient histories, we can evaluate the impact of the partitioning rule on the texture gradients for identical sets of velocity fields. For the uniform stress calculations, the pyramidal slip system strength is five times the basal strength, and the other model parameters are given in Table 1. The textures predicted using the uniform stress assumption are considerably weaker than the constrained hybrid textures. However, the trends with respect to the through-thickness texture gradients are quite similar. As is evident from Figure 27, the near-centerplane textures are nearly identical for all of the reduction

Paul R. Dawson and Esteban B. Marin

132 <0001>

- unidirectional rolling - 20% reduction/pass pass 1 - total reduction 20%

FIG.26. Near-surface (A= 0.98), midheight (s = 0.50). and near-centerplane (.I. = 0.02) textures computed using constrained hybrid assumption. Total reduction of 59% in four passes. (0001) equal area projection: scale i n multiple of random. s is the normalized distance from the centerplane.

schedules. However, the near-surface textures do show differences. For the case involving the full reduction in a single pass, there is a definite tilting of the c-axes in the near-surface texture, and the greatest texture intensity appears at the surface. For the case involving four reductions of 20% per pass, the tilt of the c-axes is less pronounced, and centerplane and surface texture intensities are comparable. In fact, for this case the variations in texture through the thickness of the workpiece are small, in terms of both the positions and magnitudes of the principal components. Thus although the details of the textures are different for the two partitioning assumptions, the trends they predict regarding the influence of rolling schedules on texture variations are comparable.

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133

coo01 > - unidirectional rolling - 20% reductionlpass pass 3 - total reduction 48.8% ND ND ND

RD

RD

pass 4 - total reduction 59%

RD

m a . int. = 61.48 s = 0.02 0.40

m a . int. = 58.67 s = 0.50 1.00 2.51

max. int. = 53.41 s = 0.98

6.32 15.91 40.00

FIG 2 6 . -continued

VII. Studies of Microstructure At several points in the preceding sections of this article, we have noted that assumptions must be made to link the macroscale and microscale motions. That is, we must choose a rationale to partition the macroscopic straining among the crystals of an aggregate. The results presented in Section I11 show the sensitivity of the computed textures to the linking hypothesis. In the example of the rolling of HCP titanium, the strong basal textures are predicted in part because of the characteristics of the assumption employed (constrained hybrid). We must also decide on the level of detail used to represent the orientation distribution, whether this is in terms of the number of elements in the finite-element discretization of orientation space or the number of crystals in a discrete aggregate. In this section of the article we present two studies in which we examine these issues via numerical simulation.

Paul R. Dawson and Esteban B. Murin

134

(a)

cOOOl> - unidirectional rolling - 59% reduction in 1 pass ND

ND

ND

RD

max. int. = 2.31 s=0.02 0.50

max. int. = 4.74 ~=0.98

max. int. = 2.65 ~=0.50 1.08

1.66 2.24

2.82 3.40

(b) <0001> - unidirectional rolling - 59% reduction in 2 passes ND

ND

ND

RD

max. int. = 2.36 s=0.02 0.50

max. int. = 2.51 ~=0.50

RD

max. int. = 3.40 ~=0.98

1.08 1.66 2.24 2.82 3.40

FIG.27. Near-surface (s = 0.98), midheight ( s = 0.5). and near-centerplane ( s = 0.02) textures using the uniform stress assumption. a) Total reduction in one pass; b) total reduction in two passes; c) total reduction in [our passes. (0001) equal area projection; scale is multiple of random. s is the normalized distance from the centerplane.

A. AGGREGATE SIZESTUDY In the simulation of metal-forming processes, large numbers of elements are commonly needed to resolve the workpiece deformation accurately. In such cases, it is advantageous to quantify the texture with as few orientations as possible to

Mechanics of Metal Deformation Processes (c)

135

cOOOl> - unidirectional rolling - 59% reduction in 4 passes ND

max. int. = 2.35 s=0.02

ND

ND

max. int. = 2.74 ~=0.50

max. int. = 3.10

~=0.98

0.50 1.08 1.66 2.24 2.82 3.40 FIG.

27. -continued

lessen the computer execution times. Clearly, the smaller the number of crystals in an aggregate, the more difficult it becomes to represent a texture well, so the minimum acceptable size usually is dictated by the complexity of the texture. A measure of the robustness of a representation is the sensitivity of derived mechanical properties to modifications in the representation, such as deleting a few crystals or altering their orientations. For example, two sets of crystals may be selected randomly from the same orientation distribution. If the sample size is sufficiently large, the mechanical properties derived from both are indistinguishable. However, if the sample size is too small, the derived properties differ. Should small samples be assigned to different elements in a body, the properties in the body vary spatially. Consequently, the deformation is inhomogeneous, even if the boundary conditions normally give rise to a homogeneous state of stress. Such variations in deformation ultimately have an impact on the texture evolution. Beaudoin et al. [ 121 simulated the compression of cylindrical aluminum specimens taken from a rolled plate. The specimens were discretized with finite elements and assigned different aggregates of crystals sampled from the same initial orientation distribution for the rolled aluminum. A number of simulations were performed, using aggregates of different sizes, but for any one simulation the same number of crystals was assigned to every element. The influence on texture evolution was substantial. Simulations using large aggregates (- 1000 crystaldaggregate) showed nearly uniform deformation over the entire sample, and texture evolution equivalent to a homogeneous deformation. Simulations having small aggregates in every element showed substantial inhomogeneity in the

136

Paul R. Duwson and Estebun B. Murin

straining over the sample and developed more diffuse textures-ones actually in better agreement with experiment [ 131. More diffuse texture with smaller numbers of crystals in every aggregate is not a surprising result, once it is evident that the deformation differs locally from the macroscopic average. A less obvious issue is whether the number of orientations can affect the manner in which the individual crystals reorient for a particular local deformation. For simulations based on strict application of the Taylor assumption (and identical slip system strengths), this issue does not arise. Every crystal deforms with the macroscopic deformation rate, and the lattice reorientation is not influenced by the behavior of other crystals in the aggregate. The aggregate size does become important, however, for partitioning rules in which the crystal deformation rate depends on the texture, and thus on the texture representation. In such instances, the number of crystals in an aggregate may affect the texture evolution, both through the variability in the properties from aggregate to aggregate and through its influence on the behavior of the aggregate itself. For HCP crystals that are inextensible along the c-axis, the constrained hybrid assumption offers a method for determining the crystal deformation rates from the macroscopic values. With this assumption, both effects just discussed are possible. The latter behavior is examined first by comparing the texture evolution of isolated aggregates under identical imposed deformation histories. To concentrate on the influence of geometric hardening alone, hardening of the slip system is suppressed (slip system hardening is not substantial for this material, and although we do consider hardening elsewhere in the paper, it is not unreasonable to treat the slip systems strength as constant). A moderately high rate sensitivity is specified ( m = 1/3) [84]. Samples of 1024 crystals are constructed from aggregates of different sizes. For the largest aggregate size, only crystals from a single aggregate appear. For smaller aggregate sizes, the number of aggregates is simply 1024 divided by the number of crystals in the aggregate. The initial orientations for crystals in all aggregates of one size are chosen independently from the same isotropic distribution. Figure 28 shows the (0001) pole figures for a plane strain compression deformation to an effective strain of 0.75. The textures for the different cases are qualitatively similar: the c-axes rotate toward the compression (ND) axis, with some spread toward the transverse (TD) direction. However, the intensity of the texture is higher for a sample composed of smaller aggregates than a sample composed of larger ones. The maximum intensity increases from about 12.8 (times random) for a sample having a single aggregate of 1024 crystals to approximately 15.5 (times random) for samples composed of aggregates having only 16 crystals. As is evident in Figure 29, the stress rises during compression because the crystals

137

Mechanics of Metal Deformation Processes TD

<0001>

TD

RD

1024 crystals I agg. max. int. = 12.75

256 crystals I agg. max. int. = 12.80

TD

TD

64 crystals I agg. max. int. = 14.03

16 crystals I agg. max. int. = 15.55

0.53 1.00 1.90 3.61 6.85 13.00 FIG.28. Texture prediction using the constrained hybrid assumption for homogeneous plane strain compression textures computed with aggregates of various sizes. (0001) equal area projection; scale is multiple of random.

are collectively rotating toward an orientation with higher Taylor factors (principally toward having the c-axis aligned with the compression axis). Since the slip system strengths are constant, the increase in stress is due entirely to geometric hardening. The small aggregate size sample shows appreciably higher stress at strains above 0.75, consistent with its stronger texture. The cause of the more rapid texturing originates with the projection operator’s dependence on aggregate size. The projection operator’s magnitude is larger for smaller aggregates, rising sharply as the number of crystals in the aggregate drops below 100 (Figure 30). Consequently, there is a systematic influence of the aggregate size on the magnitude of the crystals’ deformation rates from the projection operator. The number of crystals chosen to represent a texture therefore affects the predicted rate of texture evolution.

Paul R. Dawson and Esteban B. Marin

138

---+--- 16crysIagg

--+-

0.0

0.2

64cryslagg 256cryslagg 1024 crys I agg

0.4

0.6

0.8

Macroscopic effective strain (E) FIG.29. Geometric hardening predicted using the constrained hybrid assumption for homogeneous plane strain compression computed with aggregates of various sizes.

We now return to the influence of aggregate size on the spatial variations in properties. Finite-element simulations of plane strain compression are performed with the viscoplastic finite-element formulation outlined in Section V.B, using a mesh composed of 1000 elements (Figure 31) in the same fashion as Beaudoin et al. [12]. In each element resides an aggregate with an identical number of orientations, but independently chosen from an initially uniform distribution. Simulations are performed using aggregates of 16, 64, 254, and 1024 crystals. The deformed meshes after a strain of unity for the 1024 and 16 crystaldaggregate cases, presented in Figure 3 1, illustrate the spatial heterogeneity introduced by the variations in mechanical properties with smaller aggregates. The corresponding texture evolution appears in Figure 32. Although there is a tendency for the texture to be more diffuse when the deformation varies spatially (as allowed in the finite-element simulation), the dominant effect on texture is from the projection operator being a function of the aggregate size. For simulation results to be insensitive to the aggregate size, the number of crystals in an aggregate should number at least 250 [84].

Mechanics of Metal Deformation Processes

139

2.0

'A

a V ' 1.0

Q)

cn

s Q)

2 0.5

0.0 1

Number crystals / aggregate FIG.30. Average projection tensor predicted using the constrained hybrid assumption for various aggregate sizes and levels of strain under plane strain compression.

&=o.o

L

x=RD

y=TD z=ND

Y

FIG.3 1. Finite-element meshes for two aggregate sizes. Constrained hybrid assumption; plane strain compression. (A) Initial mesh: (B) Deformed meshes.

140

Paul R. Dawson and Esteban B. Marin A. FINITE ELEMENT SIMULATIONS

D

<0001> &=0.75

T

A

1

18.00 1024 crystals 1 agg. Max. Int. = 17.96

16 crystals / agg. Max. Int. = 24.56

B. MATERIAL POINT SIMULATIONS

I

8.74 4.24

2.06 1 .oo 0.49

1024 crystals 1 agg. Max. Int. = 18.39

16 crystals / agg. Max. Int. = 23.22

FIG.3 2 . Comparisons of textures from homogeneous and heterogeneous straining resulting from two aggregate sizes. Constrained hybrid assumption; plane strain compression. (0001) equal area projection; scale is multiple of random.

B. HYBRIDELEMENT POLYCRYSTAL SIMULATIONS Numerical modeling of polycrystals provides an approach for studying the behavior of polycrystalline metals that complements experimental data. Trends in the behaviors of polycrystals can be extracted from the simulation results, provided that there is confidence in the accuracy of the simulation tool. Such trends often are difficult or expensive to obtain experimentally,making simulation attractive as a useful alternative for experiment. Of course, simulation does not replace experiment; rather, simulation can reinforce experiment by assisting in the interpretation of the experimental findings. For polycrystalline solids, simulations of polycrystals are especially valuable in developing an understanding of the role of grain interactions in the deformation of constituent crystals and in the subsequent texture evolution. It has been appreciated since the first uses of Taylor and Sachs

Mechanics of Metal Deformation Processes

141

assumptions that the assumed grain interactions are greatly simplified, and that the simplicity gained in the models comes at the expense of the accuracy of the predictions. This is not to say that such predictions have not been valuablequite the contrary. However, the predictions from these models often give texture components that are displaced in orientation space from the experimental observations and evolve too rapidly. To improve on the models is a difficult task, because the exact influence of the grain interactions on the texture evolution in particular is not easily abstracted. In this example we discuss simulations of collections of crystals that represent samples of the metal. Every crystal in a sample coincides with a distinct finite element, so that the properties within an element are those of a single crystal, the orientation of which is determined from sampling of an orientation distribution. Balance laws are enforced over the collection of crystals (elements) via the finite-element method. The macroscopic motion is imposed through boundary conditions on the body defined by the crystals, rather than a priori through a partitioning assumption such as the Taylor hypothesis. Such simulations are of the first category outlined in the Introduction. As summarized in the Introduction, finiteelement simulations of polycrystals of the first category have been conducted for many years. Recent advances in computer speeds, especially those enabled by parallel architectures, have made the simulation of large three-dimensional polycrystals a much more viable tool for studying the behaviors of polycrystals. The advantage of modeling a polycrystal with a finite-element discretization is that the crystal interactions emerge from the simulations as a consequence of enforcing the balance laws at the crystal interfaces. Using parallel computing strategies, sufficiently large numbers of crystals can be considered to provide physically meaningful environments for the crystals. That is, each crystal is surrounded in three dimensions by other crystals and is distant from the boundary of the domain. One example of studying three-dimensional polycrystals is the simulation of FCC metal behavior, using a viscoplastic approximation together with a hybrid finite-element formulation [14, 1201. The simulations give textures that are more diffuse than corresponding computations performed with a Taylor assumption. Furthermore, important components of the texture differ in strength and location in orientation space. In particular, the finite-element simulations develop the Brass component under plane strain compression, whereas predictions using the Taylor assumption do not. This is attributed to the heterogeneity in the straining from crystal to crystal, especially certain shear components of the deformation rate that are zero in the macroscopic average. Grain shape alters the strength of the heterogeneity for certain components of the deformation rate, and consequently further modifies the texture. The importance of the relative strength of a crystal’s neigh-

142

Paul R. Dawson and Esteban B. Marin

bors dominates over the orientation of the crystal in determining the deviation in its deformation rate from the macroscopic average [ 1201.

1. Hybrid Finite-Element Formulation The simulations presented in this section employ the hybrid element formulation of Beaudoin et al. [ 141. The more conventional velocity/pressure formulation described in Section V.B and used in the rolling application (Section V1.B) fails to converge smoothly if the number of crystals in each aggregate becomes too small. For a single crystayaggregate (that is, each element is an individual crystal), the solution usually fails to converge all together. Although the inclusion of elasticity can alleviate this difficulty [82], it complicates the formulation. The R-value analyses of Section V1.A use this latter approach, largely because the elastic response and the transition from elastic to elastoplastic behavior is a central issue in the evaluation of the R-value. Hybrid element formulations prove very effective in retaining a viscoplastic approximation, while achieving convergence robustly [132,6, 191. The hybrid formulation [ 141is constructed to obtain solutions that enforce equilibrium of traction across intercrystal boundaries. The crystals are the volumes associated with the domain decomposition at the heart of hybrid methods. The grain boundaries are domain boundaries. Within single crystals, equilibrium is ensured by the use of self-equilibrated stress trial functions. The elements, or domain subdivisions, are constrained to be in mutual equilibrium by requiring that, in a weighted residual sense, the integral of surface tractions over all surfaces vanishes. This constraint is written over all domains of the polycrystal

where 4 are weights and the superscript e denotes an elemental surface. The traction, t, at any point on the boundary is related to the stress via the Cauchy formula

t =a

*

g = (a’- PI) * g.

(119)

Substitution of the Cauchy formula into the traction equilibrium residual gives, after integration by parts, Tr[(a’ - PI) V 4 ] d v -

I ,4

*

1

t d a = 0.

(120)

Assumption of isochoric plastic deformations requires that the divergence of the velocity vanish (neglecting elastic deformations), from which a second weighted

Mechanics of Metal Deformation Processes

143

residual is formed, using weights @,

ke

@(TrD)dv = 0.

(121)

The crystal constitutive behavior is obtained from the relation between the rate of deformation and the deviatoric stress (eq. (19)). A residual is constructed using this equation, together with appropriate weights, TC,

To estimate the crystal stiffness, M c ,eqs. (19) and (20) are solved, using the deformation rate corresponding to the previous iterate of the velocity field. Trial functions are introduced in the residuals for the interpolated field variables. Using the hybrid formulation, trial functions for the deviatoric stress appear, in addition to those for the velocity and pressure (eq. (89)).

Here [ N u] are piecewise discontinuous functions that satisfy equilibrium within an element a priori [ 191. For the crystal constitutive response relation, the residual from eq. (122) relates nodal stresses to the nodal velocities,

where

and

Using the above matrices, the traction equilibrium residual (eq. (120)) is given by

c

"Rl{sC} - IGel{pl - {f)]= 0.

(127)

r

The nodal stresses can be eliminated from this equation by inverting eq. (124), and then substituting the result into eq. (127). This yields

C [[Rl[HCl-'IRIT~Ul- [Gelif') - If)] = 0. e

(128)

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Paul R. Dawson and Esteban B. Marin

This equation is solved simultaneously with the discretized residual for the incompressibility constraint

to give the velocity field for the polycrystal corresponding to its current geometry, state, and loading. Special attention is needed in solving this system by using the conjugate gradient method due to the poor conditioning resulting from the incompressibility constraint [ 121. With the velocity field known, the geometry and microstructural state are advanced over a time increment by Euler integration of the coordinate velocities and of the evolution equations for the lattice orientations and strengths. 2. HCP Polycrystal HCP metals show greater single crystal anisotropy than do most FCC metals. The difficulty of slip in the direction of the crystal c-axis accentuates the yield surface anisotropy. As mentioned previously, the difference in strength between prismatic and pyramidal slip systems can be sufficiently large to motivate the idealization that the HCP crystals are inextensible along their c-axes. Although the inextensible assumption is perhaps too severe, imposing the Taylor assumption creates difficulties as well. If every crystal must accommodate the macroscopic average, extension along the c-axis is, in general, required of every crystal. This results in both unrealistically high stress (needed to activate the pyramidal systems) and inaccurate texture predictions (since the distribution of slip over the slip systems is not accurate). Simulations of the compression of HCP titanium samples have been conducted to quantify the degree of the strain heterogeneity in a polycrystal, allowing but not requiring crystals to activate stronger pyramidal slip systems. A mesh of 4096 brick elements represents a sample of the metal having an equal number of crystals. The inner set of 1000 elements defines an aggregate of crystals referred to as a hybrid element polycrystal. The remaining outer 3096 elements serve as a medium through which a chosen deformation history is imposed. In particular, plane strain compression and uniaxial compression are examined. In both cases, crystals chosen randomly from an isotropic orientation distribution are assigned one to an element to initialize the texture. The slip system constitutive parameters correspond to those given in Tables 1 and 2. The deformation history is imposed, using macroscopic axial strain increments of approximately 0.006. Considerable heterogeneity arises during the deformation. As the sample compresses, elements distort from regular brick shapes, showing the influence of local shears. This is evident in the initial and deformed meshes for plane strain compression shown in

Mechanics of Metal Deformation Processes

145

ND

FIG.33. Initial and deformed meshes for the hybrid element polycrystal under plane strain compression.

Figure 33.* The heterogeneity in deformation is strong, and its impact on the texture evolution is substantial in comparison to textures predicted using either the constrained hybrid or Taylor assumptions. Details of the plane strain and uniaxial compression simulations are discussed in the following paragraphs, along with the implications they suggest regarding various partitioning assumptions. The textures for the hybrid element polycrystal are presented over the HCP fundamental region in Figure 34 for plane strain compression using an initial ratio of the pyramidal to basal strengths of 5. The corresponding orientation distributions for the Taylor and uniform stress assumptions appear in Figures 8 and 15. Several points can be made concerning comparisons of these predictions. Texture components for the hybrid element polycrystal share some, but not all, of the texture components predicted with the Taylor assumption. In particular, the component associated with the c-axes oriented in the rolling (RD) direction predicted by the Taylor assumption is absent (or quite weak) in the hybrid element polycrystal orientation distribution. The component of the texture associated with a c-axis orientation toward the compression (ND) axis, but tilted from it, is similar in the location for the two assumptions, although it is weaker for the hybrid element polycrystal. This feature passes through the fundamental region nearly parallel to the ND-axis, but offset from it in either the plus or minus TD directions (indicating a c-axis tilt toward the rolling direction). Furthermore, the textures predicted with the hybrid element polycrystal are more diffuse than the corresponding Taylor assumption computations. Similar points can be made concerning the comparison 'Actually, the textures shown later correspond to simulations in which the mesh is repaired at intervals of approximately 10% strain so as to avoid such severe element distortions.

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Paul R. Dawson and Esteban B. Marin

A 16.0 14.2 12.4 10.7 8.9 7.1 5.3 3.6 1.8 0.0

ITD

,RD

F IG .34. Hybrid element polycrystal orientation distribution A at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Plane strain compression; pyramidal strength 5 times basal strength. Peak value = 7.0.

of uniform stress and hybrid element polycrystal computations. Although neither texture displays c-axis orientations oriented in the rolling direction, features of the fiber near the ND axis are different. For the uniform stress assumption, there are peaks at f0.66TDmaXthat are considerably stronger than the value at the origin. Texture variations predicted by the hybrid element polycrystal are more muted. The orientation distribution for the uniform stress assumption also generally displays greater texture intensities. For the case of pyramidal strength 10 times the basal strength, the hybrid element polycrystal texture (Figure 35) is more diffuse than the texture corresponding to a ratio of 5. Furthermore, there is a tendency for the c-axes to exhibit less tilt away from the TD axis. The texture for the Taylor assumption (Figure 36) with pyramidal strength 10 times basal does differ from the Taylor assumption texture with lower pyramidal strength, but to a lesser extent than differences in the hybrid element polycrystal results. In contrast to the hybrid element polycrystal, the Taylor assumption results show increased intensity in the texture with greater pyramidal strength. The uniform stress assumption gives virtually no difference

147

Mechanics of Metal Deformation Processes

A

F I G . 3 5 . Hybrid element polycrystal orientation distribution A at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Plane strain compression: pyramidal strength 10 times basal strength. Peak value = 5.4.

for the cases of pyramidal strength 5 and 10 times the prismatic strength (the latter texture is not shown). These stronger slip systems are not activated in either case. The trend toward less tilt of the c-axes in the hybrid element polycrystal textures is interesting in comparison to the constrained hybrid assumption predictions (shown in Figure 14). This assumption gives virtually no tilt, but rather shows a single component of texture positioned along the ND axis at ND = fNDma, (same point due to symmetry). It appears that the hybrid element polycrystal may indeed be approaching this limiting case for infinitely strong pyramidal slip systems (inextensible crystals), although this point has not been proved. A major distinction, however, continues to be the strengths of the orientation distributions. The constrained hybrid orientation distribution is far more intense than the hybrid element polycrystal distribution. The heterogeneity of straining among crystals of an aggregate plays a critical role in modifying the texture evolution. The Taylor assumption fixes the crystal deformation rates so that they are identical; the uniform stress and constrained hy-

148

Paul R. Dawson and Esteban B. Marin

A 16.0 14.2 12.4 10.7

8.9 7.1

5.3 3.6 1.8

0.0

ITD

,RD

FIG. 36. Discrete aggregatenaylor assumption orientation distribution A at an effective strain of unity shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Plane strain compression; pyramidal strength 10 times basal strength. Peak value = 22.4.

brid assumptions both allow for different deformation rates in every crystal. For both of these latter models, the variation in deformation rate depends only on a crystal’s own orientation plus the orientation distribution for the aggregate. In the hybrid element polycrystal, the additional dependence on crystal arrangement is introduced. Thus a crystal’s deformation rate depends on the orientation of crystals that neighbor it. The effect of this dependence has been explored for FCC polycrystals [ 1201 as well as for HCP polycrystals presented here. The methodology involves repeating the simulation of the response of the hybrid element polycrystal under plane strain compression using different assignments of orientations to elements, but keeping the same set of orientations. In this way, every crystal has a different set of neighbors in each simulation. Reassignments are repeated to give a total of 25 simulations. Each orientation then has associated with it 25 deformation rates corresponding to 25 sets of neighbors for the same plane strain compression loading. A summary of these data is shown in Figure 37, in which the largest, smallest, and average values of one deformation rate component are

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o Maximum of 25 0

0.5 1.0 Theta [rad]

Minimum of 25 Average of 25

1.5

F I G . 37. Low, high, and average of the crystal’s extensional deformation rate components for 25 hybrid element simulations using inner 1000 crystals to define a polycrystal. Plane strain compression; pyramidal strength 5 times basal strength.

plotted as a function of the angle between the crystal c-axis and the compression (ND) axis. It is evident that the effect of neighborhood is very strong. Differences between high and low values of deformation rate are considerably larger than the variations in the average values of deformation rate with the c-axis orientation. A similar plot for the constrained hybrid and Taylor assumptions (Figure 38) shows a single value for the Taylor assumption and a distribution for the constrained hybrid assumption that is similar to the hybrid element polycrystal average values. The constrained hybrid assumption has only a single value for any orientation,

2.0 n v)

Taylor Constrained Hybrid

1.5

Y

Theta [rad] FIG.3 8. Crystals’ extensional deformation rate components for 1000 orientations computed using the constrained hybrid assumption. Plane strain compression.

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owing to the assumption’s dependence on only the crystal’s orientation and the full orientation distribution. This is significant, as it shows that although variations in straining give a plausible distribution of deformation rate with crystal orientation, they are not adequate to model the full effect of strong anisotropy in the single crystal-behavior. The comparison between experiment and theory is made difficult for HCP systems by the broad range of behaviors the systems display. The crystal’s aspect ratio (ratio of c-axis to a-axis lengths) is important, so trends for zinc or zirconium may be different from those for titanium. Furthermore, the temperature of the deformation and alloying additives influences the texture evolution through their effects on the relative strengths of active slip systems [9]. At lower temperatures, especially in pure metals, twinning often is an important deformation mode. We restrict our attention here primarily to textures developing in the warm-to-hot regimen for single-phase (a)materials. Under these restrictions, twinning is not significant, although large differences in the relative strengths of basaUprismatic and pyramidal systems can exist. The textures reported for such conditions are fewer than those reported for lower temperatures where twinning occurs. Tanabe et al. [125] have reported data for warm rolling that show a strong tendency for c-axes to align toward the compression (ND) axis, but to be tilted toward the rolling (RD)direction. This is in agreement with the textures computed using the hybrid element polycrystal. Larson et al. [78], Thornburg and Piehler [129], and Peters and Luetjering [lo61 all reported similar c-axis tilt toward the rolling direction for titanium systems with sufficient alloying to suppress twinning. This is in contrast to pure titanium deformed at low temperatures in which twinning is significant and the c-axis tilt is toward the transverse (TD) direction [107, 1081. Uniaxial compression textures computed using the hybrid element polycrystal for pyramidal strengths of 5 and 10 times basal strength are shown in Figures 39 and 40. In these cases, the deformation is imposed only to an effective strain of 0.75 because of degradation in the performance of the elements. Again, greater pyramidal strength tends to orient the c-axes more in line with the compression ( z ) axis and to give a more diffuse texture. The texture components associated with the c-axes being perpendicular to compression axis tend to weaken as the pyramidal strength increases from 5 to 10. The texture obtained using the constrained hybrid assumption has a single fiber, located along the compression axis (Figure 41). This appears to be a limiting case for very large pyramidal strength for the hybrid element polycrystal. As with plane strain compression, the hybrid element textures are much weaker than those for the constrained hybrid assumption. Textures are shown in Figures 42 and 43 for the Taylor assumption (with

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A 20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0

FIG.39. Hybrid element polycrystal orientation distribution A at an effective strain of 0.75 shown on cutting planes through the HCP fundamental region of' Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Uniaxial compression; pyramidal strength 5 times basal strength. Peak value = 7.1.

strengths of 5 and 10 times pyramidal) and in Figure 44 for the uniform stress assumption (only for 5 times, as 5 and 10 times textures are virtually identical). Interestingly, the Taylor and uniform stress textures are quite similar, although the offset from the compression axis is larger for the Taylor assumption. Increasing the pyramidal strength tends to strengthen the Taylor assumption texture, but not to a significant extent. Neither of these partitioning rules leads to the elimination of the c-axis texture component perpendicular to the compression axes. A number of modeling efforts have examined the impact of the relative strengths of slip systems, including the effect of twinning [79, 107, 109, 138, 91 on texture evolution for various HCP metals. Whereas the self-consistent theories do allow for some variations in straining, Taylor analyses do not. This variation is important in that it leads to more diffuse textures as well as to changes in the relative strengths of texture components. Tools such as the hybrid finite-element formulation are a means of quantifying, the impact of this feature of the behavior.

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FIG. 40. Hybrid element polycrystal orientation distribution A at an effective strain of 0.75 shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Uniaxial compression: pyramidal strength 10 times basal strength. Peak value = 4.1.

VIII. Summary Finite-element techniques offer the capability to simulate deformations that are spatially heterogeneous, that are governed by nonlinear equations, and that are controlled by properties that evolve with the deformation. Polycrystal plasticity can be used effectively in such finite-element formulations as the constitutive description of a textured metal to quantify its anisotropic properties from its crystallographic texture and the behavior of individual crystals. The advantages in combining finite-element methodology with polycrystal plasticity stem from being able to analyze complex problems, such as those that arise in metal deformation processes, with a theory that directly represents real features of the state, and to evolve the state as deformation proceeds. Critical to the use of such a state variable constitutive theory is the ability to initialize the state variables directly from tests and to compare simulation predictions to experimental observation. Here polycrystal plasticity has an advantage resulting from the intensive efforts

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A 50.0 45.0 40.0 35.0 30.0 25.0 20.0 15.0 10.0 5.0 0.0

FIG.4 1. Discrete aggregatekonstrained hybrid assumption orientation distribution A at an effective strain of 0.75 shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Uniaxial compression. Peak value = 49.0.

in quantitative texture analyses over the past several decades. Textures can be determined readily from experiment and rendered as orientation distributions. Slip system strengths are less accessible, but when the theory is restricted to the use of average strengths, values can be estimated from routine mechanical tests (tension or compression) of macroscopic samples. In this article we discuss the implementation of polycrystal plasticity theory in finite-element formulations. The intent is to document a methodology for accomplishing this task, discuss some of the issues that arise, and demonstrate its application to metal deformation processes. Several capabilities are essential for the implementation to be successful. One is that the method for representing the texture is indeed adequate for describing the complex textures that are present in metals. To capture a texture with accuracy requires either large numbers (more than 1000) of individual orientations in discrete aggregates or a representation of the orientation distribution probability density with a comparable number of degrees of freedom. For this task we see a considerable advantage in the use of piecewise approximations from finite element discretizations.

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A 20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0

FIG. 42. Discrete aggregaternaylor assumption orientation distribution A at an effective strain of 0.75 shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Uniaxial compression; pyramidal strength 5 times basal strength. Peak value = 22.8.

Another capability that is important is the methodology for linking the continuum fields with their counterparts at the crystal level. Macroscopic properties are evaluated by averaging single-crystal properties over an orientation distribution. The properties depend on the behavior of the individual crystals, as well as the manner in which the macroscopic deformation rate is partitioned among the constituent crystals. Furthermore, the evolution of state, as defined by the texture and slip-system strength, is sensitive to the partitioning rule, as was demonstrated for HCP crystals by using a number of rules. There is not a single rule that provides optimal partitioning; rather, the single-crystal properties often are influential in determining which rules are successful and which are not. The magnitude of the rate dependence, the degree of anisotropy, and the hardening behavior all affect the partitioning of deformation. A third component of a successful implementation is a finite-element formulation for the motion of the body that is consistent with the microstructural characterization. There is no unique finite-element formulation that is universally supe-

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A 20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0

FIG.43. Discrete aggregate/Taylor assumption orientation distribution A at an effective strain of 0.75 shown on cutting planes through the HCP fundamental region of Figure 3. Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Uniaxial compression; pyramidal strength 10 times basal strength. Peak value = 21.2.

rior. The hybrid approach is particularly useful for the viscoplastic approximation when the number of orientations within an element is small and the discontinuities in properties at interfaces are appreciable. In the hybrid formulation, the residual of equilibrium focuses on interelement tractions, tending to eliminate imbalances at element interfaces that can lead to poor convergence. For instances when there is a large sample of crystals within every element and the average properties tend to be smooth, a more traditional velocity-based viscoplastic formulation performs well. The inclusion of elasticity, while complicating the implementation, improves the robustness if elements contain only a single orientation. The applications presented are intended to demonstrate instances where the approach is a particularly useful tool. Deformation of the sheet is one case in which the texture affects the stability of the deformation field and thus the formability of the sheet. Here we focus on the computation of R-values, but in other publications we show the dependence of sheet performance in hydroforming and limiting dome height tests on the metal texture. In rolling, texture variations arising from

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A 20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0

2.0 0.0

FIG.44. Discrete aggregate/uniform stress assumption orientation distribution A at an effective strain of 0.75 shown on cutting planes through the HCP fundamental region of Figure 3 . Cutting plane position relative to the maximum coordinate value is indicated to the right of the plane. Uniaxial compression; pyramidal strength 5 times basal strength. Peak value = 10.5.

the inhomogeneity of the deformation are of technical importance for the mechanical properties of the product. Together, the finite-element method and polycrystal plasticity provide a method for quantifying the strength of texture gradients. As discussed here for the rolling of HCP titanium, the simulations can predict the effect of the rolling schedule on the variations in texture within the rolled metal. Finite-element simulations performed at small scale can help expose the behavior of polycrystals and assist in the assessment of partitioning rules. In the examples presented, the heterogeneity of straining over an aggregate can be seen to diffuse the texture, as well as to modify the components predicted in comparison to Taylor, uniform stress, or constrained hybrid assumptions. Furthermore, the strong dependence on local neighborhood is demonstrated. Additional refinement is expected to reveal further insights into the behaviors of polycrystals. A major factor in the successful combination of polycrystal plasticity and finiteelement formulations for metal deformations is the availability of modem computing resources. Strategies that utilize parallel computer architectures are essential to being able to embed in every element aggregates of crystals, whether they

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are represented by a discrete set of orientations or by a piecewise discretization (finite element) of orientation space, that have sufficient detail to capture realistic textures. With such strategies, simulating the deformation of a complex threedimensional part can include a complete characterization of the texture in every element and the evaluation of the mechanical properties from an appropriate averaging of single-crystal responses. The definition of “appropriate” depends in part on the intended use of the simulation results. For many applications the simple Taylor assumption suffices. For others it does not, and different assumptions must be used. To obtain increased accuracy or to model more complex materials, the variability of straining over the crystals in an aggregate is quite important. Although some models do exist for this purpose, as is discussed in this article for HCP metals, they are not entirely satisfactory. The expanding resource offered with parallel computing offers the potential to address this issue, in the short run by providing better understanding of polycrystal behaviors, and in the long run by eliminating the need to invoke partitioning assumptions.

IX. Notation Surface area of body Surface area in orientation space Orientation distribution Finite-element approximation of A Nodal parameters in finite-element approximation of A Slip direction on the (Y slip system Domain of the body Domain of the body in the natural (relaxed) configuration Crystal c-axis vector Diffusion parameter cc

@

cc

-

11 3

Macroscopic deformation rate Matrix form of D Crystal deformation rate Elastic portion of the crystal deformation rate Plastic portion of the crystal deformation rate Matrix form of DP Plastic portion of the crystal deformation rate in the relaxed configuration Matrix form of D p Base vectors

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Paul R. Dawson and Esteban B. Marin Green strain tensor components Scaling function in angle/axis representation Elemental matrix in orientation distribution evolution formulation Elemental matrix in velocity formulation Macroscopic deformation gradient Crystal deformation gradient Plastic portion of the crystal deformation gradient Plastic portion of the crystal deformation gradient in the relaxed configuration Metric tensor for orientation space Elastic strain matrix in velocity formulation Elemental volumetric mode in velocity formulation Element size Crystal spdstrain matrix for velocity formulation Symmetry rotations Assembled elemental ([ S"]{h'])matrices Second-order identity tensor Fourth-order identity tensor Residual for probability density conservation equation Assembled elemental [ K A ] matrices in orientation distribution evolution formulation Elemental stiffness matrix in velocity formulation Assembled elemental [ K " ] matrices Macroscopic velocity gradient Crystal velocity gradient Elastic part of the crystal velocity gradient Scaling factor for the velocity gradient Plastic part of the velocity gradient Mean linear intercept measure of grain size Normal vector to the a! slip system Slip-system constitutive parameters Crystal compliance Crystal elastic compliance Crystal plastic compliance Crystal compliance matrix Mass coefficient matrix Crystal plastic compliance matrix Axis normal vector in angle/axis representation

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Interpolation functions for Interpolation functions for uh Interpolation functions for p h Spatial derivative of [ N u ] Pressure Crystal projection tensor Matrix form of Pc Nodal point parameters in finite-element approximation of p Symmetric portion of the Schmid tensor, T, for a slip system Matrix form of p(Y Skew portion of the Schmid tensor, T, for a slip system Crystal orientation Set of crystal orientations comprising an aggregate Residual in orientation distribution approximation Rotation tensor Rotation in decomposition of F Elemental residual on deviatoric motion in velocity formulation Elemental residual on volumetric motion in velocity formulation Fundamental region Segments of the surface of R* Differential length in orientation space Average stiffness Crystal plastic stiffness Crystal elastic stiffness Crystal stiffness matrix Crystal plastic stiffness matrix Crystal elastic stiffness matrix Time Time step Traction vector Traction vector imposed on a B Schmid tensor Temperature Melt temperature Velocity vector Value of u imposed on the surface of B Finite-element approximation of u Nodal parameters in finite-element approximation of u Volume of body

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Paul R. Dawson and Esteban B. Marin Volume of orientation space Volume fraction of grains Crystal reorientation velocity Elastic stretch Vector representation of Q* Macroscopic spin Crystal spin Plastic portion of crystal spin Plastic portion of the crystal spin in the relaxed configuration Matrix representation of spin terms in eq. (58) Body coordinates Transformation matrix for vector representation of D Partitioned stiffnesskompliance for relaxed constraints

A. GREEKSYMBOLS Slip-system identification Volumetric factor (det (I c)) Shearing rate on a slip system Sum of the slip-system shear rate magnitudes Slip-system constitutive parameters Christoffel connexion tensor Diffusivity used in numerical solution of orientation distribution Effective strain Elastic strain tensor at the current time Elastic strain tensor at the end of the previous time step Vector normal to the surface of B Vector normal to flat grain boundaries Trace operator in matrix form Weighting functions used in finite-element solution of orientation distribution Nodal parameters used in finite element approximation of $ Weights used on the surface of R* in the finite-element formulation for the orientation distribution evolution Weighting function used in equilibrium residual in velocity solution Weighting functions used in volumetric deformation constraint of velocity formulation Elastic bulk modulus

+

K

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Elastic shear modulus Base vectors for grain axes Lattice spin Macroscopic Euler spin Crystal Euler spin Macroscopic Cauchy stress Crystal Cauchy stress Resolved shear stress on the (11slip system Macroscopic Kirchhoff stress Crystal Kirchhoff stress Slip-system strength Average slip-system strength Slip-system hardening parameters Angle between rolling direction and tensile axis of R-value specimen Slip-system hardening parameter

B. CONVENTIONS Vectors and second-order tensors are indicated with boldface lower- and uppercase letters, respectively, e.g., v and T; fourth-order tensors are denoted by calligraphic letters, e.g., P.The dyadic product of two vectors v1 and v2 is indicated as v1 8 v2. Tensor operations between two second-order tensors T1 and T2 are indicated as T1 Tz for the inner product (a second-order tensor), T1 8 T2 for the dyadic product (a fourth-order tensor), and TI : T2 for the scalar product (a scalar). Contraction operations over two indices between a fourth-order (P)and a second-order (T) tensor and between two fourth-order tensors PI and 732 are represented as P : T (a second-order tensor) and PI : P2 (a fourth-order tensor), respectively. The vector cross product between two vectors v1 and v2 is given by v1 x v2. Where index notation is used, we refer the tensor components to a general coordinate system, with the summation convention over repeated indices implied. Deviatoric quantities are denoted with primes. V indicates the nabla operator, and the trace operator for a second-order tensor A is indicated by Tr(A).

.

X. Appendix: Matrix Representations The various second order-deviatoric tensors used in the crystal constitutive equations, such as the crystal deformation rate tensor D'", are expressed as 5 x 1

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vectors, using the convention

-

-

In this context, the term (d* WP - W P d * )in eq. (58) is represented in matrix form as [~?P](E’*},where [WP] is the following 5 x 5 skew-symmetric matrix: -

[ W P ]=

I

0

0

0

0

0

W13 aw’p a ,wl3

2Wf2

0

0

-W& -WF3

WIp3

-W&

-2W’p2 -W’p3

W& -aw;,

-awg

Wf3

0 W‘p2

-Wf2 0

.

Furthermore, the vector {a} and the matrix [XI in the finite-element equations (eqs. (90-105)) are used in the following transformations: T O ) = {6IT{D},

(D’) = [Xl(D),

where { D ) = (Dl1 0 2 2 0 3 3 D2l D31 D32}T and ( D ’ ) is the 5 x 1 vector representation of the deviatoric part of ( D } . They are given by

(6) = (1 1 1 0 0

O}T

Acknowledgments Support for this work has been provided by the Office of Naval Research under contract N O 0 0 14-95-1-0314, and by the National Science Foundation under grant MSS-9114861. Computing resources on the Connection Machine CM-5 were provided by the National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign. The authors are grateful to Ashish Kumar for performing the computations of texture evolution using the finite-element

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orientation space formulation; to Vincent Prantil for original efforts in implementation of the constrained hybrid model; and Carlos T6me for use of codes for computing HCP yield surfaces. The authors wish to thank Armand Beaudoin, Nathan Barton, Donald Boyce, Fred Kocks, David Mika, Gorti Sarma, and Rudy Wenk for valuable discussions, comments, and suggestions. Many thanks to Karen Biesecker for her careful efforts in preparation of the manuscript.

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processed BSCCO superconductors. Meclz. Muter: 15,201-222 (1993). 2. S. L. Altmann, Rotations, quaternions and double groups. Oxford Univ. Press, Oxford, 1986. 3. R. J. Asaro, Micromechanics of crystals and polycrystals. Ad\. Appl. Mech. 23, 1-1 15 (1983). 4. R. J. Asaro, and A. Needleman, Texture development and strain hardening in rate dependent polycrystals. Actrz Metall. 33, 923-953 (1985). 5 . M. F. Ashby, Mechanisms of deformation and fracture. Adv. Appl. Mech. 23, 117-177 (1983). 6. S. N. Atluri, On “hybrid” finite element methods in solid mechanics. In: Advances in cornpurer metliods for partial differential equations (R. Vichinevetsky, ed.). Publ. Association Intemationale Pour Lc Calcul Analogique (AICA), New Brunswick, NJ, 1975, pp. 346-355. 7. Atlris offormabiliiy. CP titanium grade 3. National Center for Excellence in Metalworking Technology, 1994. 8. W. A. Backofen, Deformation processing. Addison-Wesley, Reading, MA, 1972. 9. B. Bacroix, G. R. Canova, and H. Mecking, The prediction of deformation textures in a - ,8 titanium. In: Large plustic deformations: Fundanzental aspects and applications to metalforming (C. Teodosiu, J. R. Raphanel, and F. SidoroK, eds.). Balkema, Rotterdam, The Netherlands, 1993, pp. 101-108. 10. D. J. Bammann, and G. C. Johnson, On the kinematics of finite-deformation plasticity. Acta Mech. 70, 1-13 (1987). 1 1. F. Barlat, Crystallographic texture, anisotropic yield surfaces and forming limits of sheet metals. Muter: Sci. Engrg. 91.55-72 (1987). 12. A. J. Beaudoin, K. K. Mathur, P. R. Dawson, and G. C. Johnson, Three-dimensional deformation process simulation with explicit use of polycrystalline plasticity models. Internat. J. Plast. 9, 833-860 (1993). 13. A. J. Beaudoin, P. R. Dawson, K. K. Mathur, U. F. Kocks, and D. A. Korzekwd, Application of polycrystalline plasticity to sheet forming. Comput. Methods Appl. MecA. Engrg. 117, 49-70 (1994). 14. A. J. Beaudoin, P. R. Dawson, K. K. Mathur, and U. F. Kocks, A hybrid finite element formulation for polycrystal plasticity with considcration of macrostructural and microstructural linking. hteriiat. .I. Plust. 11, 501-521 (1995). 15. A. J. Beaudoin, H. Mecking, and U. F. Kocks, Development of shear bands and orientation gradients in FCC polycrystals. In: Simulation o f materiuls processing: Theory, methods and a~plicutions-NUMIFORM ’95(S. Shen and P. R. Dawson, eds.). Balkema, Rotterdam, The Netherlands, 1995, pp. 225-230. 16. R. Becker, Analysis of texture evolution in channel die compression. I. Effects of grain interaction. Acta Mefall. Muter: 39, 121 1-1230 (1991). 17. R. Becker, and S. Panchanadeeswardn, Crystal rotations represented as Rodriguez vectors. Textures and Microstructures 10, 167-1 94 ( I 989).

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41. F. C. Frank, Orientation mapping. In: Eighth international conference on textures of materials (J. S. Kallend and G. Gottstein, eds.). The Metallurgical Society, Warrendale, PA, 1988, pp. 3-13. 42. S. F. Frederick, and G. A. Lenning, Producing basal textured Ti-6A1-4V sheet. Metal Trans. B 6B, 601405 (1975). 43. H. J. Frost, and M. E Ashby, Defurmation-mechanism maps. Theplasticity and creep of metals and ceramics. Pergamon Press, Oxford, 1982. 44. M. Gotoh, A finite element formulation for large elastic-plastic deformation analysis of polycrystals and some numerical considerations on polycrystalline plasticity. Internat. J. Numer: Methods Engrg. 12, 101-1 14 (1978). 45. M. E. Gurtin, An introduction to continuum mechanics. Academic Press, New York, 1981, 46. S. V. Harren, and R. J. Asaro, Nonuniform deformations in polycrystals and aspects of the validity of the Taylor model. J. Mech. Phys. Solids 37, 191-232 (1989). 47. P. Hansbo, The characteristic streamline diffusion method for convection-diffusion problems. Comput. Methods Appl. Mech. Engrg. 96,239-253 (1992). 48. J. Hansen, J. Pospiech, and K. Liicke, Tables for texture analysis of cubic crystals. SpringerVerlag, New York, 1978. 49. E. W. Hart, Constitutive relations for the nonelastic deformation of metals. J. Engrg. Muter: Tech. 98, 193-202 (1976). SO. A. Hasegawa, T. Nishimura, and S. Ohtani, The texture hardening of titanium and its alloy sheets. In: Titanium science and technology (R. I. Jaffee and H. M. Burte, eds.). Plenum, New York, 1973, pp. 1349-1363. 51. A. J. Hatch, Texture strengthening of titanium alloys. Trans. Metall. SOC.AIME 233, 44-50 (1965). 52. F. Havlicek, M. Tokuda, S. Hino, and J. Kratochvil, Finite element analysis of micro-macro transition in polycrystalline plasticity. Internat. J. Plast. 8, 4 7 7 4 9 9 (1992). 53. A. Heinz, and P. Neumann, Representation of orientation and disorientation data for cubic, hexagonal, tetragonal and orthorhombic crystals. Acta Cryst. A47, 780-789 (199 1). 54. R. W. K. Honeycombe, The plastic deformation of metals, 2nd edn. Edward Arnold, London, 1984. 55. H. Honneff, and H. Mecking, A method for the determination of the active slip systems and orientation changes during single crystal deformation. In: Fifth international conference on textures of materials (G. Gottstein and K. Lucke, eds.). Springer-Verlag, Berlin, 1978, pp. 265-275. 56. W. F. Hosford, The mechanics of crystals andpolycrystals. Oxford Univ. Press, Oxford, 1993. 57. T. J. R. Hughes, M. Mallet, and A. Mizukami, A new finite element formulation for computational fluid dynamics. 11. Beyond SUPG. Comput. Methods Appl. Mech. Engrg. 54, 341-355 ( 1986). 58. J. W. Hutchinson, Bounds and self-consistent estimates for creep of polycrystalline materials. Proc. Roy. SOC.London Ser: A 238, 101-127 (1976). 59. G. Ibe, and K. Liicke, Description of orientation distributions of cubic crystals by means of 3-D rotation coordinates. Texture 1, 87-89 (1972). 60. C. Johnson, Numerical solution of partial differential equations by the jinite element method. Cambridge Univ. Press, Cambridge, 1987. 61. C. Johnson, A. Szepessy, and P. Hansbo, On the convergence of shock-capturing streamline diffusion finite element methods for hyperbolic conservation laws. Marh. Comp. 54, 107-129 (1990). 62. C. Johnson, A new approach to algorithms for convection problems which are based on exact transport + projection. Comput. Methods Appl. Mech. Engrg. 100,45-62 (1992).

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ADVANCES IN APPLIED MECHANICS. VOLUME 34

Nonlinear Composites PEDRO PONTE CASTANEDA Department of Mechanical Engineering and Applied Mechanics

University i$ Pennsylvania Philadelphia. Pennsylvaniu

and

PIERRE SUQUET Luborutoire de Micanique et d’Acoustique / C.N.R.S. Mar.seille, France

I . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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175 I1. Effective Behavior and Potentials . . . . . . . . . . . . . . . . . . . . . . . . . A . Individual Constituents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 B . Local Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 C. Classical Variational Principles and Effective Potentials . . . . . . . . . . . 183 D . Classical Bounds of the Voigt and Reuss Type . . . . . . . . . . . . . . . . 185 I11. Variational Methods Based on a Homogeneous Reference Medium . . . . . . . 187 A . The Variational Principles of Talbot and Willis . . . . . . . . . . . . . . . . 187 B . Bounds via Piecewise Constant Polarizations . . . . . . . . . . . . . . . . . 189 191 C . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV . VariationalMethods BasedonaLinearComparisonComposite . . . . . . . A . Nonlinear Composites with Isotropic Phases . . . . . . . . . . . . . . . B . Nonlinear Composites with Anisotropic Phases . . . . . . . . . . . . . . C . Bounds via Piecewise Constant Moduli . . . . . . . . . . . . . . . . . . . . D . Interpretation of the Variational Procedure as a Secant Method . . . . . E . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . 192 . . 193 . . 198 205

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V . A Second-Order Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A . Weakly Inhomogeneous Nonlinear Composites . . . . . . . . . . . . . . . B . Nonlinear Composites with Arbitrary Phase Contrast . . . . . . . . . . . C . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

213 216

. 216 . 220 227

VI . A Selection of Results for Linear Composites . . . . . . . . . . . . . . . . . . . 228 A . Hashin-Shtrikman Bounds for Random Composites 228 with Ellipsoidal Symmetry . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 ISBN 0-12-002034-1

ADVANCES IN APPLIED MECHANICS. VOL. 34 Copyright 0 1998 by Academic Press . All rights of reproduction in any form reierved . W65-2165/98$25 00

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Pedro Ponte Castaiieda and Pierre Suquet B. Hashin-Shtrikman Bounds and Estimates for Random Composites with Particulate Microstructures . . . . . . . . . . . . . . . . . . . . . . . . 23 1 C. Self-consistent Estimates for Random Composites with Granular 233 Microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Third- and Higher-Order Bounds for Random Composites . . . . . . . . . . 235

VII. Applications to Nonlinear Composites and Discussion . . . . . . . . . . . . . A. PorousMaterials. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Rigidly Reinforced Materials . . . . . . . . . . . . . . . . . . . . . . . . . . C. Two-Phase, Rigid Perfectly Plastic Composites . . . . . . . . . . . . . . . D. Additional Results and Comparison with Other Schemes . . . . . . . . . E. An Incremental Elastoplastic Model Based on the Variational Procedure . VIII. Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. 237 237 246 . 253 . 262 . 274

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IX. Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ,281 A. Potentials, Convexity, Concavity and Duality . . . . . . . . . . . . . . . . . 28 1 B. Derivation of the Potential with Respect to a Parameter . . . . . . . . . . . 285 C. PTensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ,288 D. A Brief Review of Other Schemes . . . . . . . . . . . . . . . . . . . . . . . 292 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.295

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.295

I. Introduction Heterogeneous materials are ubiquitous in nature, and increasingly so in manmade systems. Often the distribution of hetereogeneity is such that the material appears to be homogeneous at a large enough length scale. It is then of practical as well as theoretical interest to ask the question: What are the “average” properties of such heterogeneous materials? This review article is concerned with the theoretical prediction of the “effective properties” of such “composite materials,” directly from the properties of their constituent phases and their distribution, or “microstructure.” Of course, considerable progress has been made on this problem for the case where the constitutive behavior of the phases that make up the composite is linear elastic. The focus in this article will be on composites with nonlinear constitutive behavior, including plasticity and creep. Thus, for example, this article will be concerned with the determination of the effective stress-strain relations for metal-matrix composites. However, the emphasis will be on the development of “homogenization” methods that will apply to broad classes of nonlinear material behavior, as opposed to any specific material system. Although the effective behavior of the composite will be the main focus, it is also important to provide insight into the statistical distribution of local quantities, such as averages

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or higher moments of the strains and stresses in each phase. These local quantities are extremely useful for understanding the evolution of nonlinear phenomena such as plasticity or damage. Research on composite materials with nonlinear constitutive behavior can be traced back to the classical work of Taylor (1938) on the plasticity of polycrystals, followed by the work of Bishop and Hill (1951a, b) and Drucker (1959) on ideally plastic polycrystals and composites, respectively. As will be discussed in the body of the paper, these estimates are the nonlinear equivalents of the VoigtReuss bounds for linear-elastic systems, and as such depend on the microstructure only through the proportions of the phases (or grain orientations). Recognizing the need to incorporate additional microstructural information to obtain improved estimates, several attempts have been made in the past to provide extensions of the self-consistent model for nonlinear composites, notably by Hill (1965a, b), who proposed an “incremental” version of the self-consistent method. This work spawned a large body of work, especially in the context of polycrystalline materials (see Hutchinson, 1970, 1976), including a simplified approach that has come to be known as the “secant” method (Berveiller and Zaoui, 1979). No attempt will be made here to review this work, although a brief discussion of the incremental and secant methods will be provided. In recent years, direct numerical simulations have been developed for composites with periodic microstructures (Christman et al., 1989; Tvergaard, 1990; Bao et al., 1991), as well as for composites with more general types of microstructures (Brockenborough et al., 1991; Moulinec and Suquet, 1995). Again, no attempt will be made to review this work here, although some comparisons with numerical simulations will be given in the text. The numerical approach has the advantage of high accuracy and has provided very useful insight into the relevant physical mechanisms at work in the deformation and failure of nonlinear composites, albeit at the expense of intensive computations, particularly for composites with complex random microstructures. Furthermore, the numerical approach has the disadvantage that, in general, it does not result in explicit forms for the overall constitutive relations, making them difficult to implement in stress analyses at the macroscopic level. The present article will be concerned almost exclusively with some closely related methods that have been developed recently to estimate the effective behavior of nonlinear composites with random microstructures. The methods are based on suitable approximations in the context of rigorous variational principles for the effective behavior of the nonlinear composites, and as such have the advantage of mathematical rigor, delivering bounds that improve, often significantly, on the classical bounds of the Voigt-Reuss type. In addition, they make effective use of the various estimates available for linear composites, allowing the

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determination of corresponding estimates for nonlinear composites that are simple and which, in some cases, are even explicit. This explicit (or nearly so) character makes them extremely useful in the context of macroscopic simulations, allowing their straightforward implementation in standard finite-element codes (see Aravas et al., 1995). Next a brief outline of the paper is given. Section I1 deals with some preliminaries, including the definition of effective potentials, by means of the classical minimum energy principles, and their application to the determination of bounds of the Voigt-Reuss type for nonlinear composites. Section I11 gives a brief presentation of the variational principles of Talbot and Willis (1985). This pioneering work, which provided an extension of the Hashin-Shtrikman (1962a) variational principles for nonlinear composites, utilizing a linear homogeneous reference rnaterial, allowed the computation of the first improved bounds for nonlinear composites with random microstructures, incorporating statistical information of order two. Section IV presents new variational principles, originally developed by Ponte Castafieda (1991a) and Suquet (1993a), for isotropic and power-law composites, respectively, which allow the restatement of the effective energy function of a nonlinear composite in terms of that of an appropriately chosen linear heterogeneous reference material, where the distribution of moduli in the reference material is determined by the variational principle itself. Application of suitable approximations in the context of these variational principles then permits the determination of bounds for nonlinear composites, directly from corresponding bounds for linear comparison composites with the same microstructures as the nonlinear composites. In particular, these variational procedures allow the straightforward computation of the Talbot-Willis bounds, directly from the corresponding linear Hashin-Shtrikman bounds. But, more generally, they allow the determination of other types of bounds and estimates, which are not available from the Talbot-Willis procedure, again directly from their linear counterparts. These include, for example, higher-order bounds of the Beran (1965) type (Ponte Castafieda, 1992a). Section V starts with an asymptotic expansion, due to Suquet and Ponte Castaiieda (1993), which is exact to second order in the contrast of the properties of the phases and shows that the bounds and estimates obtained by the variational procedures of Section IV (and therefore those of Section 111) are only exact to first order in the contrast. This is unlike the Hashin-Shtrikman bounds and self-consistent estimates for linear composites, which are known to be exact to second order in the contrast. Motivated by this observation, a “second-order’’ procedure has been developed by Ponte Castafieda (1996a), which delivers estimates for nonlinear composites at finite contrast that are exact to second order. A selection of results for linear composites is presented in Section VI. Finally, Sec-

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tion VII provides some applications to sample nonlinear composites, including porous materials, rigidly reinforced composites, and two-phase power-law and ideally plastic composites. This section also includes comparisons with the classical incremental and secant models, showing that the new procedures can yield significant improvements over the classical methods, which are sometimes found to give predictions that violate rigorous bounds (Gilormini, 1995). Throughout the text, vectors and second-order tensors will be denoted by boldface letters, whereas fourth-order tensors will be denoted by barred letters. In this connection, the various types of products will be denoted by dots (e.g., u * v = u i ~ l(L , :~ ) i = j I L i j k h ~ k h 11, , :: Q = L i j k h Q i j k h ) .

11. Effective Behavior and Potentials A. INDIVIDUAL CONSTITUENTS 1. Local Potentials

The constitutive behavior of the individual constituents of the composite is assumed to be governed by a potential, or strain-energy function, w ( E ) , in such a way that the (infinitesimal) strain and stress fields, E and a,are related by

aw a = -( E ) .

a&

This constitutive relation corresponds to nonlinear elastic behavior within the context of small strains. However, by interpreting E and a as the Eulerian strain rate and Cauchy stress, respectively, the above constitutive relation can be used equally well to model$nite viscous deformations. Assuming that w is a convex function of E , the relation (2.1) can be inverted with the help of the Legendre transformation,

u ( a ) = sup(a : E - ?a(&)}, E

defining a convex stressenergy function u , such that &

=

au -

am

(a).

(2.3)

The functions w and u are dual potentials; they are related by the classical reciprocity relations depicted schematically in Figure 1 and discussed in more detail in Appendix A. (Note that u = w* in the notation of the Appendix.)

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Pedro Ponte Custafiedu and Pierre Suquet 3 00

”

0.0

0.04

0.02 E

FIG. 1. Schematic representation of the local potentials w ,u and of the secant and tangent moduli Es and Ec for the nonlinear constituents.

2. Isotropic Materials For isotropic materials, sufficiently general forms of w and u are given by W(E)

9

2

= - ks,

2

+

p(Eeq>,

(2.4)

and

where p and @ are dual convex potentials of a scalar variable. Also, a, and E, are the hydrostatic stress and strain, a, =

1

tr(u),

E,

=

1

tr(E),

a,, and E ~ ,are the Von Mises equivalent stress and equivalent strain,

177

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ad and Ed being the stress and strain deviators, ad = a - ffmI, ~d = E - E m I . Note that the influence of the third invariant on the local potentials w and u has been neglected. The resulting stress-strain relations can be written,

f f m = 3k&m,

ad

= 2Ks(Eeq)Ed9

where aeq

p’(Eeq)

p r, (Eeq )=--=-------3~eq

3~eq

-

aeq 3+’(0eq)’

The response of the phases is therefore assumed to be linear for purely hydrostatic loadings (characterized by a constant bulk modulus k ) and nonlinear in shear (characterized by a strain-dependent secant shear modulus p S ) .

EXAMPLES.Two examples of constitutive potentials are worth mentioning explicitly. The first example is concerned with the J2 deformation theory of plasticity. In particular, the Ramberg-Osgood model corresponds to the choice

where po is the initial elastic shear modulus, a0 is a reference stress, EO is a reference strain, and n 2 1 is the hardening exponent. The second example is given by high-temperature creep of metals, which is commonly characterized in terms of a power law. Neglecting elastic effects and assuming incompressibility, the dissipation and stress potentials, p and $, of the material take the forms

(2.7) and +(aeq)= -ffoso ( y + l , n + l ao

where EO and a0 denote a reference strain rate and stress, respectively, and where n and rn are power exponents related by rn = l / n . Two special cases of powerlaw materials are of special interest. The Newtonian viscous material corresponds to n = m = 1, where p = a 0 / 3 denotes the viscosity. The Von Mises rigid ideally plastic material corresponds to the limit rn + 0 (or n + a), where a0 denotes the flow stress in tension. In this last case, the stress potential becomes

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Pedro Ponte Castafieda and Pierre Suquet

unbounded for equivalent stresses exceeding 00, and it is useful to introduce the strength domain P , defined by the set

3. Crystalline Materials The general framework of potentials is also suitable to describe the creep of crystalline materials, which are, by definition, anisotropic materials. Consider a single crystal that undergoes creep on a set of K preferred crystallographic slip systems. These systems are characterized by the second-order tensors & k ) , k = 1 , . . . , K , defined by 1 P ( k ) = i ( n ( k )c3 m(k) m(k)c3 n(k)),

+

where n(k) and m(k) are the unit vectors normal to the slip plane and along the slip direction in the kth system, respectively, and c3 denotes the tensorial product of two vectors. Thus, when the crystal is subjected to an applied stress a, the resolved shear stress acting on the kth slip system is given by

The strain rate E in the crystal is the superposition of the strain rates on each slip system,

(2. I 1) where the shear strain rate y ( k ) on the kth system is assumed to depend on the applied stress only through the resolved shear stress r ( k ) ,in such a way that

(2.12) where the potentials + ( k ) are convex. A commonly used form for the slip potentials $ ( k ) is the pure power-law form

(2.13) where n(k) p 1 and (to)(k)are the creep exponent and reference stress of the kth slip system, respectively, and yo is a reference strain rate.

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It follows that the constitutive relations (2.1 1) and (2.12) may be expressed in terms of the convex potential for the crystal (2.14) which is such that (2.15) The limit as all the n ( k ) + 00 corresponds to a rigid ideally plastic crystal, with strength domain given by (2.16) 4. General Form of the Potentials Motivated by these two classes of materials, it is assumed more generally that the potential w can be put in the form

for some appropriately chosen function F , where fined as 1 2

E

is a fourth-order tensor de-

(2.18)

E = - E @ E ,

possessing the usual diagonal symmetry and positive-definite property of an elasticity tensor

The function F is therefore defined on the space of fourth-order tensors Q with diagonal symmetry. Then the constitutive relation (2.1) can alternatively be written as d

=L,(E)

E,

(2.20)

where

aF ae

L,(E)= -(6)

(2.21)

Pedro Ponte Castaiieda and Pierre Suquet

180

is the secant modulus tensor of the material,' which also has diagonal symmetry. Under the assumption (2.17), the dual potential u can be put in the form

(2.22) where G is a function of fourth-order tensors s, which is related to F by explicit relations given in Appendix A. In terms of the secant compliance tensor of the material, the constitutive relation (2.3) may be expressed in the form E

= h'&(@)

aG

:6,

Ms(Q)= (Q). as

(2.23)

EXAMPLES.The potentials of the two classes of materials described above (isotropic or crystalline materials) can be written in the forms (2.17) and (2.22), respectively. For isotropic materials note that

2 =4 R :: 3

Eeq

2 = -J 2 :: Q, am

cTq:

3

6,

= 3K :: Q,

where J and IK are two orthogonal projection tensors:

Here that

I is the identity in the space of symmetric fourth-order tensors. It follows

W(E)

=

9 ke; 2

-

+ 9(eeq)= 3kJ :: + f(-43 R :: E ) , 6

with

f ( x ) = q(,E),

(2.25)

and u(u)=

1 2 2k

- Dm

+

+((aeq)

=

1 3k J :: Q + g(3K :: Q), with g(x) = $I&).

-

'Note that the extension F of w is well defined by (2.17) on tensors in the form o = (1/2)e @ E , but it is not uniquely defined for more general fourth-order tensors. The secant tensor L, is therefore not uniquely defined, as already noted by Gilormini (1995) and Suquet (1997a), directly from (2.21).

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181

The corresponding secant tensors IL, in (2.21) and M, in (2.23) are obtained by straightforward derivations:

These secant tensors are isotropic. Similarly, for crystalline materials, note that

(2.28)

B. LOCALPROBLEM 1. Representative Volume Element Consider a representative volume element (r.v.e.) V of a composite where the size of the inhomogeneities is small compared to that of V . The composite is made up of N homogeneous phases V ( r ) ,r = 1, . . . , N , whose distribution is defined by characteristic functions x@). Let (.) and ( . ) ( r )denote spatial averages over V and V ( r ) respectively. , Then, for example,

where the notation

=

(x(')) are the volume fractions of the phases. The compact a(r)

= (u)(r),

g(r)

=p)(r)

(2.29)

Pedro Ponte Castaiieda and Pierre Suquet

182

will also be used to denote the average stress and strain in each phase. All phases are assumed to be homogeneous, with potentials w(I) and u @ ) ,and to be perfectly bonded at the interfaces. The potentials w and u depend on the position x inside V, in such a way that N

W(X,E ) =

N

C x ( ~ ) ( xw) ( ~ ) ( E ) ,

U(X, a) =

C

X ( ~ ) ( X )u " ' ( a ) .

(2.30)

r=l

r=l

2. Polycrystals A polycrystal will be regarded (in this study) as an aggregate of a large number of identical single crystals with different orientations. It can therefore be treated as a composite, where phase r is defined as the region occupied by all grains of a given orientation, relative to a reference crystal with potential given by (2.14). Letting Q(') denote the rotation tensor that defines the orientation of phase r , the corresponding potential u ( ~is) given by

where

3. Boundary Conditions and Averages The local stress and strain fields within V solve the so-called local problem consisting of the constitutive equations (2. l), the compatibility conditions satisfied by E , and the equilibrium equations satisfied by u:

aw u = -(e),

as

E

1 = - (Vu 2

+ Vu'),

div(u) = 0 in

V.

(2.31)

The problem is ill-posed in the absence of boundary conditions. Classically, two classes of boundary conditions can be considered on a V:

.

AfJine displacements

u(x) = E x on a V

Uniform traction

u(x) n(x) = Z n(x) on

.

-

(2.32)

a V.

(2.33)

The difference between the two types of boundary conditions has been discussed in detail by Suquet (1987). The mean strain and stress are the averages of the

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183

local strain and stress fields (with usual extensions in the case of voided or rigidly reinforced materials): (2.34)

The relation (2.34) is either a mere consequence of the boundary condition (2.32) (when (2.32) is adopted) or a definition. Similarly, (2.35) is either a consequence of the boundary condition (2.33) (when (2.33) is adopted) or a definition. In either case, the following result (Hill, 1963) holds:

LEMMA(Hill). Let a be a divergence-free stressjield and u a displacement jield, and assume that one of the boundary conditions (2.32) or (2.33) is satisjied. Then, C : E = (a : E ( u ) ) .

(2.36)

It is emphasized that E and c are not necessarily related by the constitutive relation. Hill’s lemma is useful in determining the effective or homogenized behavior of the composite, which is defined here as the relation beween E and X.

c. CLASSICAL VARIATIONAL PRINCIPLES AND EFFECTIVE POTENTIALS The solutions u and a of the local problem (2.31), (2.32) can be given the following two equivalent variational representations:

Minimum potential energy. u is the solution of the problem (2.37) where

.

K(E) = {v = E x on a V).

(2.38)

Pedro Ponte Castatieda and Pierre Suquet

184

Minimum complementary energy. u is the solution of the problem

where

S(Z) = {t,div(t) = 0 in V,

(t)= Z}.

(2.40)

Effective strain-energy potential. Noting that the infimum problem in (2.37) defines the average strain energy in the composite, the effective strain-energy potential Weff is defined as

w e f f ( ~=)

inf ( w ( E ( v ) ) ) ) .

(2.41)

VEK(E)

Then,

a weff

-(E) aE

=

(-a w ( E ( u ) ) :

E(;))

= (u :

aE

~(2)).

But au/aE satisfies

au aE

- =II.x

on

av.

It follows from Hill’s lemma that

a weff(E) = ( u ) : II = x, aE

(2.42)

which is the effective stress-strain relation for the composite.

Effective stress-energy potential. Similarly, the effective stress-energy potential Ueff is defined as

in terms of which,

The potentials Weff and Ueff are convex (as a consequence of the convexity of w and u). It can can be further shown (see Suquet, 1987; Willis, 1989a), starting from (A2) of Appendix A and using Hill’s lemma, that they are in fact (Legendre) dual functions such that

Weff(E)+ Ueff(x) = ( w ( E ) )+ ( u ( u ) ) = (U : E ) = x : E.

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185

The potentials (2.41) and (2.43) correspond to the boundary conditions (2.32). Adopting the boundary condition (2.33) would have led to different pairs of dual potentials, again given by the variational representations (2.41) and (2.43), but with different definitions of the set of admissible fields K(E) and S(X),namely,

K(E) = (v,

(E(v))

= E},

S(X) = {t,div(t) = Oin V,

t

. n = X VnonaV}.

However, under the additional assumption that the potentials w and u are strictly convex, the two types of boundary conditions are equivalent for the r.v.e., and are equivalent to the periodic boundary conditions used in the mathematical theory of homogenization (Bensoussan et al., 1978; Sanchez-Palencia, 1980). The limiting case of rigid ideally plastic materials for which the potentials are convex but not strictly convex requires special treatment, as in Bouchitte and Suquet (1991). Then, Weff is a positively homogeneous function of degree one in E, usually referred to as the plastic dissipation function, and it is useful to introduce the effective strength domain of the composite, defined as (Suquet, 1983,1987; de Buhan and Taliercio, 1991) Peff= { X such that there exists a(x) with ((r) = X, div((r(x)) = 0, and a(x) E P @ ) ,for x in phase r } .

(2.44)

Note that

Weff(E) =

{X : E},

SUP

x E peff and that

U " f f ( X )=

o +cc

i f X E peff, otherwise.

The boundary of Peffdefines the extremal surjfiuce of the composite (Hill, 1967).It can be characterized by a yield function F e f fsuch , that F e f f ( X 5 ) 0 if X E P e f f . The extremal surface depends on the flow stresses, the volume fractions and the arrangement of the individual phases. For a discussion of the general properties of P e f f ,refer to Suquet (1987).

D. CLASSICAL BOUNDS OF THE VOIGT AND REUSSTYPE The minimum energy principles (2.37) and (2.39) may be used to obtain rigorous bounds for the effective potentials Weff and Ueff. This was recognized long ago by Bishop and Hill (1951a,b) for rigid ideally plastic polycrystals and by

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Pedro Ponte Custuiiedu and Pierre Suquet

Drucker (1966) for composites with elastic ideally plastic phases. Use of uniform trial fields in the variational principles (2.37) and (2.39) leads to the rigorous bounds of the Voigt (1889) and Reuss (1929) type,

and

c N

U"ff(Z;>5 ( u ) ( Z ) =

c(r)u(r)(Z),

(2.46)

r=l

or, equivalently,

where an upper * denotes the convex dual function. In the context of polycrystals, these bounds are often referred to as the Taylor (1938) and Sachs (1928) bounds, respectively.

EXAMPLE.The Reuss and Voigt bounds for incompressible, isotropic, power-law constituents read

where

When m = 0 (corresponding to rigid-plastic materials), the Reuss bound simplifies to

a ; =

inf

r = l , .... N

air).

As already observed, the Voigt and Reuss bounds incorporate only limited microstructural information, in the form of the volume fractions of the constituent phases. Because of this, they are not very useful in general, particularly when the contrast between the phases is large. In fact, they are known to be exact only to first order in the contrast (see Section V.A.l). The following sections are concerned with variational methods that have been developed to obtain sharper bounds incorporating additional microstructural information-beyond the phase

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187

volume fractions-in the form of two- and higher-point statistics for the distribution of the phases in the composite.

111. Variational Methods Based on a Homogeneous Reference Medium Hashin and Shtrikman (1962a, b, 1963) introduced a variational procedure to estimate the effective modulus tensor of elastic composites with statistically isotropic microstructures. The Hashin-Shtrikman (HS) variational principles consist in an alternative representation of the effective potentials for the composite in terms of suitably chosen polarization fields relative to a homogeneous reference material with modulus tensor I,(”).Making use of the Green’s function for the elasticity problem associated with the linear homogeneous reference material, and using the hypothesis of statistical isotropy, Hashin and Shtrikman were able to obtain rigorous upper and lower bounds for the effective modulus tensor Leff of the composite, by respectively choosing I,(o)to be equal to the “maximum” and “minimum” modulus tensors of the phases I,(“).A generalization of the HS variational principles, which is suitable for nonlinear composites, was given by Talbot and Willis (1985), following Willis (1983). This extension of the HS variational principles, which can be used to obtain improved bounds (depending on up to two-point statistical information) for nonlinear composites, is discussed next. A. THEVARIATIONAL PRINCIPLES OF TALBOTAND W I L L I S Define w ( ” ) to be the potential function of a linear homogeneous reference material with uniform modulus tensor I,(’), such that

and assume that the “difference” potential (w- w(O)) is a concave function, so that the concave polar of this difference potential is defined as (see Appendix A)

*

It then follows from the fact that the difference potential is concave that

w(x, e ) - w(O)(e) = i n f { t : e - ( w - w(’))*(x, t)}, *A subscript * identifies a concave polar, whereas a superscript * denotes a convex polar.

(3.2)

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Pedro Ponte Castaiieda and Pierre Suquet

which is nothing more than the statement that w - w(O) = (w - w(’))**. Therefore, substituting (3.2) for w in expression (2.41) for the effective potential Weff, and interchanging the order of the infima over E and t,one arrives at

Taking the “polarization field” t in the “inner” minimum problem as given, it follows that the minimizing displacement field u solves the boundary value problem:

div(IL(’) : E ( u ) )= -div(t),

u E IC(E).

(3.4)

Then, making use of the Green’s function G(’) associated with the system (3.4) in the domain V , it is possible to obtain the following expressions for the strain tensor:

where E is the average strain over V , and where r ( O ) is the linear integral operator defined by r(0)

*t=

1”

r(O)(x,x’) : [t(X’)

-

(t)] dV’,

(3.6)

whose kernel is related to G(O)via

In this last relation, the parentheses enclosing the subscripts denote symmetric parts, and in (3.6), the term (t)has been added to “regularize” the integral (see Willis, 1981). was essential in Note that the concavity of the difference potential (w attaining the equality in (3.3). If (w - w ( ~ is ) )convex, it is possible to obtain a corresponding result where the infimum over the polarization fields is replaced by a supremum, and where the concave polar is replaced by a convex polar (see Talbot and Willis, 1985). Typically, however, (w - w(O)) is neither concave nor convex-for example, for a power-law material with potential (2.7). In this case, the equality in (3.3) must be replaced by an inequality (either 5 or 2 , depending on whether (w - w(’)) has weaker-than-afine or stronger-than-afine growth at infinity, respectively). A dual variational principle may be obtained (see Talbot and Willis, 1985, for details), starting from the definition (2.43) of the stress potential Ueff, and

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189

assuming that the function ( u - u(O)) is convex, where u(O) is the stress potential of the linear reference material, dual to (3.1). Then, using the fact that u - u(O) = ( u - uto))**, it can be shown that

where 9 now plays the role of a strain polarization. For a given polarization distribution, the inner problem can once again be solved formally by means of the relevant Green's functions in terms of 6. For brevity, these details will be omitted here (see Willis, 1981).

B. BOUNDSVIA PIECEWISE CONSTANT POLARIZATIONS Of course, the polarization field in (3.3) is difficult to determine exactly. Because of this, it is helpful to introduce the approximation of piecewise constant polarization: N r=l

Recalling that denote the volume fractions of the phases, and making = (x use of the fact that the average of a tensor field T over phase r is given by (T)@)= ((x(~)/&))T), it follows from (3.5) and (3.6) that the average E @ ) = ( E ) ( ' ) over phase r of the strain tensor E is given by .

N

where

( r , s = 1, . . . , N ) are tensors that depend only on the microstructure of the composite and on L(O).Furthermore, they are known (Kohn and Milton, 1986) to be symmetric in the superscripts r and s, and are not all independent, satisfying the relations N

N

r=l

s=l

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Pedro Ponte Castaiieda and Pierre Suquet

Similarly, using integrations by parts, together with the system (3.4) and relation (3.3, it can readily be shown that ( W @ ) ( ~ ( U ) ) )=

1 2

w(")(E)- -(t : ( E ( u )- E)),

(3.11)

but since .

N

N

it follows, from (3.3), that N

_ -1

2

N

N 7; t(r) :r ( r s ) :

t(s)

(3.13)

r=I \ = 1

where (t)= C Nr Z~ l ( ' ) tThen, ( ~ )optimizing . over the polarizations 1, . . . , N ) , one obtains the conditions (for the t('))

t(')

(r =

( r = 1 , . ..,A'), (3.14)

so that, from (2.42), (3.13), and (3.14), one finally gets, replacing the inequality in (3.13) by an equality, the approximate stress-strain relation

C = L'O' : E + (t), where the t(') are obtained from relations (3.14). The upper bound (3.13) for Weff(E) was given by Ponte Castaiieda and Willis (1988), following an analogous development by Willis (1986) in the context of nonlinear dielectric composites. An alternative form of the result (Willis, 1991) may be obtained by noting, through the use of (3.9), that the optimality conditions (3.14) can be rewritten in the form

which can be inverted (see Appendix A) to give (3.15)

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191

so that the (Legendre) dual variables E(') satisfy the conditions

( r = 1, . . . , N ) .

(3.16)

In terms of these variables, the bound (3.13) may be rewritten in the form

(3.17) where the t(') are given in terms of the E ( r ) by expression (3.15). It is possible to obtain nontrivial lower bounds for the effective stress potential U e f fby an analogous development, starting from (3.7), and taking the polarization field 7 to be piecewise constant. The details are omitted here (see, for example, Willis, 1991) C. DISCUSSION The expression (3.17) provides an upper bound for Weff, for any choice of w(O);the best bound is obtained by minimizing over IL(O). Note that the bound is finite only if (w- w(O)) has weaker-than-afJine growth at infinity, which would be the case, for example, for the class of power-law materials defined by (2.7). The minimization with respect to IL(O) is complicated by the fact that the computation of (w(') - w(O))** can be difficult. Ponte Castafieda and Willis (1988) and Willis (1989a, b) obtained nonoptimal bounds by restricting their attention to values of IL(O) for which (w(')- w(O))** = ( ~ ( ~ w(O)). 1 Later, Willis (1991, 1992) showed that improved bounds, agreeing with those of the variational procedure of Ponte Castafieda (1991a), could be obtained by eliminating this unnecessary restriction. For the special case of composites with linear constitutive behavior, it is possible to choose L(O),in two different ways, such that ( ~ ( ' 1 - w(O)) is either concave or convex, thus allowing, from (3.13), the construction of both upper and lower bounds for the effective modulus tensor of the composite (i.e., the classical Hashin-Shtrikman bounds). By contrast, for nonlinear composites, only a onesided bound is available for Weff by the method outlined above, the direction of which depends on the growth conditions on w.In this connection, it is emphasized that the upper bound (3.17) obtained from (3.3) for Weff and the corresponding lower bound obtained from (3.7) for Ueff can be shown to be exactly equivalent

192

Pedro Ponte CastaAeda and Pierre Suquet

(see Talbot and Willis, 1985). However, Talbot and Willis (1994,1995) have succeeded in obtaining improved bounds in the “other” direction, by the introduction of suitably chosen nonlinear reference materials. The classical upper bounds can be recovered formally from the above TalbotWillis variational principles in the limits as the reference modulus tensor L(O) tends to 0 or 00. Thus, for example, it is easy to see that letting tend to 00 in (3.7) and taking the polarization to be uniform leads to a trivial problem for c,which when solved leads to the Voigt upper bound (2.45). Similarly, the Reuss bound can be obtained directly from (3.7), with L(O)tending to 0. The estimate for Weff provided by (3.13) and (3.14), or (3.16) and (3.17), after optimizing over the choice of I,(’), is explicit except for the microstructural parameters r(rs), which must be determined for specific classes of microstructures. Explicit expressions for these microstructural parameters have been determined by Willis (1977, 1978) and Ponte Castaiieda and Willis (1995) for various classes of random microstructures with prescribed two-point correlation functions for the distribution of the phases, including microstructures of both the “particulate” and “granular” types (see Section VI). By using these results, bounds have been determined for special types of nonlinear composites and polycrystals, for example, by Ponte Castaiieda and Willis (1988), Willis (1989a, b, 1991), Talbot and Willis (1991), and Dendievel et al. (1991).

IV. Variational Methods Based on a Linear Comparison Composite Variational methods for obtaining improved bounds and estimates for the effective behavior of nonlinear composites, making use of the effective modulus tensor of suitably chosen linear-elastic comparison composites, were introduced by Ponte Castaiieda (1991a) for composites with isotropic phases and by Suquet (1993a) for composites with power-law constituents. In addition, a hybrid of the Talbot-Willis and Ponte Castaiieda procedures, using a linear thermoelastic comparison composite, was proposed by Talbot and Willis (1992). Finally, a procedure, also using a linear-elastic comparison composite, specifically designed for rigid ideally plastic composites, was developed by Olson (1994). Although all of these procedures are formally different (and were given different derivations by the various authors), they can in fact be shown to be equivalent under appropriate hypotheses on the local potentials. A distinct advantage of these variational procedures involving linear comparison composites, however, is that they can not only easily recover the nonlinear Hashin-Shtrikman bounds of the Talbot-Willis procedure, directly from the corresponding linear Hashin-Shtrikman bounds, but,

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in addition, they are able to deliver higher-order nonlinear bounds, such as Berantype bounds, as well as other types of estimates that may not be available from the Talbot-Willis procedure. In this section, brief accounts will be given of the variational principles of Ponte Castaiieda (1992a) and Suquet (1993a) for composites with isotropic and powerlaw phases, respectively. This will be followed by a generalization, due to Suquet (1997b), of the variational procedure of Ponte Castaiieda, which is developed for nonlinear composites with anisotropic constituents. It will be shown that this generalization is capable of delivering as special cases, not only the variational principles of Ponte Castaiieda (1992a) and Suquet (1993a) for composites with isotropic constituents, but also those of deBotton and Ponte Castaiieda (1995) for polycrystalline aggregates of anisotropic single-crystal grains. The variational principles will then be used to generate a general class of bounds for nonlinear composites, by making suitable approximations in the set of admissible linear comparison composites. Finally, various interpretations of the variational procedures will be developed, including a recent interpretation of the resulting bounds in terms of secant moduli, due to Suquet (1995).

A. NONLINEAR COMPOSITES W I T H ISOTROPIC PHASES 1. Variational Principles for Materials with a Certain Concavity Hypothesis Consistent with relations (2.4), (2.25), and (2.30), the potential w of a nonlinear composite with isotropic phases may be written in the form

where N

N

k(X) =

X(r)(X)k(r), r=l

f ( X , E$)

=

X(r)(X)f(r)(E:q),

(4.1)

r=l

and where the functions f " ) , characterizing the deviatoric behavior of the material, are defined by the relations f ( ' ) ( p ) = v ( ' ) ( E ~ ~for ) p = E : ~ . It will be assumed that the functions f ( ' ) satisfy the following.

Concavity hypothesis. The f ( ' ) are assumed to be concave functions of p , such that f ( ' ) ( p ) = -co for p < 0, f ( ' ) ( O ) = 0, and f ( ' ) -+ 00 as p -+ 00.

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Pedro Ponte Castaiieda and Pierre Suquet

By definition (see Appendix A), the concave dual function of f

( r ) is

given by

where the last equality follows from the fact that - f ( ' ) ( p ) = 00 for p < 0. Note that f:' is a concave, nonpositive function, such that f *( r )(4) = -00 for q 5 0. It follows from the concavity hypothesis that f::' = f ' " ) , and therefore that

Note that the above hypotheses on f ( r ) are consistent with weaker-than-quadratic growth for w@)at infinity, in agreement with the physical requirements for plasticity and creep. For example, for the power-law material (2.7), ~ p ( ~ ) (0 5 m 5 l), so that f ( ' ) p ( ' + m ) / 2is a concave function in the interval [0, 001, even if ~ p (is~itself ) convex. Next, introduce a linear comparison composite with potential wo,such that

-

- EL:^

Then, using the identity (4.2) with q = ip.0, it follows that the potential of the nonlinear composite w may be given the exact representation (4.4) where (4.5) Note that (4.6)

so that (4.7)

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195

Now, substituting expression (4.4) for the local potential w into expression (2.41) for the effective potential Weff, it follows that

from which it is concluded, by interchanging the order of the infima over PO,that

E

and

where V ( p 0 ) = (v(x, po(x))) and Wit'" denotes the effective potential of the linear comparison composite: (4.9) This variational representation for the effective potential of a nonlinear composite in terms of the potential of an appropriately chosen "linear comparison composite" is due to Ponte Castaiieda (1992a). It is emphasized that, under the concavity hypothesis on the f'') functions, the variational representation (4.8) and the classical representation (2.41) are exactly equivalent. Thus, under these circumstances, the variational statement (4.8) can be given the following interpretation: the effective potential Weff of the nonlinear composite solid, as defined by (2.41), can be alternatively determined from the effective potential Wtff of a linear heterogeneous comparison solid, with bulk modulus k(x) and with shear modulus po(x), the precise variation of which is determined as the solution of the variational problem (4.8). Note that although the bulk modulus of the linear comparison composite is constant within each phase (the same as for the nonlinear material), the corresponding shear modulus will be nonuniformly distributed within each phase. Because of this, the variational principle (4.8) is, in general, at least as difficult to implement as the original classical variational principle (2.41). However, the variational principle (4.8) has the advantage that it allows useful approximations that are not accessible directly from the classical variational principles. One possible approximation in (4.8) is to replace the minimum over the set of arbitrarily variable, nonnegative shear moduli by the smaller set of piecewise constant, nonnegative moduli. The application of this approximation for the determination of bounds and other estimates for the effective behavior of nonlinear composites will be considered in a later subsection. This type of approximation was introduced, directly, by Ponte Castaiieda (1991a). It is also possible to start from the complementary energy representation (2.43) for Ueff to obtain a corresponding dual version of the variational statement (4.8).

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Pedro Ponte Custufiedu and Pierre Suquet

To accomplish this, on account of (4.4), note that

where

is the stress potential of the linear comparison composite. From (4.7), also note that E

[

: u - u(x, u)}- wo(x, E ) )

= sup sup { E : a U

-

wo(x, E ) } - u(x, a)]

E

= sup {uo(x, u) - u(x, (7)).

(4.1 1)

U

Then, substituting expression (4.10) for u into expression (2.43) for U e f f ,and interchanging the infimum over u and the supremum over po, which is allowed by an appropriate version of the saddle point theorem, it is concluded that

Ueff(z) = sup

{u;"ff(z) - V(po)},

(4.12)

/I.O(X)>O

where it is recalled that V ( p o )= (v(x, po(x))) and where

is the effective stress potential of the linear comparison composite. Finally, it is emphasized that the two dual versions (4.8) and (4.12) are exactly equivalent (i.e., there is no duality gap). To see this note that

Ueff(C) =

SUP

{E : C - Weff(E)}

E

=

sup wn(x)>o

[ sup {E : C - Wiff(E)} - V ( p 0 )) E

(4.14)

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197

2. Variational Principles for Power-Law Materials Special variational principles for pure power-law materials, also using linear comparison composites, have been proposed by Suquet (1993a). The composites under consideration here are made up of power-law materials with strain-energy functions (2.7) with the same exponent n and the same reference strain EO, but with different flow stresses q.For such composites, the variational characterization of the relevant effective strain potentials specializes to

Next, introducing a linear composite, which is incompressible and isotropic with an arbitrary nonnegative shear modulus po(x), at point x, and which occupies the same volume element V as the given nonlinear composite, it is possible to write that

Then, using Holder's inequality, one can show (see Suquet, 1993a, 1997a) that

for all positive fields po(x). The above inequality is in fact an equality when po(x) = ~ a o ( x ) ~ & - ~ ( v (and x ) ) therefore

The infimum of (aos&+'(v)) over all admissible fields v can be computed from (4.15) by interchanging the order of the infima, and one obtains, finally,

Note that when the constituents are power-law with the same exponent, the en) the effective energy Weff are positively homogeneous of ergy functions w ( ~ and degree rn 1 with respect to E and E, respectively.Therefore (4.16)compares two

+

Pedro Ponte Castaiieda and Pierre Suquet

198

functions, Weff and (W~"f)(mt1)/2, which have the same degree of homogeneity. The variational principle (4.16) can be given a dual and equivalent form,

B. NONLINEAR COMPOSITES WITH ANISOTROPIC PHASES 1. Generalized Variational Principles Assume that the functions F ( r j , defining the strain potentials w ( ~through ) relations of the type (2.17), are concave on the space of positive, symmetric fourthorder tensors e, i.e., they satisfy the following inequality:

F(')(te1

+ (1 - t ) Q ) 2 tF(')(e1) + (1 - t)F(')(e*)

ve1, e2,

0 5 t 5 1.

(4.18)

Note that this hypothesis implies weaker-than-quadratic growth for the potentials w ( ~on) the strain E , when e is set equal to E , as defined by (2.18). The concave dual function of F(') is defined (see Appendix A) as

F.$)(L) = inf(IL :: Q - F ( ' ) ( Q ) ) e

Note that F,'"

is concave, and that F(')(Q) = inf(L :: e - F : ~ ) ( I L ) ) , IL

from which it follows that

L=

~

aFi.1

a F(') (Q)

is the inverse of

ae

8

=

~

aL

(IL),

(4.19)

these relations being understood in the sense of subdifferentials when the functions F and F* are not differentiable. Next, define F ( x , e) as N

r=l

Recalling the definition (2.18) of F ( X , E < v ( x > ) )= inf

6 , at

every point x in V , one has that

{ I L ~ ( X ) ::

E ( v ( x ) )- F,(x,ILO(X))}.

M X )

The infimum is in fact restricted to stiffness tensors Lo(x) for which the function F* is finite. This restriction implies that ILo(x) is positive definite (see Ap-

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199

pendix A). It follows, from the definition (2.41) of the effective potential Weff, that

Then, introducing a linear comparison composite with local potential,

1 wo(x, e(v)) = ILO :: E ( V ) = - E ( V ) : ILo(x) : E ( V ) , 2

(4.21)

and interchanging the infima in (4.20), one arrives at the following exact variational representation for the effective potential, namely,

where Woff is the effective potential (4.9) of the linear comparison composite defined by the local potential (4.21), and V(IL0) = (u(x,ILo(x))),with

u(x, ILo(x)) = -F*(x,ILo(x)) = sup [F(x, Q) - ILo(x) :: Q].

(4.23)

Q

Note that the optimality condition in (4.23) is precisely the definition of the secant modulus IL, (cf. relation (2.21)). The relation (4.22) expresses the nonlinear effective properties of the composite (through its potential Weff) in terms of two functions:

Wgff is the elastic energy of ajctitious linear heterogeneous solid (called the linear comparison composite) made up of phases with stiffness ILo(x) at point x; the linear comparison solid is chosen from among all possible comparison composites by solving the optimization problem (4.22).

u(x, .), the role of which is to measure the difference between the nonquadratic potential w (x,.) and the quadratic energy of the linear comparison solid. The relation (4.22) is exact and strictly equivalent to the variational characterization of Weff given in (2.41). It also provides an interpretation of the strain field in the actual nonlinear composite, which is the strain field in the optimal linear comparison solid. However, solving the optimization problem (4.22) exactly is a formidable task, and is often as difficult to achieve as the initial variational problem involved in the definition of Weff.The function V can be explicitly expressed in terms of the dual functions F:), which at least for simple potentials w ( ~are ) easy to evaluate. The difficulty lies in the precise determination of the energy Wtff

Pedro Ponte Custufieda and Pierre Suquet

200

for a linear comparison solid consisting of infinitely many different phases. Very little is known about this problem, and progress in the understanding of N-phase linear composites (with N 1 3) would certainly result in a better understanding of nonlinear composites, as clearly reflected by (4.22). For this reason, except for very specific situations, e.g., laminates (deBotton and Ponte Castaiieda, 1992; Suquet, 1993a), the optimal solution of (4.22) is not known, and only suboptimal solutions are determined. By “suboptimal” it is meant that the class of linear comparison composites considered must be restricted for explicit results to be obtained. One possible reduction of the problem consists in, instead of minimizing over the whole set of arbitrary variable L(x), considering only the smaller set of piecewise constant positive stiffness tensors. This is carried out in Section 1V.C. However, the general principle given can also be used in cases where the distribution of stiffness tensors does not coincide with the distribution of the phases. This was illustrated, for instance, in Suquet (1993a), where a well-known result by Drucker (1966) was recovered by choosing appropriately the linear comparison composite. This result is that the shear strength of a composite where a shear plane can be passed through the weakest phase is the strength in shear of the weakest phase. The appropriate choice of the linear comparison composite was a compliant band around the shear plane surrounded by a stiff matrix. Another example was given in Ponte Castaiieda (1992b), where exact results were derived for sequentially laminated composites, making use of nonuniform choices for the comparison moduli in the matrix phase of the laminates. A variational representation for the stress potential Ueff that is equivalent to (4.22) for Weff may be obtained by following an argument exactly similar to that followed in (4.14), to obtain the result that

U“ff(X) = sup {U;”f(X)- V(ILO)}.

(4.24)

Lo>O

Finally, note that the functions G(‘) in the alternative writing (2.22) of the stress potential are convex functions of the fourth-order tensor s (see Appendix A), such that U ( X , t)=

G(R) = SUP (Mo(x) :: R - G*(Mo(x))}, Mo

1

R = - t @ t. 2

It is then possible, directly from the variational representation (2.41) for Ueff and using the minimax theorem, to obtain the result that

Ueff(X) = SUP {Uiff(X)- (G*(Mo))}, Mo

(4.25)

20 1

Nonlinear Composites where

(4.26) Again the effective potential Ue' governing the nonlinear properties of the composite is expressed in terms of the quadratic stress potential of a suitably optimized linear comparison composite. 2. Special Variational Principles

i. Isotropic constituents.

When the individual constituents are isotropic with strain potentials of the type (2.4), the function F , as has already been shown, has the form

F ( Q )= 3kJ :: Q

F ( e ) = -co

+ f ( 43 JK :: e ) -

when JK :: Q ? 0,

otherwise,

where k and f are phase dependent. Then, the dual function F, is given by (the details of the calculation are given in Appendix A) F* (Lo) = f*

3

(5 PO),

when Lo admits the decomposition

Lo = 3kJ

+ 2p&,

with

PO > 0,

(4.27)

or -cc otherwise. The infimum over LOin (4.22) can therefore be restricted to isotropic tensors LOin the form (4.27), without loss of generality, and the variational statement (4.24) for Weff reduces to the simplified form (4.8) of Ponte Castaiieda (1992a). Similarly, both forms of the the dual variational principle (4.24) and (4.25) can be shown to reduce to (4.12) for composites with isotropic constituents.

ii. Polycrystals. When the individual constituents are single crystals (refer to Sections II.A.3, II.A.4 and II.B.2), the functions G(') have the form K k= 1

where it is recalled that

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Pedro Ponte Castaiieda and Pierre Suquet

It can then be shown (see Appendix A) that

when the compliance tensor M(r)has the form (4.28) and +cc otherwise. The supremum in (4.25) can therefore be restricted to compliance tensors Mcr) having the decomposition (4.28). Thus the corresponding local stress potential for the linear comparison polycrystal is given by

It follows that the final form of (4.25) for polycrystals is

U"ff(X) =

{ U,"ff(X) - V ( a { ; i ) } .

sup

(4.30)

cy;~))(x)>o

r = l , ..., N , k = l , ..., K

where Uiff is the effective potential associated with the linear comparison polycrystal with grain potentials (4.29), and where

r=l k=l

This is the variational principle of deBotton and Ponte Castaiieda (1995) for nonlinear polycrystals, which was originally derived by assuming convexity of the functions g,(Li.Note that the functions a,(;;(x),k = 1, . . . , K , are defined over the region in space occupied by the crystals with fixed orientation r. iii. Power-law constituents. When the individual constituents are (incompressible) power-law materials with the same exponent m (recall that 0 5 m 5 l), the composite itself is a power-law materiaL3 In other words, the local potentials and the effective potential are positively homogeneous of degree rn 1:

+

W ( r ) ( h E= ) h ~ + l ~( (E ') ,)

Weff(hE) = Am+' Weff(E)

+

Vh >_ 0.

3T0 prove that Weff is positively homogeneous of degree m 1, it suffices to note that the solution of the local problem (2.31), (2.32) corresponding to an overall strain hE is Xu, where u is the displacement field for an overall strain E.

Nonlinear Composites

203

The function F defining the strain potential w is itself a power-law function of degree ( m 1)/2, and its dual function is a power-law function of degree (m l)/(m - 1). Next, letting Lo(x) = tf,o(x), for arbitrary positive t , and noting that W;" and V = - ( F * ) are homogeneous of degrees 1 and ( m l ) / ( m - 1) in Lo, respectively, it follows from the variational statement (4.22) that

+

+

+

+

Weff(E) = jnf inf tW;ff(E) t ( m + l ) / ( m - ' ) V ( & ) ) / . Lo>Ot>O

where W;" is the same as Wtff in (4.22), with Lo replaced by t o . Then the minimum over t can be easily evaluated to obtain another exact representation of Weff (note that V = - ( F * ) is positive; see Appendix A):

where the hats have been dropped for simplicity. A similar exact representation for Ueff can be given (the details are omitted for brevity):

iii.1 Isotropic power-law constituents. As already mentioned, when the individual constituents are isotropic, it is sufficient to consider isotropic linear comparison composites. For materials governed by the potential (2.7), the functions f , f * , g and g* take the forms

and

The variational principles (4.3 1) and (4.32) then reduce to the variational principles (4.16) and (4.17) of Suquet (1993a), which were originally derived by means of Holder's inequality, as seen previously.

Pedro Ponte CastaAeda and Pierre Suquet

204

iii.2 Power-law polycrystals. The corresponding formula for power-law polycrystals with slip-system potentials (2.13) is obtained similarly, directly from (4.32). The result is

r=l,,.,,N, k = 1 , ..., K

iv. Rigid ideally plastic constituents. In the ideally plastic limit ( m + 0), the variational representations (4.3 1) and (4.32) respectively reduce to

and

U"ff(Z) =

o

if U;"'(X) i v ( L ~ n) o +co otherwise.

MY^,'

> 0,

(4.35)

The right-hand side of (4.34) is, for every LO, a positively homogeneous function of degree one with respect to E. It is the dissipation function associated with the convex set P(Lo) = { X such that Utff(X) 5 V(Lo)}. Taking the infimum over Lo in (4.34) is equivalent to taking the intersection between the sets P(L0): peff =

n

P(L~).

LpO

This last expression can be useful when one is looking for P e f f rather , than Weff, and any choice of LOgives an estimate of Peff from the outside. Note that all of the sets P(L0) are defined by a quadratic equation in stress space, but that their intersection can have an arbitrary shape. In particular, it can have vertices, as illustrated by the case of composites reinforced by aligned fibers considered in Section VII. Similarly, simplified forms of the above results may be obtained for rigid ideally plastic composites with isotropic constituents, as well as for rigid ideally plastic polycrystals.

Nonlinear Composites

205

c. BOUNDSVIA PIECEWISE CONSTANT MODULI 1. Nonlinear Composites with Anisotropic Phases

i. Strain potential Weff. As mentioned in Section IV.B, the exact representation for the effective potential Weff requires the determination of the effective potential of a linear composite with infinitely many different phases, which is an extremely difficult problem. One possible simplification of the problem is to restrict the optimization over Lo(x)to the set of piecewise constant moduli,

c N

Lo(@ =

(r) (r)

x

(x),

(4.36)

r=l

ILt)

where the tensors are taken to be constant. The resulting optimization problem no longer provides an exact representation of the effective potential We' but, instead, gives an upper bound for this potential

where Woff is now the effective potential (4.9) of a linear composite with the same microstructure as the nonlinear composite. In this linear comparison composite, the domains V(') are occupied by linear phases with stiffness Lt).This comparison composite has an overall stiffness Liff,so that 1 Wiff(E) = - E : Lgff : E, 2

(4.38)

and the functions d r )are defined by (4.39) The bound (4.37) is a generalization for composites with anisotropic phases of a correspondingbound for composites with isotropic phases that was introduced by Ponte Castaiieda (199 la). An alternative generalization for anisotropic composites was given by Talbot and Willis (1992), which amounted essentially to (4.37), where the functions were defined by relations of the type (4.6) with generally anisotropic wt).It should be noted that these authors obtained their bounds as a special case of a more general result that does not require the hypothesis of concavity of the F ( r ) . Three important observations can be drawn from the definition (4.37) for the potential eff. First, the form (4.37) of the bound eff (E) involves an optimiza-

w

w

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Pedro Ponte Custuiiedu and Pierre Suquet

tion problem for the positive definite tensors LIT', which is (usually) solved by the set of stationarity conditions (4.40) Using these stationarity conditions, it follows by derivation of (4.37) with respect to E that the stress-strain relation for the linear comparison composite may be written in the form

aw eff aE

(E) = Lgff( L : ) )

: E,

(4.41)

where the )!L are now the modulus tensors satisfying the optimality relations (4.40). Thus the relation (4.41) is an approximation to the exact stress-strain relations of the nonlinear composite. Note that, in spite of its appearance, this effective stress-strain relation is nonlinear, because of the nonlinear dependence of the optimal Lr)on the average strain E. This observation is due to deBotton and Ponte Castaiieda (1992, 1993) in the context of nonlinear composites with isotropic phases. Second, note that the expression (4.38) for Woff can be rewritten in the form N

where

z(r)is the the second moment of the strain in phase r , defined as -

E

1 '"(v) = ( E ( v ) ) ( r ) = - ( E ( V ) 2

@ E (IV ) ) V

(4.42)

It then results, from (4.37) and (4.39), that N

.

r = l , ...,N

N

-

N

In the last equality, 2 = 2 ("(u), where u is the displacement field in the linear comparison composite. The form (4.44) of the upper bound (4.37) can be derived directly from the concavity of F ( r ) ,as originally done in Suquet (1995, 1997a) for composites with isotropic phases.

Nonlinear Composites

207

Third, the optimality conditions for Lt)in (4.43) read

Then, recalling the equivalence relation (4.19) and the definition (4.39) of the u ( ~ ) functions, the optimality conditions (4.40) for the Lf)can be rewritten in the form

The last equality in (4.45) expressing the second-order moment of the strain in each phase of the linear comparison composite in terms of its effective stiffness LEff has been obtained here as a consequence of the optimality conditions (4.40). It is interesting that one can directly obtain (see Appendix B) the expression of the second-ordermoment of the strain (or stress) in each phase in a linear composite by derivation of the effective strain energy of the composite (Suquet, 1995, 1997a):

These relations apply in particular to the linear comparison composite.

ii. Stress potential Ueff. A bound that is equivalent to (4.37) can be obtained by considering the stress potential Ueff and its variational representation (4.25). Thus, restricting the optimization in (4.25) to piecewise constant compliances ~ , f ) ,one obtains

where U;ff is now the effective stress potential associated with the same linear comparison composite as for Wlff above-one with the same microstructure as the nonlinear composite, but where the domains V(') are occupied by linear phases with compliances M". From this result, it follows that

a ueff(X)= M;ff(Mp) : x, ax

Ex-

(4.48)

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Pedro Ponte Castaieda and Pierre Suquet

where the optimal M t ) are determinedby conditions analogous to those of (4.40). It also follows from (4.47) that N

N

z(r)

where = ( m ) @ ) = i(cr @ cr)@)is the second moment of the stress field in phase r of the linear comparison composite.The compliancesM (l ' of the comparison material are determined as the solution of the optimization problem (4.47), which can alternatively be written in terms of the solution of the following nonlinear problem for the variables ( r ) :

2. Nonlinear Composites with Isotropic Phases When the nonlinear constituents are isotropic, it has already been shown that the constituents of the linear comparison composite can be chosen to be isotropic. The bulk modulus is equal to the bulk modulus k(') of the nonlinear constituent, and the only modulus that has to be determined is the shear modulus &) in each phase. Thus the bound (4.47) reduces to

(4.51) where the functions are defined by the relations (4.6). The upper bound (4.51) for Weff,as well as the analogous lower bound,

r = l , ...,N

(4.52) was originally proposed by Ponte Castaiieda (1991a). From the associated optimality conditions, it follows that the effective stress-strain relations for the composite may be approximated by (deBotton and Ponte Castaiieda, 1992, 1993) C = LEff(pt)): E,

E = MEff(pt)): C.

(4.53)

Nonlinear Composites

209

Similarly, the nonlinear tensorial optimality conditions (4.45) can be shown to reduce to N scalar nonlinear equations:

(4.54)

a&)

= ( ( E : ~ ) ( ‘ ) ) ’ / ~ . These nonlinear equations can be given, alternaNote that tively, in terms of the stressxnergy potential,

(4.55)

Again, note that F&)= ( ( D : ~ ) ( ~ ) ) ’The / ~ . bounds for Weff and Ueff can then be rewritten:

(4.56)

where

w

u

These simplified forms of the bounds eff and eff, using the optimality conditions (4.54) and (4.55), were first given by Suquet (1995, 1997a). For power-law composites, one obtains the results

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Pedro Ponte Castaiieda and Pierre Suquet

and

also due to Suquet (1993a). 3. Nonlinear Polycrystals Restricting the optimization in (4.47) to compliance tensors giving finite values for the functions u(") leads to the result (deBotton and Ponte Castafieda, 1995) that

ueff(c)2 u eff (X)=

sup LYj;;20

\..,

r=l

{fc

: Mi""(Q) :

e - y~c"'g:;;*(a; N

K

r = l k=l

,....N

k=1, ...,K

where Q denotes the whole set of positive slip compliances a:;;, and MIeff is the effective compliance tensor of the linear comparison polycrystal with grain compliances M(r),as given by (4.28) in terms of the slip compliances a. Here also the effective stress-strain relation of the polycrystal may be approximated by the stress-strain relation (4.48) of the linear comparison composite, with the optimal M): replaced by the optimal a:;;.The nonlinear optimality relations (4.50) read

(4.59) These nonlinear equations can be expressed more explicitly in terms of the slip compliances a:;; and the corresponding second moment of the resolved shears,

21 1

Nonlinear Composites The result is

(4.60) In addition, the bound can be rewritten in the form N

K

(4.61) r = l k=l

For power-law polycrystals, one also has the result

D.

INTERPRETATION OF T H E VARIATIONAL

PROCEDURE AS A SECANT METHOD It has already been noted that the stiffness tensors in the linear comparison composite are piecewise constant (by assumption) and are determined by the optimality conditions (4.40). This situation is reminiscent of the secant method (described in more detail in Appendix D). A rigorous connection between the variational bound (4.37) and the secant method can be made following Suquet (1995). The characterization (4.44) of involves a variational problem:

w

N

Under appropriate hypotheses on the growth of the function F @ ) ,the variational problem (4.63) admits a unique solution u, which satisfies

u E IC(E),

[

aJ

(u),v*] = 0,

vv* E IC(0).

(4.64)

Pedro Ponte CastaAeda and Pierre Suquet

212

The derivative a J/av is the Frtchet derivative of the functional J,and [ , ] is to be understood in the sense of a duality product. A straightforward calculation shows that

[

av

(v),

.*I

= (e(v) €4 E ( V * ) ) @ ) .

(4.65)

The variation of J with respect to v is

[g (u), where I$)

c N

=

c(‘)(e(u) :

ILp : e(v*))?

(4.66)

r=l

is the secant tensor in phase r , (4.67)

By virtue of (4.66), the solution u of (4.64) solves the following system of equations: (4.68) where

cx N

IL, (x) =

( T “1).

( r )(x)ILj.’)

r=l

Given the tensors , ):LI the above problem is a classical one for a linear elastic material. Note, however, that these tensors themselves depend on the strain field E through the second moments of the strain 7 which themselves depend on the tensors s = 1, . . . , N . Recall that the second moments of the strain in the individual phases are given by (4.46). The problem is therefore nonlinear, consisting of the set of equations (4.67) and (4.46), which are equivalent to (4.45). In conclusion, the variational procedure, when restricted to piecewise constant moduli, can be interpreted as a secant procedure. The nonlinear composite is replaced by a linear composite with constant (but unknown) stiffness tensors in each phase. These tensors are given by the constitutive law as the secant tensor for the some “effective” second moment of the strain 2 or of the stress dl- ( r ) , which performs (in a certain sense) an averaging of the strain or stress field in each phase. This is not the usual average (or first moment) classically used in most secant methods (Berveiller and Zaoui, 1979; Tandon and Weng, 1988), since in

ILt),

PLATE1. Changes of mode shapes during loading.

step 10

step 50

step 200

step 250

step 350

step 679

(3)

PLATE2. The buckling process, perfect cylinder.

step 37

step 50

step 70

step 100

step 120

step 262

PLATE3. The buckling process, imperfect cylinder.

PLATE4. Unidirectional composites with fibers aligned in the x3 direction. Cross-sectional

(x,-x*) maps of accumulated plastic strain corresponding to different macroscopic stresses. a) Pure shear. b) and c) Combined in-plane shear and axial tension. [b) corresponds to the state of stress at the vertex of the extremal flow surface.] d) Pure uniaxial tension along x3 (from Moulinec and Suquet, 1995).

Nonlinear Composites

213

r

general % ( r ) and ( r ) are different from the fourth-order tensor formed with the averaged strain or stress,

-

z(r)

p r ( u p = 21 c@) dr).

1 @ u ) ( r )# 1 - 2(u

@

-

@

The idea of considering an effective stress based on the second moment of the stress in each phase, instead of the usual first moment of the stress, is not entirely new. Something similar has been proposed by Qiu and Weng (1992) in the special context of porous materials. More specifically, these authors made use of the distortional energy in a linear comparison porous material to estimate the strain in the matrix phase, which allowed them to obtain improved estimates, relative to those obtained by the classical secant procedures, for the effective behavior of nonlinear porous materials. However, these authors took advantage of an approximation that is only exact when the matrix is incompressible, but which introduces errors relative to the “exact” (in the context of the piecewise constant moduli approximation) results of this section when the matrix phase is compressible (see Suquet, 1997a). Second moments have also been used earlier by Buryachenko and Lipanov (1989a, b) in the specific context of a generalization of the “multiparticle effective field scheme” for nonlinear composites. However, these authors apparently did not use (see Buryachenko, 1996) the exact expression for $(‘I, using instead an approximate formula that is also only exact for incompressible materials. The exact result for F ( r )was known and used by Kreher (1990), among others, to compute the stored energy in thermoelastic composites. Finally, after the present review was completed, the work of Hu (1996) was brought to the attention of the authors. This work, which is independent of the work of Suquet (1995, 1997a), concludes, similarly, that the variational method can be interpreted as as a secant method based on the second moment of the stress.

E. DISCUSSION

A few points are worth emphasizing at this stage. First, any estimate for the effective modulus tensor of a linear elastic composite (or class of composites) can be used to generate, by the variational procedures developed in this section, a corresponding estimate for a nonlinear composite with the same microstructure (or class of microstructures). This is a major advantage of these variational procedures using a linear comparison composite, because they are not tied in to any

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Pedro Ponte Custuiieda and Pierre Suquel

specific type of estimate. Other competing schemes, on the other hand, are closely connected with specific types of estimates. For example, the Talbot-Willis procedure, discussed in Section 111, serves to provide only estimates of the HashinShtrikman type. Second, if the relevant estimate for the effective modulus tensor of the linear elastic composite happens to be an upper bound for Le", then an upper bound is generated for Weff. If, on the other hand, the linear estimate is a lower bound, then the variational procedure cannot be used, in general, to obtain a lower bound for the nonlinear composite. In this sense, the variational procedure has the same limitation as the Talbot-Willis procedure, in that only one-sided bounds can be obtained. However, if a fairly accurate estimate (not necessarily a bound) is available for a specific type of linear composite, the variational procedures of this section can be used to generate a corresponding estimate for a nonlinear composite with the same microstructure, or type of microstructures, where these estimates (for Weff) would tend to err on the high side, because of the approximations intrinsic to the variational procedure. In particular, the variational procedures can be used to reproduce exactly the classical nonlinear Voigt bounds (see Ponte Castaiieda, 1992a), as well as the Talbot-Willis bounds (see Ponte Castaiieda, 1991a, 1992a; Willis, 1991,1992), when the Voigt and Hashin-Shtrikman bounds are used, respectively, for the linear comparison composite. In addition, however, the variational procedures of this section can be used to generate higher-order (of grade higher than 2) bounds, such as Beran-type bounds (Ponte Castaiieda, 1992a), as well as other types of estimates, such as generalized self-consistent estimates (Suquet, 1993b), which would not be available from the Talbot-Willis extension of the Hashin-Shtrikman variational principles. Finally, it is mentioned that Smyshlyaev and Fleck (1995) have recently provided extensions of the variational procedures in the context of strain gradient plasticity (see also Fleck and Hutchinson, 1997). Third, the variational procedures of this section have made use of the concuvity hypothesis (4.18) on the function F associated with the local strain potential w through relation (2.17). Although this mild hypothesis is satisfied by the standard models of plasticity and creep, pathological examples, not satisfying this hypothesis, can be constructed for which the variational procedures fail to deliver Hashin-Shtrikman bounds that are as good as those that may be obtained via the Talbot-Willis variational procedure (see Willis, 1992; Ponte Castaiieda and Willis, 1993). On the other hand, when the concavity hypothesis is satisfied, Ponte Castaiieda ( 1 9 9 2 ~has ) shown, in the context of composites with isotropic phases, that the Talbot-Willis variational principles may be derived via the variational principles of Ponte Castaiieda, directly from the Hashin-Shtrikman varia-

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215

tional principles for linear composites. As a way of preserving the advantages of both the Talbot-Willis and Ponte Castaiieda procedures, Talbot and Willis (1992) proposed a hybrid of these procedures, one that works for materials for which the concavity hypothesis is not satisfied, but at the expense of introducing a more complicated linear thermoelustic composite. Because of space restrictions, the variational principles of Talbot and Willis (1992) will not be discussed further in this work. It is noted, however, that Talbot and Willis (1997) have recently made use of these variational principles, together with a nonlinear comparison composite, to generate third-order bounds in the “other” direction. Fourth, an alternative, simpler way of accounting for materials for which the concavity hypothesis is violated has been proposed recently by Ponte Castaiieda (1996b, 1997b) (see also Kohn and Little, 1997, and Bhattacharya and Kohn, 1997, in the context of polycrystals). The idea of the method is similar to the “translation method” (Lurie and Cherkaev, 1986; Milton, 1990), except that the homogeneous quasi-convex reference material is replaced by a linear comparison composite, exactly as in the variational procedures developed in this section. Bounds for nonlinear composites can then be obtained by using a Reuss bound on the translated problem, which is now nonlinear, in combination with uny estimate for the linear comparison composite. Once again, space restrictions will not allow further discussion of this work. Suffice it to say that, at least for isotropic composites, the bounds resulting from this approach can be shown to be equivalent (when the concavity hypothesis is satisfied) to those obtained from the variational procedures reviewed in this section. In general, however, the newer method is more difficult to use than the earlier ones discussed in this section because they require an additional step involving the computation of Reuss-type bounds for nonlinear, nonconvex materials. This step can become computationally intensive, especially for polycrystalline aggregates. Fifth, the functions F(‘) in (2.17) are well defined for special “rank-one” fourth-order tensors Q of the form Q = 6 = ( 1 / 2 ) ~@ E . But their extension to arbitrary fourth-order tensors Q is not uniquely defined, even under the concavity hypothesis. The variational representation (4.22) is, of course, independent of the chosen extension, but the upper bound (4.44), valid for each possible F(‘), could depend on the chosen extension, since ( r ) is not necessarily rank one. In principle, it would be possible to optimize the upper bound by taking the infimum over all possible extensions F(‘) (the infimum of concave functions still being a concave function). This possibility and related issues about the nonuniqueness of the extension have not been yet explored in detail and will not be discussed further here.

r

weff

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Pedro Ponte Castanleda and Pierre Suquet

V. A Second-Order Theory This section is devoted to exact results pertaining to the effective behavior of nonlinear composites with small contrast (or weakly inhomogeneous nonlinear composites) and to related estimates for arbitrary contrast of the phases. In the context of linear elasticity, it is well known that the effective modulus tensor of a weakly inhomogeneous composite with random microstructure can be determined exactly to second order in the contrast. In the first part of this section, an analogous result, due to Suquet and Ponte Castaiieda (1993), is derived for nonlinear composites. By comparing this exact asymptotic result with the corresponding expansion for the variational estimates of Section IV (and therefore of Section 111), it is found that the variational estimates are only exact to first order in the contrast, when estimates that are exact to second order are used to estimate the behavior of the linear comparison composite. In the second part of this section, a recently developed theory, due to Ponte Castaiieda (1996a), which does deliver estimates that are exact to second order in the contrast for nonlinear composites at arbitrary contrast, is developed.

A. WEAKLYINHOMOGENEOUS NONLINEAR COMPOSITES 1. Small-Contrast Expansions for the Exact Effective Potential

In this section, the contrast between the phases is assumed to be small. More specifically, the potential w is assumed to depend on a small parameter t , serving to characterize the contrast between the properties of the composite and those of a homogeneous nonlinear reference material with energy function w(O)( E ) , such that W(X, E ,

t ) = W(O)(E)

+ tsW(X, E).

(5.1)

The effective potential also depends on the parameter t :

where ut and E ( u ~ )are the local displacement and associated strain fields induced by appropriate boundary conditions generating an average strain E in V. It will be assumed that We""(., t ) and ut are continuously differentiable functions of t . Since t is small, it is appropriate to look for a perturbation series expansion of Weff about t = 0, given formally by

Weff(E, t ) = Weff(E, 0) + t

a weff ~

at

(E, 0)

a2weff + yt 2 7 (E, 0) + 0 ( t 3 ) .

(5.3)

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217

The first few derivatives in this expansion may be computed by successive derivation of (5.2); this procedure will naturally involve derivatives of u,.The problem to be solved for ut is given by = 0,

uf E IC(E).

(5.4)

By differentiation of system (5.4), it is seen that uf (the dot denoting the derivative with respect to t) is, for all t , the solution of the system of equations

+

div(IL, : e(ur)) div(r,) = 0,

u, E K(O),

(5.5)

where

Note that IL, is the tensor of instantaneous or tangent moduli. The first two derivatives of Weff may be expressed in terms of only ui and u,.Indeed, it follows from (5.2) that

The first term vanishes by Hill's lemma, and therefore,

By means of the system of equations (5.5) satisfied by ut, one obtains the result that

a2weff

(-a

-(E, t ) = (6w)(x, E ( u , ) ) : e(u,)) = -(e(uZ) : ILt : e(u,) at2 ae

The relations (5.6) and (5.7), which hold for arbitrary values o f t , allow in particular the computation of the first two derivatives of Weff at t = 0. Using the fact that the material is homogeneous at t = 0, and therefore uo = E .x, it follows that

Weff(E, 0) =

w'O)

(E), (5.8)

where

21 8

Pedro Ponte CustaZeda and Pierre Suquet

In these relations, u o is the solution of the linear elasticity problem,

+

div(IL.") : E(UO)) div(t) = 0,

uo

E

K(O),

(5.10)

where

a

t ( ~ = )- ( ~ w ) ( x E). , aE

Given that the modulus tensor L(")is constant, problem (5.10)is a standard linearelasticity problem for a homogeneous material with a distribution of body forces determined by the polarization field t.Note that this is a special case of the polarization problem (3.4), encountered in the Hashin-Shtrikman variational principles of Section 111, with E = 0 and with Leo) specified by (5.9). When the composite is made up of N homogeneous phases (r = 1, . . . , N), the polarization field is piecewise constant (a constant in each phase), with

The determination of (a2Weff/at2)(E,0) then requires the computation of the elastic energy associated with uo (see (5.8)). This energy is obtained from (3.1 1) and (3.12), so that (5.1 1) "I

r=l s=l

are defined by (3.10). In conclusion, the where the microstructural tensors rcrs) following result, due to Suquet and Ponte Castaiieda (1993), is obtained: t2

Weff(E,f) = (w)(E) - 2

N

N

+ 0(t3).

t ( r :)F"") : t(")

(5.12)

r=1 s=l

Isotropic constituents. In this section, we restrict our attention to N-phase composites with isotropic constituents, with strain potentials defined by (5.1) and

219

Nonlinear Composites

Then the polarizations may be written in the form t(r)

= 36k(')E,I

+ 26p(")Ecl,

2 3

6p"') = - (6.f @I)'( E:J>

where Ed = E - E,I is the average strain deviator, and, using the spectral decomposition introduced by Ponte Castaiieda (1996a), the tangent modulus tensor L(")may be written in the form

L(O) = 3k(O)J

+ 2p(O)F+ 2h(O)lE,

(5.13)

where

and where Jl is the standard hydrostatic projection tensor, defined by (2.24). The tensors (5.14) and

F=K-E,

(5.15)

are also projections, such that

It follows from (5.3) (Ponte Castaiieda and Suquet, 1995) that, to second order in t , one has

2. Small-Contrust Expansion for the Estimate

weffof Section IV

Having obtained the small-contrast expansion to second order for the exact effective potential Weff, it is relevant to consider the corresponding expansion for

220

Pedro Ponte Castaiieda and Pierre Suquet

w

the approximate estimate eff arising from the variational procedures of Section IV. Thus, starting, for example, from (4.44), it is possible to obtain the result that

where the tensors H(") have a rather complicated form in general. Regardless of the explicit form of the the key observation is that these tensors are different from the tensors r(rs) in the corresponding expansion (5.12) for the exact effective potential Weff. This is because, whereas the tensors F(") depend on the tangent modulus tensor (5.9),the tensors can be shown to depend on the secant modulus tensor (4.67) and its derivative. In particular, for isotropic constituents, it has been remarked that the tangent modulus tensor is anisotropic, whereas the secant modulus tensor is isotropic, highlighting the difference between the secant and tangent modulus tensors. The important conclusion from this observation is that the estimate eff, obtained by the variational procedures of Section IV, for the effective potential Weff is exact only tofirst order in the contrast.

w

B. NONLINEAR COMPOSITES WITH ARBITRARY PHASE CONTRAST 1. Second-Order Estimates f o r the Effective Potential of N-Phase Composites Motivated by the findings of the previous subsection, a new method for estimating the effective behavior of nonlinear composites was proposed recently by Ponte Castaiieda (1996a). Like the variational methods of Section IV, this procedure makes use of a linear heterogeneous comparison material, but the choice of the comparison material is different, involving the tangent modulus tensors of the constituent phases, instead of the corresponding secant modulus tensors. This choice of comparison material ensures that the resulting nonlinear estimates are exact to second order in the contrast, and thus are in agreement with the smallcontrast asymptotic results of Suquet and Ponte Castaiieda (provided that the corresponding estimates for the linear comparison composite are also exact to second order). The new method is based on the Taylor formula with remainder for the phase potentials w ( ~ Thus, ). introducing reference strains E(r),the Taylor formula for w ( ~about ) E(') reads

&

(5.17)

Nonlinear Composites

22 1

where p(') and L@)denote an internal stress and a tangent modulus tensor, with components

+

respectively. Note that L (') depends on the strain E(') = A(') E(') (1 - A ( ' ) ) E , where A(') depends on E and is such that 0 < A ( r ) < 1. In terms of the average (E) and oscillating ( E ' ) components of E , the above expression for w(I) may be rewritten in the form

(5.19) where

(5.20) and where t(r)

= p ( r ) + L(r) . (E - E(r)).

(5.21)

It then follows from (2.41), by making the approximation that the strains E(r)are constant in each phase, that the effective potential W e f fof the nonlinear composite may be estimated as

where (5.23) and where the following definitions have been used: N

N

r=l

r=l

The advantage of approximation (5.22), relative to the exact expression (2.41), for the effective potential Weff of the N-phase nonlinear composite is that (5.22)

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Pedro Ponte Custuiiedu and Pierre Suquet

requires only the solution of a linear problem for an N-phase themoelastic composite, as defined by the Euler-Lagrange equations of the variational problem P in (5.23):

div(L : E ( u ' ) ) = -div(t),

u'

E

IC(0).

(5.25)

In general, estimates for N-phase linear-thermoelastic composites can be obtained by appropriate extension of the corresponding methods for N-phase linear-elastic composites (see, for example, Budiansky, 1970; Laws, 1973; Willis, 1981). Note that similar, but not equivalent, representations for the effective behavior of nonlinear composites, also using hetereogeneous thermoelastic reference materials, have been proposed by Molinari, Canova and Ahzi (1987) and Talbot and Willis (1992). Given an estimate for P , the expression (5.22) therefore provides a corresponding estimate for Weff,for all choices of the Ecr)and E@).A plausible prescription for the E(') is to set them equal to the averages of the strain field over the phases r . However, since the exact strain field is not known, the approximate field E , as determined by (5.25), is used instead, so that the proposed prescription for the E(') becomes

+

Physically, this is a where E ( r ) has been used to denote ( E ) ( ' ) = E (.d)(rj. good choice in the context of the estimate (5.22), because the strain E in phase r is expected to oscillate about its average in phase r in such a way that large deviations would only be expected in regions of relatively small measure. In this connection, it is useful to note the following identity, obtained from relation (5.23) (see Appendix B.3 for details), namely, (5.27) which can be used to obtain the phase-average strains .G('j, directly from P , via the relation (5.28) Therefore, the reference strains E"' may also be computed from P , by means of relations (5.26) and (5.28).

Nonlinear Composites

223

It is further remarked that the prescription (5.26) for the E(') is optimal in the sense that the estimate (5.22) for Weff is stationary with respect to the E('). To see this, note, from (5.20), that

and, from (5.27), that

so that, from (5.22),

which, because of the prescription (5.26), is identical to zero. One important consequence of the stationarity of the prescription (5.26) is that the overall stress-strain relation (2.42) for the composite may be approximated as

where the Z") are determined from relations (5.28), and where

This result is easily obtained by taking the derivative of relation (5.22) with respect to E, with E(') held fixed (because of stationarity), and enforcing (5.26). Notice that the "correction" term in the average stress-strain relation depends on the second moment of the difference between the strain field and its average over the phases. The prescription (5.26) also allows simplification of the estimate (5.22) for We". Note that the Euler-Lagrange equations (5.25) of the problem (5.23) for P imply, using integration by parts, that (t : E ( U ' ) )

= -(E(U') : L : E(U')),

(5.31)

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Pedro Ponte Custaiiedu and Pierre Suquet

which, with the help of prescription (5.26) and definition (5.21) of the polarizations T ( ~ ) can , be used to rewrite estimate (5.22) in the simpler form

Weff(E)= Weff(E)

where the E(r) are determined by relations (5.28). Finally, the choice of E@)in definition (5.18) of the L(') is not as straightforward, and, in particular, stationarity of Weff with respect to E(') cannot be implemented. For this reason, Ponte Castaiieda (1996a) proposed the following physically motivated prescription for the E@),namely, E ( r ) = g(r) = ~ ( r ) .

(5.33)

There are other possibilities, but they have yet to be explored in full detail. One interesting consequence of prescription (5.33) is that it implies that

(5.34) 2. Exactness to Second Order in the Contrust It follows, from result (5.31), that it is also possible to rewrite estimate (5.22) for weffas N

(5.35) where E' is obtained from the solution of the boundary value problem (5.25) for u'. Now, for weakly inhomogeneous composites, with the parameter t in (5.1) set small, and assuming that

the following two observations can be made. First, note that the functions v ( ~ ) are in fact the second-order Taylor expansions of the functions w ( ~about ) Ecr), evaluated at E. Therefore.

Nonlinear Composites Second, the the form

t('),defined by

225

the relations (5.21), can be similarly shown to be of

(5.38) from which it follows that the solution of the boundary value problem (5.25) for u' is given by

u' = tuo

+ O( t2) ,

where uo is the solution of the boundary value problem (5.10) associated with the small-contrastexpansions of Section V.A.1. Combining these two observations, it is concluded that

r=l

which is in agreement with the small-contrast expansion (5.3) with (5.8). It can also be verified that prescriptions (5.28) and (5.33) for E(') and E(r),respectively, are consistent with hypotheses (5.36). Therefore, the second-ordertheory of Ponte Castaiieda (1996a) is exact to second order in the contrast. 3. Two-Phase Composites For two-phase composites,a well-known result by Levin (1967) permits further simplification of the thermoelastic problem P , and therefore of the corresponding estimate for Weff. The result for P , which depends only on the effective modulus tensor Leffof a two-phase, linear-elastic composite with phase modulus tensors IL(') and L(2),is given by

1 P = - ( A t ) : (AIL)-' : (ILeff - (IL)) : (AIL.)-' : ( A t ) , 2

(5.39)

where AIL = L(')- IL.(2) and A t = t(')- ~ ( ~ It1 then . follows, from (5.28) and (5.33), that the prescriptions for E(') and E(') reduce to

E(') = E(') = E ( r ) = E + (A(') - 1) : (AIL)-' : ( A T ) ,

(5.40)

where the A(') denote the strain-concentration tensors (Hill, 1965a)for the linearelastic composite problem. They are such that c ( l ) ~ ( l )+ c ( 2 ) ~ ( 2 = ) 1,

Leff = c ( l ) ~ ( l ). ~

( 1+ ) , ( 2 ) ~ ( 2 ). ~ ( 2 )

which can be used to solve for the tensors A(r)in terms of the L(') and Leff. It is emphasized that estimates of any type for Leffcan now be used to gener-

226

Pedro Ponte Castaiieda and Pierre Suquet

ate corresponding estimates for Weff. For example, as pursued in Section VII, Hashin-Shtrikman and self-consistent estimates for Leffmay be used in (5.40) to generate, via (5.32), corresponding Hashin-Shtrikman and self-consistent estimates for We". Note, however, that prescription (5.40) for E(') is implicit in the sense that the expressions for I,(') and t('),appearing on the right-hand-side of (5.40), also depend on E('). 4. Isotropic Composites The application of the above procedure is briefly described here for composite materials with isotropic phase potentials of the form w ( r ) ( e )=

9 k(')&;L, 2

-

+ f"'(&:q),

(5.41)

where k(') denotes the bulk modulus and f ( ' ) characterizes the shear response of phase r . We note that the functions f ( ' ) are generally nonlinear, except that they are required to comply with the previously stated hypotheses on w. Given the above expression for w(') and recalling, from (5.33), the prescriptions that E(') = E(') = E ( " ) , one computes, from relations (5.18), ,(I'

= 3k(r)~,(;)1+ 2 p ( r ) 2 i ) ,

(5.42)

where

h ( r ) = FL(r)

and where J,

and IF(')

(5.45)

are projection tensors defined by (2.24), (5.46)

and

respectively. No further simplification is available in general for the second-order estimates (5.32), but fairly explicit results can be obtained for two-phase random composites

Nonlinear Composites

227

with statistically isotropic microstructures, in three and two dimensions, the latter physically corresponding to transverse shear of a fiber-reinforced composite with transverse isotropy. These simplifications for composites with isotropic phases and statistically isotropic microstructures arise because, in this case, the phase average strains E(') can be assumed to be aligned with the applied macroscopic strain E. Some more explicit results will be given in Section VII. C. DISCUSSION In this section, a perturbation expansion (Suquet and Ponte Castaiieda, 1993), exact to second order in the contrast, has been carried out for the effective potentials Weff of nonlinear composites. It is emphasized that the second-order term in the expansion depends only on the two-point statistics of the composite and completely specifies its effective behavior (to second order in the contrast). By comparison with this exact result, it was also found that the variational estimates of Section IV (and therefore those of Section 111)are exact only toJirst order in the contrast. In this connection, it is relevant to emphasize that the nonlinear HashinShtrikman bounds of Section IV are not "second-order'' bounds in the same sense as their linear counterparts. Like the linear bounds, the nonlinear bounds do incorporate second-order statistics, but unlike them, they are not exact to second order in the contrast. In addition, in this section, a second-order theory has been developed (Ponte Castaiieda, 1996a), that does deliver estimates that are exact to second order in the contrast. However, the approximations involved in this second-order theory are such that it is not possible to control the sign of the error in the approximations involved, so that the resulting estimates, unlike the variational estimates of Section IV, cannot be guaranteed to be bounds. Another important limitation of the second-order theory is the existence of a duality gap (i.e., fieffand do not satisfy the duality relation Ueff = (w"')*). More specifically, the corresponding estimates for the stress potential Ueff, obtained by a completely analogous procedure (to the one followed in Section V.B. 1 for Weff),are found to be nonequivalent to those for Weff. This is unlike the case for the variational estimates and U of Section IV, which were found to satisfy the duality relation. As a practical matter, in plasticity and creep, the second-order estimates based on the developments of Section V.B.l for Wefr are found to be more accurate than the analogous estimates for Ueff (see Ponte Castaiieda and Kailasam, 1997, for an analogous situation in the context of nonlinear conductivity). Roughly speaking, this is because Taylor expansions for w (which is subquadratic) are more accurate than the corresponding Taylor expansions for u (which is superquadratic).

+ff

weff

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Pedro Ponte Castaiieda and Pierre Suquet

In theory, it would be desirable to develop methods that deliver bounds that are exact to second order in the contrast, although this may pose a formidable task, in general. In practice, however, as will be discussed in Section VII, the bounds of Section IV and the second-order estimates of this section provide complementary information, which can be used to estimate rather efficiently and accurately the overall behavior of nonlinear composites.

VI. A Selection of Results for Linear Composites The methods that have been developed in Sections IV and V.B. 1 make use of estimates for the effective modulus tensor of comparison linear-elastic and thermoelastic composites to generate corresponding estimates for nonlinear composites. Before presenting applications of these methods, a brief selection of various bounds and estimates for linear-elastic composites is given in the present section. For more comprehensive information, refer, for example, to the review articles by Hashin (1983), Walpole (1981), and Willis (1981), as well as the monograph by Nemat-Nasser and Hori (1993).

A. HASHIN-SHTRIKMAN BOUNDS FOR RANDOM COMPOSITES SYMMETRY WITH ELLIPSOIDAL Define the joint probability function of finding simultaneously phase r at x and phase s at x’ as

where statistical homogeneity has been assumed, so that P ( r s ) ( xx’) , = P ( ‘ ” ) ( xx’). Under the no-long-range order hypothesis, the finite-body (over V ) kernel in definition (3.6) of the operator k(O)may be replaced by the corresponding kernel constructed from the infinite-body Green function, which becomes a function of x - x’ only. Then, using the ergodic assumption allowing the replacement of ensemble averages by volume averages over the representative volume element of the composite V , it follows (Willis, 1977, 1981), by interchanging the order of integration in expressions (3.10) for the tensors K‘(rs), that

Nonlinear Composites

229

where r(O)(x) is now the infinite-body kernel associated with a homogeneous material with modulus tensor L(O). It is further assumed that the two-point probability function has "ellipsoidal symmetry," so that P('")(x) = P(")((IZ -XI) for some constant, symmetric tensor Z. Note that the special case where Z = I, such that the P ( r s )depend only on 1x1, corresponds to statistical isotropy. Thus ellipsoidal symmetry defines the class of microstructures that would be obtained by uniformly stretching statistically isotropic microstructures. Under this statistical hypothesis of ellipsoidal symmetry, Willis (1977, 1981) has shown that the microstructural tensors r(rs) reduce to

where

with

Note that P(O) has the diagonal symmetry of an elasticity tensor. It is therefore easier to use than the Eshelby tensor S(O) (Eshelby, 1957), to which it is related by P(O) = ScO): M(O), with M(O) = (Leo))-' denoting the compliance of the reference medium. The tensor P(") is known explicitly for a few cases of practical relevance. For example, when the reference medium is isotropic and the phases are assumed to be isotropically distributed, so that Z = I, the tensor P(O)is also isotropic, and

with

Other cases of special interest are given in Appendix C and are recalled in the following sections as needed. Given the above explicit expressions for the microstructural tensors F(") in terms of P(O),still within the context of the Hashin-Shtrikman variational procedure, it is possible to specialize to linear-elastic composites the expressions (3.9)

Pedro Ponte Custufiedu and Pierre Suquet

230

for the average strain in phase r , k c r )= A(’) : E, and (3.17) for the effective potential Weff. The result can be written in terms of the relevant effective modulus tensor, given by

(6.4)

As mentioned earlier, the choices LC0)= rnax,{IL(‘)} and LC0)= rnin,.{lL(‘)) lead, respectively, to rigorous upper and lower bounds for ILeff. It is emphasized that such bounds, although appearing to depend only on the volume fractions, also incorporate two-point statistics (through the microstructural tensors P(’)), and therefore have the potential of being sharper than the Voigt-Reuss bounds. The bounds (6.4) are due to Willis (1977) and are known to be exact to second order in the contrast SIL = IL - lLC0), so that Leff

- (IL)

-

(SIL : P(O) : (SlL - (SIL)))

+ O(SlL”),

which is in agreement with the general result (5.12) (simplified with the help of (6.1)). When the microstructure is statistically isotropic (with Z = I), the celebrated bounds of Hashin and Shtrikman (1962a, b, 1963) are recovered from (6.4). For example, for two-phase composites with isotropic phases,

L ( r ) = 3k‘r)j + 2pL(r)~,

Leff = 3keff~+ 2 p e f f ~ ,

where

with k p ) and pf’ given by (6.3). It is known (Francfort and Murat, 1986) that these bounds are attainable by composites with sequentially laminated microstructures, and are therefore optimal, provided that the phases are well ordered, > 0. One interesting feature of the sequeni.e., if ( p ( l )- p L ( 2 ) ) ( k (-’ ) tially laminated microstructures is that they are “particulate” in the sense that the constituents occupy clearly defined “matrix” and “inclusion” phases. The upper

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23 1

bound requires the stiffer phase to occupy the matrix phase, and vice versa for the lower bound. This is suggestive of the fact that the Hashin-Shtrikman bounds may be appropriate for composites with particulate microstructures, at least for twophase systems. The next section develops this notion further. Another important case is that of two-phase composites with isotropic phases and “spheroidal symmetry” corresponding to transverse isotropy. In this case, the IF’() tensor is also known, and is given by relations (Cl) in Appendix C. The corresponding HashinShtrikman estimates (6.4) may be used to model laminated and fiber-reinforced composites (both continuous and chopped fibers).

B. HASHIN-SHTRIKMAN BOUNDSAND ESTIMATES FOR RANDOM COMPOSITES WITH PARTICULATE MICROSTRUCTURES Willis (1978, 1981) made an application of the Hashin-Shtrikman variational principles to N-phase composites with particulate microstructures consisting of a random distribution (in space) of families of aligned, self-similar inclusions of phase r (r = 2, . . . , N) in a matrix of phase 1, where the two-point probability function for the distribution of the centers of the inclusions was assumed to be statistically homogeneous and to satisfy the “ellipsoidal symmetry” hypothesis. This statistical hypothesis is defined by the requirement that the P ( r s )depend only on x” = x’ - x through the combinations IZ!”’ x”1, for some tensors Z!’), symmetric in their superscripts. In addition, no overlap of inclusions was assumed, so that P ( r s ) = 0 for overlap conditions. For two-phase systems, when the inclusions are ellipsoidal with identical shape, characterized by a tensor Z, and the distributional tensors Z:’) are all assumed to be equal to Z, Willis (1978) obtained Hashin-Shtrikman bounds for the pertinent effective modulus tensor Le“, by setting ILco) = L(’). The result was in precise agreement with the bounds (6.4), specialized for two-phase systems, which were derived originally for general classes of ellipsoidal microstructures (i.e., for microstructures that are not necessarily particulate). A generalization of this result for N-phase composites consisting of N - 1 types of aligned ellipsoidal inclusions, characterized by shape tensors Z j r ) , distributed with ellipsoidal symmetry in matrix of phase 1, with distribution shapes Z:”’ (different from the Z“), was given by Ponte Castafieda and Willis (1995). The result for the relevant microstructural tensors (3.10) is

-

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Pedro Ponte Castatieda and Pierre Suquet

where IP':r) and)';'PI denote the P-tensors (6.2) associated with the inclusion and distribution shape tensors Z r ) and Z!", respectively. The corresponding estimates for Leff are obtained from the piecewise-constant polarization HashinShtrikman estimates (3.17), with L(O)set equal to the modulus tensor of the matrix L('),so that the polarization field vanishes exactly in the matrix phase. When L(') happens to be equal to the maximum or minimum of the L@), the resulting estimates are, respectively, rigorous upper and lower bounds for Leff;otherwise, they are plain variational estimates. When all of the distribution shape tensors Z:') are identical, say, equal to Z d , the result for Lefftakes the simple form N

Leff =

A(r) = (1+

IP'y:

C

c ( r ) L ( r ) : A('),

r=l

where IP'd is the IP' tensor (6.2), associated with the distribution shape tensor Zd, and 6L(') = L(r)- I,(').These estimates provide a generalization of Eshelby's (1957) estimates for composites with dilute concentrations of ellipsoidal inclusions, with which they agree to first order in the volume fraction of the inclusions. Note that the distribution effects appear only to second order in the volume fraction of the inclusions, whereas the particle shape effects are of first order in the volume fraction of the inclusions. These estimates also reduce to the estimates (6.4) of Willis (1977) when = P,! = IP' and when either the stiffest or the most compliant material occupies the matrix phase. (In this case, they also agree with the so-called Mori-Tanaka (1973) estimates, but not more generally, when the Mori-Tanaka scheme can give nonsymmetric, and therefore physically unacceptable, predictions for Leff.)Finally, note that the no-overlap hypothesis places restrictions on the maximum volume fractions of the various types of inclusions, depending on the aspect ratios, as well as on the orientations of the ellipsoidal inclusions and their distributions relative to each other (see Ponte Castaiieda and Willis, 1995). In a closely related development, Hervt et al. (1991) made use of the HashinShtrikman variational principles to obtain upper and lower bounds for the effective modulus tensor of elastic composites with statistically isotropic distributions of composite sphere assemblages (Hashin, 1962). (Note that the bounds of Hashin for this class of microstructures did not make use of the statistical isotropy hypothesis, and are therefore weaker.) A generalization of the work of Hervt et al. (1991) for composites with ellipsoidal distributions of more general "morphologi-

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cally representative patterns” has been given by Bornert et al. (1996). For N-phase composites, when the morphologically representative patterns are “composite ellipsoids” with a common matrix phase, one of the bounds can be determined explicitly and is found to be in precise agreement with the corresponding one-sided bound (6.6) of Ponte Castaiieda and Willis (1995) (provided that the stiffest or most compliant material occupies the matrix phase). On the other hand, the other bound requires numerical computation in general (Bornert, 1996). For the special cases of composite spheres and cylinders distributed isotropically, however, the other bound may be computed exactly when the phases are isotropic (Hervt et al., 1991; Hervt and Zaoui, 1993). When the phases are additionally assumed to be incompressible, the result specializes to with

where the superscripts 1 and 2 have been used to denote the matrix phase and the spherical inclusions, respectively. One important practical implication of the work of Bornert et al. (1996) (see also Bornert, 1996) is that the one-sided bounds (6.6) of Ponte Castaiieda and Willis (1995) may be used as appropriate estimates for composites with particulate microstructures, at least for two-phase systems, provided that the contrast and the volume fraction of the inclusions are not too large. This observation is consistent with the previous comment on the optimality of the Hashin-Shtrikman bounds for statistically isotropic composites with isotropic constituents, and their attainability by microstructures that are particulate in character (Francfort and Murat, 1986). In particular, it means that expressions (6.6) may be used as valid estimates for particle- and fiber-reinforced composites. Finally, it is mentioned for completeness that Hashin-Shtrikman bounds have also been developed for other, more general types of microstructures, including the works of Lurie and Cherkaev (1986) and Milton and Kohn (1988) for composites with generally anisotropic microstructures.

c. SELF-CONSISTENT ESTIMATES FOR RANDOM COMPOSITES WITH

GRANULAR MICROSTRUCTURES

In the context of the Hashin-Shtrikman estimates (6.4), the observation was made by Willis (1977) that if the reference modulus tensor Leo) is chosen equal to the effective modulus tensor Leff,as given by relations (6.4), an implicit equation

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is obtained for I,(’), which when solved for L(O) leads to an estimate for Leff. This prescription reproduces exactly the self-consistent estimates of Budiansky (1965) and Hill (1965b) for two-phase composites, as well as the self-consistent estimates of Hershey (1954) and Kroner (1958) for polycrystalline aggregates, without the need for making the explicit assumption that the grains are ellipsoidal in shape. Thus the variational estimates (6.4) for Leff,with the prescription L(O) = Leff,provide a generalization of the classical self-consistent method for random composites with prescribed two-point statistics. Similarly, it is possible to consider the limit as the volume fraction of the matrix phase vanishes in the particulate Hashin-Shtrikman estimates (6.6), provided that the shape and orientation of the inclusions are set equal to those of the distribution ellipsoids. The resulting microstructure is “granular” in character, being composed of aligned ellipsoidal grains of identical shape and orientation, but of varying size so as to fill space. In this case, there is no advantage in choosing the modulus tensor L(O) of the homogeneous reference material to be equal to that of the matrix phase, since there is no matrix phase and all of the phases are now inclusions. Then perhaps the only sensible prescription is once again to choose L(’)equal to Leff,as given by expression (6.6), so that the average polarization in the composite vanishes identically. The resulting estimate for Leffis, of course, not a bound, but has the advantage that it treats all of the phases symmetrically, which may be appropriate for certain classes of composites with granular microstructures, such as polycrystals. Furthermore, perhaps not surprisingly, the resulting estimate is found to agree (once the phase indices are relabeled) with the above-mentioned self-consistent estimates for general microstructures with prescribed two-point statistics. This suggests that the self-consistent estimates may be appropriate for composites with granular types of microstructures, in much the same way as the Hashin-Shtrikman estimates were found to be appropriate for composites with particulate microstructures. An alternative interpretation and generalization of the self-consistent estimates in terms of “perfect disorder” has been given by Kroner (1977). The fact that the self-consistent estimates may be appropriate for granular-type microstructures is also suggested by the numerical results of Suquet and Moulinec (1997), where the classical self-consistent estimates are shown to be in good agreement with the results of numerical simulations for a special class of granular microstructures. A related result (Milton, 1985; Avellaneda, 1987) that will be useful to keep in mind, in the context of nonlinear composites, is the fact that the classical self-consistent estimate is also attainable-that is, there is at least one microstructure for which the self-consistent estimate is an exact result. Again, not surprisingly, such a microstructure is granular in character.

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235

Other types of self-consistent prescriptions have been proposed in the literature, including the generalized (or three-phase) self-consistent estimates of Christensen and Lo (1979), as well as the differential self-consistent scheme of McLaughlin ( 1977). The generalized self-consistent scheme is believed to provide adequate predictions for the overall properties for two-phase composites consisting of disordered assemblages of composite spheres and, in spirit, consists in considering a single composite sphere embedded in an infinite reference medium whose properties are precisely the unknown elastic properties of the composite. For two-phase incompressible phases with statistically isotropic distribution, the effective shear modulus predicted by this generalized self-consistent scheme is determined as the solution of the nonlinear equation

where the function F is defined by (6.7). Generally speaking, however, it is more difficult to give these types of estimates statistical interpretations, although Bornert (1996) has recently made progress along these lines in the context of the three-phase model. For brevity, these various estimates will not discussed be here, but it will be emphasized once again that the nonlinear homogenization procedures discussed in earlier sections have the capability of generating bounds or estimates for the overall properties of nonlinear composites from the corresponding bounds or estimates of any linear homogenization scheme.

D. THIRD-A N D HIGHER-ORDER BOUNDSFOR RANDOM COMPOSITES Beran ( 1965) introduced a procedure to obtain variational estimates depending on up to three-point statistics, directly from the minimum energy representations (2.41) and (2.43) for the effective potentials. These estimates were simplified and improved in various ways by Kroner (1977), Milton (1982), and Willis (198 1). However, for N-phase composites, these estimates are fairly complicated, involving microstructural tensors analogous to the k('")but , which depend on the threepoint probability functions P ( r s t )Note . that such bounds are known to be exact to third order in the contrast for weakly inhomogeneous composites. Here, for simplicity, only the simplification of Milton and Phan-Thien (1982) for two-phase composites with isotropic constituents and statistically isotropic microstructures will be mentioned. Thus, denoting the bulk and shear moduli of the phases by k(')

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Pedro Ponte Custuiiedu and Pierre Suquet

and p('), respectively, the third-order estimates for the effective shear and bulk moduli of the composite keff and peffmay be written in the forms

where f and jl are functions of the volume fractions c('), the phase moduli k(') and p @ )and , some third-order microstructural parameters q(') and {('I, lying in the interval [0, I]. For example, the third-order upper and lower bounds on keff are obtained by setting

respectively. Similarly, upper and lower bounds on peffare obtained by setting jl = 0 /6 and E/6, where 0 and E are given by rather complicated expressions (see eqs. (48) and (49) of Milton and Phan-Thien, 1982). When the phases are incompressible, however, the expression for j l for the upper bound reduces to

and q ( 2 )= 1 - q ( ' ) . ) (In these expressions, < ( 2 ) = 1 - {(I) Assuming for definiteness that k ( ' ) < k(2)and p ( ' ) < pLL(2), it is interesting to remark that the above third-order upper and lower bounds for keff and peffagree exactly with each other in the limits as q ( l ) and { ( I ) approach 0 and 1, reducing to the corresponding Hashin-Shtrikman (HS) upper and lower bounds in these limits, respectively. In particular, this means that the HS estimates are exact for statistically isotropic microstructures with q ( ' ) and (('1 equal to either 0 or 1. Examples of such microstructures are the sequentially laminated microstructures of Francfort and Murat (1986). Note that such microstructures are particulate in character, providing further evidence for the appropriateness of the Hashin-Shtrikman estimates for at least certain classes of particulate microstructures. Higher-order bounds incorporating statistical information of order higher than three have been proposed by a number of authors (see, for example, Kroner, 1977; Milton and Phan-Thien, 1982). Even-order bounds are obtained from the HashinShtrikman variational principles and odd-order bounds from the classical variational principles. As efficient computational methods are developed to measure

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237

three- and higher-point statistics, the practical value of these higher-order bounds is expected to become more significant. In any event, higher-order bounds for linear composites can be as easily incorporated into the nonlinear homogenization procedures as the two-point bounds. In the next section on examples, however, only higher-order bounds of the Beran type will be developed, with the limited goal of illustrating the general ideas.

VII. Applications to Nonlinear Composites and Discussion This section presents some examples of the application of the procedures of Sections IV and V.B for a few specific cases, including porous and rigidly reinforced materials, as well as more general two-phase power-law and perfectly plastic composites. For simplicity, almost all of the nonlinear examples will be restricted to two-phase systems with isotropic phases, although a few results will be given for power-law polycrystals. A. POROUS MATERIALS Although porous materials with anisotropic matrix phases could be considered more generally, in this section for simplicity only porous materials with isotropic matrix phases will be considered. Thus the matrix phase strain and stress potentials will be taken to be of the form (2.4) and (2.5). Some selected bounds and estimates for the corresponding effective potentials Weff and Ueff are given below. 1. VariationalBounds and Estimates

Because of the assumed isotropy, the results of Section IV.C.2 for composites with isotropic constituents can be used to obtain bounds for the effective potential Weff of porous materials. Thus, specializing equations (4.56) and denoting the matrix by phase 1, one has that

(7.1) where

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Pedro Ponte Castaiieda and Pierre Suquet

and where the first equation must be solved for ?

with

The corresponding lower bounds for U e f can be shown to have an analogous form. Use of any upper bound or estimate for the effective modulus tensor of a linear porous material, or class of porous materials, with an isotropic matrix then leads to corresponding upper bounds or estimates for the effective strain potential of nonlinear porous materials. No special simplificationof the resulting nonlinear estimates is available in general, but when the matrix phase is additionally assumed to be incompressible ( k ( ' )+ co),so that the effective modulus and compliance tensors of the linear porous comparison material can be written in the form

L

independent of for some microstructural tensors and 6, for Weff and the corresponding estimate for Ueff reduce to

w e f f ( ~I ) c(1)40(l)(E::)),

ueff(X)

the estimate (7.1)

c ( l ) ~ ( l ) ( ~eq (l)),

(7.3)

where

Some results of special interest for 2):

and/or

are listed below.

Hushin-Shtrikman bounds for statistically isotropic microstructures. When the distribution of the void phase is statistically isotropic, the linear HashinShtrikman (HS) bound (6.4) leads to a corresponding upper (lower) bound for Weff (Ueff).It is determined by the expressions

This HS bound for all statistically isotropic porous materials was first obtained by Ponte Castafieda (1991a) and Suquet (1992), directly from (4.51) and (4.57), respectively. Willis (199 1) showed that this result could be obtained, alternatively, by means of the Talbot-Willis procedure, thus improving an earlier result by Ponte Castafieda and Willis (1988), which made use of a nonoptimal choice of the ho-

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239

mogeneous reference material in the context of the Talbot-Willis procedure. Talbot and Willis (1992) made use of the estimate (6.4), together with a version of (4.51), to obtain the more general result (7.4). The bound (7.5) was also derived as an ad hoe estimate (not as a bound) by Qiu and Weng (1992) by estimating the stress in the matrix from the energy in the porous material. In this connection, it is relevant to note that although the “energy method’ of Qiu and Weng gives results that are in agreement with (7.3) for porous materials with incompressible matrix phases, the method delivers less accurate results (different from (7.1)) for porous materials with compressible phases. Related ad hoc estimates, in the context of a “multiparticle effective field method,” have also been obtained by Buryachenko and Lipanov (1989a,b), by estimating the stress in the matrix from its second moment. Once again, these early estimates agree with the bound (7.5) for dilute porosity levels when the matrix is incompressible, but not more generally (see Buryachenko, 1996, for details). Incidentally, an alternative, simpler way of obtaining multiparticle effective field estimates for nonlinear composites would be to make use of the corresponding estimates for linear composites in the context of the general nonlinear estimate (7. I), interpreted as an approximation. Hushin-Shtrikman bounds for ellipsoidal voids distributed with ellipsoidal symmetry. Using the HS bounds (6.6) of Ponte Castaiieda and Willis (1995), specialized for porous materials with incompressible phases, it follows that Weff is given by (7.3) and (7.4), with

where P = (l/c(’))(Pi - c(’)Pd). When both the shapes of the pores and the distribution are spherical, this result specializes to (7.5). In an attempt to incorporate the effect of pore shape evolution during deformation processing, an application of this result for perfectly plastic composites with identical shapes for the voids and the distribution was given by Ponte Castaiieda and Zaidman (1994). More general results when the shape of the pores and distribution are different have been obtained by Kailasam et al. (1997a, b). Hushin-Shtrikman bounds for cylindrical voids with circular cross section. Taking the limit as the shape of the voids and distribution becomes cylindrical with circular cross section, the following result (Suquet, 1992) is obtained

where the axis of symmetry has been taken to be aligned with the x3 direction.

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Pedro Ponte CastaZeda and Pierre Suquet

Hashin-Shtrikman boundsfor cracked solids. Another important case of the general result (7.6) is when one of the aspect ratios of the voids tends to zero, leading to cracks. (Note that d2)+ 0 in this case.) When the cracks are penny shaped, aligned, and distributed isotropically (in space), the following upper bound is obtained:

(7.8) = $nn(2)a3is a crack density parameter corresponding to n ( 2 )cracks where d2) of mean radius a per unit volume. The corresponding results for "flat" distributions of cracks (when the crack interactions are weak), which are obtained by linearizing (with respect to a ( 2 )the ) above result, were first given by Suquet (1992) and Talbot and Willis (1992). When the cracks are randomly oriented and distributed isotropically, the following upper bound is obtained:

which is due to Ponte Castaiieda and Willis (1999, in the linear context.

Self-consistent estimates. Making use of the self-consistent (SC) estimates of Hill (1965b) and Budiansky (1965), it follows (Ponte Castaiieda, 1991a) that expression (7.3) provides an estimate for Weff with (7.9) Note that the result is a rigorous upper bound for the special microstructure that attains the linear self-consistent estimate.

Beran third-order bounds. Finally, making use of the Milton (1982) simplified form of the McCoy (1970) third-order bounds for linear elastic composites, it is straightforward to derive the following third-order upper bound for porous materials with statistically isotropic microstructures

Bounds of this type for nonlinear composites were first proposed by Ponte Castaiieda (1992a) (see also Ponte Castaiieda, 1997b). Note that when the third-order

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24 1

parameters (('1 and ~ ( ' 1are equal to 1, this result reduces to the HS upper bound ( 7 3 , but is generally tighter than (7.5) for other values of {('Iand q ( ' ) .

2. Second-Order Estimates As the second-order theory of Ponte Castaiieda (1996a) is very recent, not many results are currently available. However, counterparts of the HS estimate (7.5) and the SC estimate (7.9) are available for incompressible-matrix porous materials with statistically isotropic microstructures (or isotropic distributions of spherical pores), provided that the pores are additionally assumed to be incompressible, so that the composite is incompressible ( E m = 0). Thus these results physically correspond to the case where the pores are saturated with an incompressible fluid. Assuming isotropic behavior for the matrix phase, as characterized by the function f ( l ) in relation (5.41) (with k(') + oo),the second-order estimate (5.32) for the fluid-saturatedporous materials may be written in the form

(7.10)

+

where E ( ' ) = (1 c(')w)E is obtained from the consistent estimate (5.40) for the average strain in the matrix phase.

Hashin-Shtrikman estimatesfor statistically isotropic microstructures. Using the HS estimate (6.4) for the linear comparison porous material with (anisotropic) matrix modulus tensor given by (5.43), one obtains an estimate of the form (7.10) with

where r ( ' ) = p ( ' ) / A ( ' )and , where the function a , arising from the relevant P(O) tensor, is given by expression (C7) in Appendix C. Note that a depends on the material properties, through r ( ' ) ,as well as on the third invariant of the strain, through the variable 8 (recall from Appendix C that cos(38) = 4 det(Ed)). It is important to emphasize that the second-order estimates for statistically isotropic microstructures depend on the third invariant of the strain, whereas the corresponding variational bounds of Section IV do not.

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Pedro Ponte Castaiieda and Pierre Suquet

Selj-consistent estimates for statistically isotropic microstructures. Proceedtensor in (6.4) now ing similarly, but taking into account the fact that the depends on the anisotropy of L(O) = Leff= 2heffIE 2peffF,one arrives at

+

w =-

[

-

1 c(2)a(8,

- seff

~

r ( ' ) a(6,sef f ) - seff

I' -1

where serf= peff/heffis obtained as a function of r ( * )and c(l) from the solution of the equation [seff

-

a(8,Seff)c(')] = r ( ' ) [ l- / 3 ( ~ , eff>c( 2 )

1 9

where the function /3, also defined by the corresponding tensor, is given by expression (C8) in Appendix C. Note that depends on r ( ' ) and 8. The above second-order estimates of the HS and SC types are due to Ponte Castaiieda (1996a) and Ponte Castaiieda and Nebozhyn (1997). Note that the above HS estimates also can be used to model the effective behavior of materials with dry pores under purely deviatoric loading conditions (with zero hydrostatic strain). However, the above SC estimates cannot be used to model nonhydrostatic loading of dry pores-in particular, the percolation limits of the saturated and dry pore problems are known to be different. (This is a well-known fact for linear-elastic composites.) Some preliminary results for hydrostatic loading of porous materials (with dry pores) have been given very recently by Nebozhyn and Ponte Castaiieda (1997). Making use of the (2-D) expressions (C10) for a and /3, instead of (C7) and (CS), the above formulae can also be used to obtain estimates for the plane strain transverse shear of a (fluid-saturated) porous material with aligned cylindrical pores.

3. Sample Results for Power-Law Porous Materials Purely deviatoric loadings. Figure 2 shows a comparison of the HashinShtrikman-type variational bounds (7.5) and second-order estimates (7.1 1) for statistically isotropic porous materials. The behavior of the (incompressible) matrix is characterized by the power-law relation (2.7), so that for purely deviatoric loading conditions (Em = 0), the effective potential Weff can be written in the form

Weff(E) =

m+l

(7.12)

where it is recalled that 6 depends on the determinant of the strain (6 = 0 corresponds to axisymmetric deformation, whereas 8 = 3r/6 corresponds to simple

243

Nonlinear Composites 1, . . . , . . . . . . . ,

. . .

I

. . .

I

0.8 -

0.6 -

0.4 -

0.2 -

n = 1000 U.0

F I G .2. Power-law porous materials with statistically isotropic microstructures. Various predictions for the effective flow stress for purely deviatoric loading as functions of the porosity c(*). Variational upper bounds (VB+) and second-order estimates (SOE) are shown. The Voigt upper bound VB+(V+) is microstructure independent. The upper hound VB+(HS+) was obtained by bounding the stiffness of the linear comparison composite by means of the Hashin-Shtrikman upper bound, and is valid for all isotropic microstructures. For the second-order estimate, the effective stiffness of the linear comparison composite was also estimated from the Hashin-Shtrikman upper bound and results are given for uniaxial tension (0 = 0) and simple shear (0 = n / 6 ) .a) n = 10. b) n = 1000.

~0"~'.

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Pedro Ponte CastaAeda and Pierre Suquet

shear). Results are shown, in Figure 2, for two values of the power-law exponent n = l/rn equal to 10 and 1000. It can be seen that the second-order estimates (SOE) generally lie below the variational bounds (VB). It can also be seen that although the variational bounds are independent of the type of loading, the corresponding second-order estimates are different for the extreme cases of uniaxial tension (0 = 0) and simple shear (0 = n / 6 ) , with the shear results always lying below the tensile results. Note that the difference between the shear and tensile results becomes progressively larger, as the level of nonlinearity increases, with the second-order estimates remaining close to the variational estimates for tension, but with the second-order estimates predicting sharper drops in the load-carrying capacity of the porous material in shear. As first pointed out by Drucker (1959), this sharper drop for large values of n (tending to perfectly plastic behavior) is possible under shear loading because of the availability of localized deformation modes (i.e., slip bands) passing through the pores. There is also experimental evidence for this type of behavior (see Spitzig et al., 1988). On the other hand, for the axisymmetric deformation mode, the plastic deformation is diffuse through the matrix (see Duva and Hutchinson, 1984), and there are relatively small differences between the variational and second-order estimates (see Ponte Castaiieda, 1996a, for more details). It is emphasized that the second-order procedure has the capability of capturing more accurately the anisotropy of the localized deformation fields by means of the use of the anisotropic tangent modulus tensors (see Ponte Castaiieda, 1992a, for more details). Hydrostatic predictions. For hydrostatic loading conditions (E,, = 0), the Hashin-Shtrikman (HS) variational bounds (7.5) for the power-law porous materials can be written in the form

(7.13) where miff = (1 - c(~))(c(~))-('+,')/'. This result is a rigorous upper bound for all isotropic microstructures, including isotropic distributions of spherical pores. (Note that 0:" + 00 as c ( ~-+) 0, which makes sense because the matrix material has been assumed to be incompressible.) From the exact solution of the problem of a spherical shell subjected to hydrostatic loading (see, for example, Budiansky et al., 1982), an alternative bound can be constructed for composite-sphere (CS) types of microstructures. The result is

Note that this result coincides exactly with the HS bound when rn = 1, in which case the CS microstructure is known to attain the HS bound. However, for any

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245

other value of in, the CS bound is always sharper than the HS bound. For example, in the limit as m + 0, the HS bound approaches (1 - c ( * ) ) / G ,whereas the CS bound approaches - In d2).It is noted that these two estimates can give very different predictions for dilute porosity levels (as d2)+ 0). Although it is reasonable that the CS bound should be sharper than the HS bound (because it applies for a very special type of statistically isotropic microstructure), it is important to note that the variational procedure can also be used to obtain a bound for the CS microstructure; unfortunately, the resulting bound is exactly the same as the HS bound above. The reason for the relative weakness of the HS bound is related to the fact that, for hydrostatic loading, the exact strain field in the CS microstructure varies as r P 3 (with Y denoting the radial coordinate), so that the exact secant modulus for this type of loading varies as r3(1-n')/2.Therefore, for an isolated void in an infinite matrix, the exact secant modulus can vary all the way from small values, in the vicinity of the void surface, to large values, far away from the void surface. It is thus seen that the approximation of a constant secant modulus in the matrix cannot be very good in this case. Fortunately, this is a very special type of situation; more typically, as, for example, for shear loading of a porous material, the secant modulus exhibits a narrower range of values-except in the vicinity of corners and other singularities, where the strains can get large locally (i.e., in regions of small volume)-and therefore the approximation of piecewise constant (by phase) secant modulus is more sensible in general. Of course, the advantage of the variational (and second-order) estimates is that they can be applied equally well for other, more general situations for which exact solutions-like the one for hydrostatic loading of a spherical shell-are not available. In the specific context of rigid perfectly plastic porous materials, a model that makes use of the exact solution for hydrostatic loading of a spherical shell was advanced by Gurson (1977). Of course, this model is very good for hydrostatic loading conditions, but it has been found to violate the HS bound (7.5) for purely deviatoric loading conditions (see Ponte Castaiieda, 1 9 9 1 ~Leblond ; et al., 1994). It is also restricted to pores of spherical shape, whereas the variational bounds can also be used for general nonspherical pore shapes (see Ponte Castaiieda and Zaidman, 1994). Analytical extensions of the Gurson model for aligned spheroidal pores have been given recently by Golaganu et al. (1993, 1994) and by Girirjeu (1996) following the work of Lee and Mear (1992a). An example of a porous material that is not statistically isotropic is provided by the periodic hexagonal patterns of voids considered in unit cell studies for creeping solids (Van der Giessen et al., 1995). Nonlinear self-consistent schemes for porous materials have been proposed by Michel and Suquet (1992) and Michel(l994).

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Pedro Ponte Castaiiedu and Pierre Suquet B. RIGIDLYREINFORCED MATERIALS

In this section, composite materials with isotropic nonlinear matrix phases reinforced by a rigid phase are considered. As in the previous example, the phase strain and stress potentials will be taken to be of the form (2.4) and (2.5). Some selected bounds and estimates for the corresponding effective potentials Weff and Ueff are given below.

1. Variational Bounds and Estimates Because of the assumed isotropy, the results of Section IV.C.2 for composites with isotropic constituents can be used to obtain bounds for the effective potential Weff of rigidly reinforced composite materials. Labeling the matrix as phase 1 and specializing eq. (4.56), one obtains the following bound for Ueff:

(7.14) where

(7.15) and where the first equation must be solved for

a

with

Use of any lower bound or any estimate for the effective compliance tensor of a rigidly reinforced composite with an isotropic matrix then leads to corresponding lower bounds and estimates for the effective stress potential of nonlinear rigidly reinforced composites. When the matrix phase is additionally assumed to be incompressible ( k c ' )+ co),the resulting composite is also incompressible and the corresponding estimates for We"' and Ueff can be written in the form (7.3), (7.4), with E,, = 0, in terms of appropriate microstructural tensors i and = i-' . Some bounds and estimates for Weff and/or Ueff are listed below in terms of the variables g,!:' and/or respectively (the matrix being assumed to be incompressible).

a$,),

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247

Hashin-Shtrikman estimates for ellipsoidal inclusions distributed with ellipsoidal symmetv. In this case, the HS estimates (6.6) of Ponte Castaiieda and Willis ( 1995) for ellipsoidal rigid inclusions distributed with ellipsoidal symmetry are lower and upper bounds for Liff and M8ff,respectively. Because of this fact, the expressions (7.3) do not yield rigorous bounds for Weff andlor Ueff, respectively. However, as mentioned earlier, the HS estimates (6.6) can be interpreted as appropriate variational estimates for particulate microstructures, and for this reason the corresponding nonlinear results can be interpreted as appropriate variational estimates for particulate microstructures. Thus expression (7.3), with the inequality replaced by an equality (in the sense of an approximation), gives estimates for Weff andor Ue“. The result is given by expressions of the form (7.4) with (7.16) where c(’)P= Pj - c(*)Pd.For spherical particles, distributed with statistically isotropic symmetry, the following estimate is obtained: (7.17) This “lower” estimate was proposed by Ponte Castaiieda (1991b, 1992a) for isotropic rigidly reinforced composites and generalized by Talbot and Willis (1992) for anisotropic composites. Talbot and Willis (1992) and Li et al. (1993) gave results for aligned spheroidal inclusions. GWjeu and Suquet (1997) have recently given an application to rigidly reinforced materials, where the matrix is taken to be of the Gurson type. Hashin-Shtrikman bounds for statistically isotropic microstructures. In this case, the HS upper bounds for linear elastic composites with arbitrary statistically isotropic microstructures are unbounded, and therefore the corresponding upper bounds for Weff are also unbounded. Physically, this corresponds to the fact that statistical isotropy does not exclude the possibility of rigid material lines or surfaces extending from one end of the specimen to the other, i.e., percolation. However, when the microstructures are additionally assumed to be particulate in character (which excludes the possibility of percolation, at least for small enough volume fractions of inclusions), it is possible to obtain finite upper bounds for the effective modulus tensor of rigidly reinforced composites. Thus linear HashinShtrikman bounds of this type were obtained by HervC, Stolz, and Zaoui (HSZ) (199 1) for composite-sphere assemblages and more generally for morphological patterns by Bornert et al. (1996). More recently, Bornert (1996) pointed out that in

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Pedro Ponte Castaiieda and Pierre Suquet

fact the (lower) bounds for composite-sphere assemblages can also be interpreted as rigorous bounds for composites with the larger class of particulate microstructures considered by Ponte Castafieda and Willis (1995). When both the shapes of the rigid inclusions and the distribution are spherical, the upper bound can be computed explicitly from the corresponding linear bound (6.7) of Hashin (1962) and H e r d et al. (1991) (they are identical in this case) and is given by

This nonlinear HSZ bound for statistically isotropic rigidly reinforced materials with composite-sphere assemblage microstructures was first obtained by Suquet (1993a), directly from (4.57). Hashin-Shtrikman estimates for jiber-reinforced composites. Taking the shape of the inclusions and distribution to be cylindrical with circular cross section in the general result (7.16), the following result (Li et al., 1993) is obtained:

where the axis of symmetry has been taken to be along the x3 direction. Note that this composite is inextensible along the fiber direction and can only undergo shear in the transverse and longitudinal directions. Hashin-Shtrikman estimates for rigid disks. Another important case of the general result (7.16) is that in which one of the aspect ratios of the rigid inclusions tends to zero, leading to disks. (Note that c ( ~ + ) 0 in this case.) When the disks have circular cross section, and are aligned and distributed isotropically, the following result is obtained:

where = is the disk density parameter corresponding to n(2)disks per unit volume of mean radius a. The corresponding results for “flat” distributions of disks (when the disk interactions are weak) are obtained by linearizing the above results and were first given by Talbot and Willis (1992) and Li et al. (1993).

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When the disks are randomly oriented and distributed isotropically, the following result (Ponte Castaiieda and Willis, 1995) is obtained:

Self-consistent estimates for statistically isotropic microstructures. Making use of the self-consistent estimates of Hill (1965b) and Budiansky (1965), it follows that (Ponte Castaiieda, 1991a) (7.20)

Beran third-order bounds for statistically isotropic microstructures. Finally, making use of the Milton (1982) simplified form of the McCoy (1970) thirdorder bounds (6.9) for linear-elastic composites, it is straightforward to derive the following third-order estimates for rigidly reinforced materials with statistically isotropic microstructures:

Note that when the third-order parameters <('I and q ( ' ) are equal to 1, this result reduces to the Hashin-Shtrikman estimate (7.17). Because for these values of < ( l ) and q ( ' ) ,the Beran upper and lower bounds coincide, the above result is a rigorous upper bound for nonlinear composites with values of the Milton parameters ( ( I ) and q ( ' ) equal to 1. It was mentioned earlier that the HS estimate (7.17) was a valid estimate for particulate statistically isotropic microstructures. The above argument shows that it is a rigorous upper bound for the subclass of particulate statistically isotropic microstructures with Milton parameters set equal to 1.

2. Second-Order Estimates Once again, not many second-order estimates are currently available for rigidly reinforced composites, but counterparts of the HS estimate (7.17) and the SC estimate (7.20) for statistically isotropic microstructures (or isotropic distributions of spherical voids) have been derived recently by Ponte Castaiieda (1996a) and Ponte Castaiieda and Nebozhyn (1997), respectively. Assuming isotropic, incompressible behavior for the matrix phase, as characterized by the function f ( l ) in relation (5.41), second-order estimates of the HS and SC types for rigidly reinforced composites are given below.

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Pedro Ponte Castaiieda and Pierre Suquet

Hashin-Shtrikman estimatesfor statistically isotropic microstructures. Using the relevant HS estimate for the linear comparison composite with matrix modulus tensor L(')given by (5.43) to obtain, via (5.40), a corresponding estimate for the average strain in the matrix of the nonlinear composite, the estimate (5.32) simplifies to

where r ( l ) = p ( ' ) / A ( ' )and where the function a is given by expression (C7) in Appendix C. Note that this result depends on the third invariant of the strain through the variable 0. Self-consistent estimatesfor statistically isotropic microstructures. Similarly, using the pertinent SC estimate for the linear comparison composite and taking into account the anisotropy of the IL(') and P (') tensors, one arrives at the result

is obtained as a function of r ( l )and c ( ' ) from the solution where seff= peff/Aeff of the equation

where the function j3 is given by expression (C8) in Appendix C. Making use of the (2-D) expressions (C10) for a and j3, instead of (C7) and (C8), the above formulae can also be used to obtain estimates for the plane strain transverse shear of a fiber-reinforced composite.

3. Sample Results for Power-Law Materials For rigidly reinforced power-law materials with effective potential of the form (7.12), Figure 3 shows comparisons of the dilute coefficients y , such that

Nonlinear Composites

25 1

2.5

Y 2

1.5

1

0.5

0

.

0

* / I

,

I

I

0.2

,

I

,

I

,

,

0.4

,

I

0.6

,

I

,

I

0.8

,

,

,

1

2.5

Y 2

1.5

1

0.5

0

(b)

I /n

FIG.3, Power-law material containing rigid inclusions at dilute concentration. Effective strengthening coefficient y . a) Results for 3-D statistically isotropic microstructures. b) Results for 2-D statistically isotropic microstructures. The predictions of the variational bound (VB+) and the second-order theory (SOE) make use of the exact dilute (D) expression for the stiffness of a linear comparison composite containing rigid inclusions of spherical and cylindrical shapes, respectively. They are compared with the corresponding numerical results of He (1990) and Lee and Mear (1991) for 3-D axisymmetric tension, and Lee and Mear (1992b) for 2-D transverse shear of a fiber-reinforced composite. Note that the 3-D predictions for the SOE include three values of the loading parameter 8 , varying between . Vol. 44, uniaxial tension (Q = 0) and simple shear (0 = n/6).(Reprinted from J. Mecl?.P h ~ s Solids, P. Ponte Castafieda, Exact second-order estimates for the effective mechanical properties of nonlinear composite materials, 827-862, 1996, with kind permission from Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington OX5 IGB, UK.)

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Pedro Ponte Custuiedu and Pierre Suquet

obtained from the variational bounds (7.17) and second-order estimates (7.21), with the corresponding numerical estimates obtained from the solution of an isolated rigid sphere (or cylinder) in an infinite matrix (He, 1990; Lee and Mear, 1991, 1992b; see also Duva, 1984). The matrix behavior is characterized by the relations (2.7), and the dependence of y on the value of the power-law exponent n is explored. Note that the SC and HS estimates agree to first order in the volume fraction for dilute concentrations of spherical inclusions; i.e., they give the same predictions for y . Furthermore, it is emphasized that since the values of y are exact in the dilute limit (Einstein, 1906; Eshelby, 1957), the corresponding nonlinear results that are obtained from the variational procedures are rigorous upper bounds in this case. Predictions are shown for various values of the third invariant parameter 8, ranging between uniaxial tension (0 = 0) and simple shear (8 = n/6), for (3-D) statistically isotropic microstructures, as well as for transverse shear (2-D) of a fiber-reinforced composite with transverse isotropy. Also shown for comparison is the Reuss lower bound. The main observation is that the second-order estimates lie within the rigorous upper bound provided by the variational method and the Reuss lower bound. In addition, they are in fairly good agreement with the numerical simulations. In particular, for transverse shear, it is observed that the strengthening effect of the cylindrical fibers vanishes in the limit of perfectly plastic behavior. (A similar behavior is observed for the 3-D isotropic composites loaded in shear, but not in tension.) This is once again in agreement with Drucker's (1959) observations regarding the availability of localized deformation modes in shear (see Ponte Castaiieda, 1996a, for details). Figure 4 shows some predictions obtained by means of the variational estimates (7.3) and (7.4), together with (7.16), for the effective flow stress a;ff of power-law materials reinforced by statistically isotropic distributions of randomly oriented spheroidal particles. The particles are assumed to be rigid, at a fixed volume fraction d2)= 0.25. The results for .iffare plotted as functions of the aspect ratio of the inclusions w,for several values of the power exponent n. For n = 1, the results, of course, specialize to the corresponding linear-elastic results of Ponte Castaiieda and Willis (1995), which show that nonspherical shapes for the particles can have a significant effect on the effective stiffness of the composite. Both oblate (w < 1) and prolate (w > 1) shapes may lead to sharp increases in pgff, particularly when the shape of the particles is such that they tend to come into contact with one another (recall that the linear estimates of Ponte Castaiieda and Willis, 1995, are based on the assumption of no overlap for the inclusions, which in the present case implies the restriction that 0.25 < w < 2.) For other values of n, similar observations may be made for the effect of w on with the only difference that increasing nonlinearity ( n ) tends to reduce the magnitude of the

atff,

25 3

Nonlinear Composites

1

0.1

10 w

1

F I G . 4. Power-law materials with statistically isotropic distributions of randomly oriented rigid particles. Predictions of the variational procedure for the effective flow stress as functions of the aspect ratio w of the spheroidal inclusions, for values of n = 1, 3, 10, m. The volume fraction of inclusions is d2)= 0.25. (The results are rigorous upper bounds for 0.25 iw < 2.)

.iff

strengthening effect in relative terms. Finally, note that second-order estimates are not yet available for the case of randomly oriented inclusions and therefore could not be shown in the figure. C. TWO-PHASE, RIGIDPERFECTLY PLASTIC COMPOSITES Another class of nonlinear composites for which some explicit analytical results are available is for two-phase rigid perfectly plastic composites with isotropic constituents. In this case, the relevant nonlinear equations for the comparison moduli or reference strain in the phases can sometimes be solved exactly. 1. VariationalBounds and Estimates

Consider a two-phase composite with isotropic, ductile phases governed by the Von Mises criterion, aeq(X)

5a ; ' )

in phase r.

(7.22)

The variational representation (4.34) can be used to derive explicit results for some cases of interest.

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Pedro Ponte Castanleda and Pierre Suguet

Isotropic composites. When the composite has overall isotropy, the dissipation potential Weff depends only on the second and third invariants of the strain and, because of homogeneity, can be written in the form

Weff(E) = aiff(6)Eeq,

(7.23)

where 6 depends on the determinant of the normalized deviatoric strain, as already mentioned. In the context of the variational procedures of Section IV, the use of a piecewise constant shear modulus ,uo(x) in (4.34) leads to the following upper bound for 0;ff:

Note that his upper bound is independent of 6 and therefore of the third invariant. of isotropic two-phase Rigorous upper bounds for the effective flow stress composites can then be obtained by incorporating upper bounds for the effective shear modulus peffof the linear comparison composite in (7.24). Examples of such rigorous upper bounds are given by the Hashin-Shtrikman upper bound for general isotropic microstructures and by the HervC-Stolz-Zaoui upper bound for isotropic composite sphere assemblages. The infimum in (7.24) can be computed analytically for the case of the Hashin-Shtrikman upper bound. For the case of the composite sphere assemblage, the rigorous upper bound of HervC-Stolz-Zaoui can be used in (7.24), but the infimum must be evaluated numerically.

atff

Hashin-Shtrikman boundsfor statistically isotropic microstructures. Assuming that 0;’) 3 a:’’ for definiteness, the Hashin-Shtrikman upper bound reads (Ponte Castaiieda and deBotton, 1992; Suquet, 1993a; Olson, 1994)

where d is the dimension of the space (3 in this case). Hashin-Shtrikman estimates for spherical inclusions distributed with statistical isotropy. Estimates for the effective flow stress of the composite can also be obtained by using estimates for peffappropriate to the class of microstructure under consideration. When the estimate for peffis accurate within the class of microstructure under consideration for arbitrary contrast p ( l ) the resulting expression for oiffis likely to be an upper bound for this class of microstructures. For instance, the Hashin-Shtrikman lower bound is appropriate for describing the effective shear modulus of dispersions of spherical inclusions (phase 2) in

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255

a matrix (phase 1) at moderate volume fractions of inclusions. (In fact, as has been mentioned already, it is a rigorous upper bound for composites with Milton parameters { ( I ) and q ( l ) equal to 1.) When used in (7.24), the optimization procedure can be carried out analytically. Assuming that 1 a0’”,the estimate for the overall flow stress resulting from this calculation is (Ponte Castafieda and deBotton, 1992)

00”

when

and

when

(7.27) These expressions, which can be interpreted as approximate estimates for composites with general particulate microstructures, are indeed upper bounds for composites with those microstructures for which the Hashin-Shtrikman lower bound for peffis exact (e.g., sequentially laminated composites). Note that the estimate (7.27) predicts that the strengthening effect of the inclusions (when the inclusions are stronger than the matrix) saturates after a certain finite increase in the strength of the inclusions. This is a consequence of the non-hardening character of the matrix phase, which would be expected to carry all the deformation, for sufficiently strong (but still non-rigid) particles.

Exact result for laminated composites. As already mentioned, for laminated composites, the fields are constant in each phase, so that the approximations made in the Hashin-Shtrikman and variational procedures are exact. Therefore, application of the variational procedure, together with the HS estimates for laminated materials, leads to the exact result,

Pedro Ponte Castaiieda and Pierre Suquet

256

where C, = 43[lX . nI2 - [n . (X . n)I2] corresponds to longitudinal shear and

Cl =

,/-

(n is the normal to the layers). This result is originally due

to de Buhan (1983), who derived it using limit analysis. The derivation of this result (as well as of corresponding results for more general nonlinear laminates), using the variational procedure, was carried out by deBotton and Ponte Castaiieda (1992) and Suquet (1993a).

Hashin-Shtrikman bounds and estimates for unidirectional composites with transverse isotropy. For unidirectional composites with transverse isotropy (or for fiber-reinforced composites with circular fibers of phase 2 distributed isotropically), the expression for the effective yield function reduces to

where y ( l ) denotes the ratio p t ) / p f ) and where the tensor = pf)Mbff is the (normalized) effective compliance of the fiber-reinforced linear comparison composite with incompressible and isotropic phases. In general, this result requires numerical computation, but for transverse and longitudinal shear, the result simplifies to expressions of the form (7.25) and (7.26, 7.27) with d = 2. Similarly, for (axisymmetric) uniaxial tension, the following result is obtained:

which agrees with the Voigt estimate. These results are due to Ponte Castaiieda and deBotton (1992) and Moulinec and Suquet (1995) (see also deBotton, 1995). More general results for particle-reinforced composites have been given by Ponte Castaiieda and Zaidman (1996), and Kailasam et al. (1997a,b). 2. Second-Order Estimates For two-phase, rigid perfectly plastic composites with statistically isotropic microstructures (or with isotropic distributions of spherical particles of phase 2 in a matrix of phase I), the second-order estimates (5.32) for Weff can be simplified.

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257

The result can also be written in the form (7.23), where the effective yield strength is given by

and

In these relations, C is the integral (C9) obtained in the derivation of the P tensor in Appendix C, evaluated at riO) = 00. Note that these results, which are due to Ponte Castaiieda (1996a), therefore depend on the third invariant of the strain, as measured by 8 . Also note that these results agree exactly with the corresponding second-order, small-contrast expansion of Suquet and Ponte Castaiieda (1993)

For simple shear loading conditions (recall that C(8, 00) + 00 as 0 + n / 6 ) , the above results specialize to

An identical result is obtained for fiber-reinforced microstructures with transverse isotropy loaded in transverse shear. It is emphasized that the small-contrast expansion above diverges for simple shear loading, whereas the corresponding second-order estimate does not diverge, as just seen.

3. Discussion Statistically isotropic microstructures. The dependence of the various bounds and estimates on the volume fraction of the inclusions is examined in Figure 5a, ~ 5. ” First of all, note that as d2)+ 1, for a given value of the ratio c ~ ” / c T= some of the predictions do not tend, as might be expected, to the flow stress of

25 8

Pedro Ponte Custunledu and Pierre Suquet 5

3

2

1.15

1.1

1 .os

I

FIG.5 . Bounds and estimates for the effective flow stress of rigid ideally plastic composites. The variational bounds of Voigt VB+(V+) and Reuss VB-(R-) are rigorous upper and lower bounds valid for all microstructures. The variational upper bound VB+(HS+) deduced from the HashinShtrikman upper bound is valid for all isotropic microstructures, whereas the variational bound VB+(HSZ+) is a rigorous upper bound for all isotropic composite sphere assemblages. The variational estimate VE(HS-) deduced from the variational theory using the Hashin-Shtrikman lower bound for the linear comparison composite is an estimate for particulate-type microstructures with the hard phase in the matrix. The two second-order estimates (SOE) shown correspond to particulate microstructures with the hard phase dispersed in the soft phase (HS-), and with the soft phase dispersed in the hard phase (HS+), and are given for uniaxial tension (0 = 0) only. a) Effective flow stress no"" as a function of the volume fraction d2)of the hard phase for a given ratio of the contrast = 5. b) Effective flow stress as a function of the contrast n ; ' ) / ~ ; ' )for a given volume fraction of hard phase c ( ~ )= 0.15.

a(j2)/0;')

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259

phase 2. That the Reuss lower bound predicts no effect of the inclusions on the flow stress of the composite is consistent with Drucker’s (1959, 1966) remark that in a rigid perfectly plastic composite, if a shear plane can be passed through the weakest phase, then the shear strength of the composite is the shear strength of the weakest phase, regardless of the volume fraction of the phases. (This result suggests that surfaces can play a significant role in plasticity.) When the condition of statistical isotropy is dropped (as appropriate for the Reuss bound), a Druckertype construction can easily be made, at any volume fraction (e.g., a laminate). On the other hand, when the additional hypothesis of overall isotropy is made, it is not clear that such constructions can be made at any volume fraction and for any loading condition. (In this context, it is noted that the second-order estimates give two different predictions for uniaxial tension and simple shear, with tension showing overall strengthening and shear showing no strengthening and thus coinciding with the Reuss lower bound. This suggests that, still within the context of isotropic microstructures, the Reuss lower bound may be optimal for simple shear loading conditions, whereas it may not be for other more general loading conditions. Although a little surprising at first, perhaps this remark is not so unexpected, in view of the strong dependence of the results on the third invariant for rigid perfectly plastic composites.) Next note that the prediction deduced from the HS upper bound by the variational procedure provides an upper bound for all statistically isotropic microstructures. On the other hand, the prediction derived from the HS lower bound only gives an estimate for particulate microstructures with the stronger material in the inclusion phase. These estimates are likely to overestimate the effective yield strength of such composites, at least for low to moderate volume fractions. The prediction deduced from the upper bound of HervC, Stolz, and Zaoui (HSZ) shows that the flow stress in any assemblage of composite spheres does not tend to the flow stress in phase 2 when the proportion of phase 2 tends to 1. This result is therefore valid for all microstructures in the corresponding class. This effect is typical of perfect plasticity, as already mentioned. In the present situation, although the volume fraction of the matrix tends to 0, its “surface” (which reduces to the surface of the spheres of phase 2) does not tend to zero. Also shown in Figure 5b are plots of the various bounds and estimates as functions of the ratio a o ( * ) / ~ ~at~a) fixed value of d2). In addition, in this figure the FEM unit cell calculations of Suquet (1993a) for particle-reinforced composites are also plotted for comparison purposes. It is observed that although the two types of nonlinear estimates obtained from the linear HS lower bound exhibit the same general trends, the second-order estimates are in closer agreement with the numerical results. Also note that the variational estimates lie above the numerical results. This is consistent with the fact that the variational estimates are expected

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Pedro Ponte CastaAeda and Pierre Suquet

to overestimate the effective yield strength of the composite at this moderate level of the volume fraction of inclusions. Finally, the nonlinear estimate obtained from the linear HS upper bound lies below the microstructure-independent Voigt upper bound, and is such that the second-order estimate lies below the variational estimate, which is, of course, known to be a rigorous bound for all statistically isotropic microstructures.

Fiber-reinforced composites with transversely isotropic microstructures. In this subsection, numerical simulations by Moulinec and Suquet (1995) for the effective yield strength of fiber-reinforced composites are compared with the corresponding predictions (7.28) obtained from the variational procedure. The composites considered by Moulinec and Suquet consist of cylindrical fibers of phase 2, with circular cross section and aligned with the x3 axis, dispersed randomly in a matrix of phase 1. The overall stresses considered by these authors consist of the superposition of uniaxial tension and transverse shear C = Cll(e1 C3 el - e2 €3 e2)

+ C33e3 @ e3.

Various contrast ratios for the strengths of the two phases crFi/crA” were investigated: crA”/crJ’) = 0.5, 1.1, 2, 3, 5 , 10. For aO(*)/crJ’)= 2, the computations were performed with 11 different configurations. For the other ratios, the computations were performed on a single configuration representative of the average of the predictions over the whole set of configurations for C T ~ ~ ) / C T ~= ’ ) 2. More specifically, this configuration approaches transverse isotropy, and its overall straidstress response is close to the mean response of all configurations, both under multiaxial loading and under uniaxial tension. The results are shown in Figure 6. Note that the agreement between the numerical simulations and the variational estimates (7.28) is remarkably good. In particular, the variational estimates (7.28) capture rather well the “flat sectors” on the yield surfaces. Furthermore, for the cases involving sufficiently strong fibers, the shape of the observed extremal surfaces was found to be “bimodal” in character. Bimodal surfaces have been used by Hashin (1980), Dvorak and Bahei-El-Din (1987), and de Buhan and Taliercio (1991) (among other authors) to describe the initial yield or the flow surface of unidirectional composites. The numerical and variational results are consistent with these models and with experimental observations (Dvorak et al., 1988). The failure modes at the local level in the numerical simulations are shown in Plate 4. They reveal that the composite can fail in either of two possible modes, thus confirming more directly the bimodal character of the overall flow surface. The first mode (Plate 4a), observable for low values of the axial stress C33, corresponds to shear bands in the matrix with an inclination of approximately

Nonlinear Composites

26 1

c,,1 0;) 0.8 0.6 0.4 0.2 0 0

1

2

FIG. 6. Unidirectional composites with fibers aligned in the x3 direction. Extremal surface in the (Ell - C33) plane for different contrasts between the phases. The volume fraction of fibers is = 0.475. The overall stress is C = Ell(el 8 el - e2 8 e2) E33e3 8 e3. The comparisons are between numerical simulations (squares, circles, and crosses) for randomly isotropic configurations and the predictions of the variational method where the lower Hashin-Shtrikman bound is used for the linear comparison composite (from Moulinec and Suquet, 1995; Ponte Castaiieda and Zaidman, 1996) (Reprinted from Infernu?. J. Solids Structures, Vol. 33, P. Ponte Castaiieda and M. Zaidman, The finite deformation of nonlinear composite materials. I. Instantaneous constitutive relations, 1271-1286, 1996, with kind permission from Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington OX5 1GB,

+

UK).

f 4 5 " to the horizontal direction. When C33 reaches a threshold corresponding to the vertex of the flow surface (Plate 4b), the plastic zone spreads throughout the unit cell. As C33 is increased further (Plate 4c), the plastic strain tends to become more and more homogeneous, becoming fully homogeneous when C33 reaches ( D O ) (Plate 4d). The numerical calculations can also be used to propose a closed-form expression for the bimodal surface:

where k ( ' ) = D;"/& is the in-plane shear strength of phase 1, and k , is the in-plane shear strength of the composite. k , can either be fitted to the numerical simulations (Moulinec and Suquet, 1995), or be taken from the prediction of the variational procedure used with the Hashin-Shtrikman lower bound (Ponte Castaiieda and deBotton, 1992): k , = (1/&)aGff,where crtffis given by (7.26), (7.27) in dimension d = 2. In the second case, the agreement with the predictions of the variational procedure for the full yield surface is quite good.

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Pedro Ponte Custufiedu and Pierre Suquet

D. ADDITIONAL RESULTSA N D COMPARISON WITH OTHER SCHEMES Several other schemes have been proposed over the past 30 years to predict the overall effective behavior of nonlinear composites. Of these, two will be recalled here: they are the (classical) secunt method developed by Chu and Hashin (1971), Berveiller and Zaoui (1979), and Tandon and Weng (1988), and the incremental method originally proposed by Hill (1965a) in conjunction with the self-consistent scheme. A more detailed account of these two classical methods is given in Appendix D. Schematically, however, the secant method consists of writing the constitutive relation in phase r with the secant tensor of this phase, evaluated at the average strain Z ( r ) . Similarly, the incremental method amounts to writing the constitutive law of phase r in the form u = IL:r)(i(r)) : where I,:') is now the tensor of instantaneous or tangent moduli of the phase, given by the second derivative of the energy w(') with respect to the strain. The aim of the present section is to compare the predictions of the variational and second-order methods with those of the classical schemes, and to show, in passing, some of the shortcomings of the classical methods. 1. Statistically Isotropic Power-Law Composites

The case of two-phase, incompressible, power-law materials with the same exponent provides an interesting study case for comparing the different models. The case of particulate power-law materials has been considered by Ponte Castaiieda and Willis (1988) in the context of the Talbot-Willis procedure, by Ponte Castaiieda (1991a) and Suquet (1993a) in the context of the variational method with a linear comparison composite, and by Ponte Castaiieda (1996a) in the context of the second-order procedure. Granular types of microstructures have also been considered in these references, as well as by Gilormini (1993, who compared the different methods using the self-consistent scheme to estimate the effective properties of the linear comparison composite. He pointed out that the predictions of the incremental and classical secant method can violate the rigorous variational upper bound for isotropic composites. Michel (1996) has proposed a nonlinear extension of the self-consistent scheme for pure power-law materials. A comparison is made here for two-phase composites with particulate microstructures. Both constituents are characterized by relation (2.7) with the same exponent m but different flow stresses a$'. It is assumed that the composite is made of inclusions of phase 2 randomly dispersed in a softer material, phase 1, playing the role of a matrix. If the volume fraction of inclusions is moderate, the Hashin-Shtrikman lower bound (6.4) provides accurate estimates for the effective

Nonlinear Composites

263

linear properties of the comparison composites with the matridinclusion type of microstructure under consideration. As already mentioned, the composite is itself a power-law material with the same exponent as the individual phases, and is, in addition, incompressible. Under the assumption of statistical isotropy, the effective potential is consequently a function of the second and third invariant of the strain E and, by homogeneity, can be written in the form

Weff(E) =

(7.30)

m+l

where it is recalled that f3 is related to the (normalized) traceless strain E by cos(38) = 4det(E). Note that the variational bounds established in Section IV for power-law materials provide bounds for that are independent of the parameter 8, whereas the estimates provided by the second-order theory do depend on this parameter.

otff

Variational method. The variational method provides upper bounds or estimates of the flow stress 0;“‘ for power-law materials by solving the onedimensional optimization problem (4.57) directly, as was done in Section VI1.C. But as already pointed out, the variational method is also a modified secant method in which the secant modulus in each phase of the linear comparison composite is given by the second moment of the equivalent strain in this phase. With the purpose of illustrating this fact, the secant formulation will be used here to derive numerically the flow stress .iff.The secant tensors):LI can be expressed in terms of the shear moduli p r ) .By homogeneity, the nonlinear equations (4.55) for the secant moduli in the linear comparison material reduce to a single scalar equation for the ratio p f ’ l p f ’ , namely,

When the effective shear modulus p8ffof the comparison solid is estimated from the Hashin-Shtrikman lower bound, the first equation can be rearranged to give

where p = 2/(2+d), d being the dimension of space (d = 2 or 3). Equations (7.31) and (7.32) can be solved numerically for the ratio p f ’ l p f ) of the secant moduli in the individual phases. Once this ratio is known, the sec-

264

Pedro Ponte Castafiedu and Pierre Suquet

zd:’

z$),

ond moments of the strain in each phase, and are determined as functions of the ratio p f ) / p t ) ,by relations (4.54). In turn, the local moduli ( r ) = (1/3)ff$r)(z(r) eq )VI - 1 and the overall secant modulus j ~ $are~ then deterPO

mined. Finally, the overall flow stress is given by

otff= ~ , L L ~ ~ E & ~ .

Classical secant method. Again, by homogeneity, the nonlinear equations for the secant moduli in the linear comparison material reduce to a single scalar equation for the ratio p f ) / p t ) ,but this ratio is now estimated with the first moment (instead of the second moment) of the strain in each phase:

When the Hashin-Shtrikman lower bound is used, this equation can be rearranged into (7.34) (2)/p,, (1) . which can be transformed in an equivalent nonlinear equation for po

Second-order method. Given the definition (5.41) of the functions f “ ) , the second-order estimate (5.32) for two-phase, isotropic, incompressible composites may be written in the form

Weff(E)= c ( l ) f ( l[( ) 1 + c(2)w)2E2 eq ] + ~ ( ~ ) f ( ~ -) C[( (’ )l ~ ) ~ E : ~ ]

[ + d 2 ) w )( f ( ’ ) ) ’ [(1 + c(’)w)’E&]

- c(l)c(2)wE2 eq (1

(7.35)

1,

- (1 - ~ ( ‘ ) w ) ( f ( ~ ) ) ’ [ (l ~(l)w)”E:~]

where the estimates for the average strains in the phases have been assumed to be aligned with the average strain, such that E y ) = (1

+c(~)co)E~,

= (1 - c(’)w)Ed.

The variable w is determined by the nonlinear relation P(l) -

w=

P( 2 )

c(lI(h(2) - p(2))+ c ( 2 ) ( ~ ( 1-) p(1))+ c ( l ) c ( 2 ) ( h (l ) )~(2))2/(heff- ( h ) ) ’

which is obtained from relation (5.40), and where the moduli of the linear comparison composite kL(r) and h(‘) are determined by the expressions (5.44) and (5.43, respectively. This result is in agreement, of course, with the exact second-order

Nonlinear Composites

265

asymptotic expansion of Suquet and Ponte Castaiieda (1993),

where hp is defined in Appendix C. When the individual constituents are power-law materials with the same exponent m, this result simplifies further. In this case,

and using the Hashin-Shtrikman estimate for heff, together with l / h p = ( 2 / ( m l ) ) ( C / p ( ' ) )the , above expression for w reduces to

+

w=-

+ c(2)p(1)

c(l)p(2)

-

+ ( ( m + 1 ) / 2 ) ( p ( I ) / C' )

mp(1)

where C = C(8, m ) is given by expression ((29) of Appendix C. Note that C depends on the third invariant of the strain, as determined by 8. Then the overall flow stress glffis obtained from (7.30)and (7.39, with the result that

where w is defined by the above expression. Similarly, using the fact that = mp(O),the exact to second-order expansion (in the contrast) for the effective potential of the composite becomes

It is emphasized that while this small-contrast expansion diverges for simple shear (8 = n / 6 ) in the limit as n tends to infinity, the corresponding finite-contrast expression above never diverges and always gives physically meaningful results.

Incremental method. For incompressible power-law materials under monotonic radial loading, the incremental relations (D6) can be integrated exactly (Hutchinson, 1976)4into

X

1 m

= - Leff(E): E,

(7.36)

where Leffis the effective tensor of a linear composite, where phase r is given (') = lL.j"(E(')). Note that the tensors I,(') dethe anisotropic tangent stiffness L 4A more detailed proof is given in Suquet (1997a)

266

Pedro Ponte Castafieda and Pierre Suquet

pend on and therefore the determination of Leffrequires the resolution of N nonlinear tensorial equations, exactly as in the secant method. The incremental method for power-law materials reduces to a secant method, but where the secant tensors in each phase are anisotropic and are given by ( l / m ) L y ) . The nonlinear equation for the determination of the secant moduli are

where C is the constant defined by (C9). Note that it depends on the third invariant of E. These equations can be rearranged into

Discussion. The overall flow stresses predicted by the (classical) secant method, the variational method, the incremental method, and the second-order procedure are shown in Figure 7a. The applied overall stress is uniaxial tension. The contrast between the phases is g ~ ’ / “ ” = 8, and a value of n = 10 is considered. It is observed that the classical incremental and secant procedures lead to the stiffest predictions, whereas the more recent variational and second-order procedures lead to the more compliant predictions. In particular, recalling that the linear Hashin-Shtrikman lower bound is attained by certain specific particulate microstructures, it is noted that the variational estimates are actually upper bounds for the nonlinear composites with this specific type of microstructure. Therefore, it is observed that both the corresponding secant and incremental estimates violate this bound, whereas the second-order estimates do not. In fact, it is observed from this figure that the incremental estimates violate even the HS upper bound for statistically isotropic microstructures, at sufficiently large values of n ( m close to 0). This is rather unexpected, as this type of bound is known to correspond to the “opposite” type of microstructure, with the stronger material occupying the matrix phase. The observation that the incremental HS- estimate violates the HS+ bound is confirmed by the inspection of the case of rigid-plastic constituents, where it can be shown that, as m goes to 0, one has that lim mC(0, n = m-’) = 0.

m-0

267

Nonlinear Composites

,

,

o ~ ~ 0.2 ' " ' ' 0.4 " ' ' "0.6' ' " 0.8 ' ' "

-1.4 0

I

0.2

0.4

0.6

0.8

,

,

1

,

1

FIG. 7. Bounds and e5timates for statistically isotropic power-law composites. Effective flow stress as it function of the volume fraction c(') of the hard phase. Rigorous variational upper and lower bounds of Voigt (VB+(V+)) and Reuss (VB-(R-)), respectively. The rigorous upper bound VB+(HS+) is valid for all isotropic microstructures. The various estimates are deduced from the secant method (SE), the incremental method (IE), the variational method (VE), and the sccondorder theory (SOE). a) The estimates correspond to microstructures of particulate type, with inclusions of the hard phase dispersed in the soft phase, and are consequently evaluated with the lower Hashin-Shtrikman hound (HS-). Note that the incremental estimate violates the rigorous upper bound VB+(HS+). b) Same figure for the granular type of microstructures, where the effective properties of the linear comparison composites are evaluated by the self-consistent scheme (SC). Note that the incremental and secant estimates violate the VB+(HS+) upper bound. Both figures are for uniaxial tension (0 = 0).

Pedro Ponte Castaiieda and Pierre Suquet

268

Therefore (7.38) gives in this limit Ed:) = Ed:). From the average condition c(')E$) c(*)E$ = E,, (where it has been assumed that the average strain deviators in the phases are parallel to the average strain deviator in the composite), one then obtains Ed:) = E$) = Eeq. This implies that for rigid-plastic materials the incremental model reduces to the Voigt bound. A similar observation was made by Gilormini (1995) in the context of the selfconsistent estimate (instead of the Hashin-Shtrikman lower bound). The above result shows that the tendency of the incremental model to approach the Voigt bound (or Taylor model) when m goes to 0 is not due to the condition of selfconsistency but to the incremental procedure itself. Following Gilormini (1995), Figure 7b shows a comparison of the same homogenization methods as in the previous discussion, but using the linear self-consistent estimates (instead of the corresponding Hashin-Shtrikman estimates) to generate various types of estimates for nonlinear composites with granular microstructures. Once again, it is observed that the classical estimates tend to be stiffer than the more recent estimates, with both the incremental and classical nonlinear estimates violating the HS upper bound in this case. On the other hand, the second-order estimates are found, at this level of the contrast, to satisfy not only the HS bound for statistically isotropic microstructures, but also the stricter bound imposed by the SC estimate obtained by means of the variational procedure (recall that it is a rigorous bound for the class of microstructures attaining the linear SC estimate). Finally, it is emphasized that of all four nonlinear homogenization procedures, only the second-order procedure gives estimates that are exact to second order in the contrast of the phases. The other three (variational, classical secant, and incremental) give estimates that are exact only tojrst order in the contrast.

+

2. Rigid Inclusions in a Rigid Ideally Plastic Matrix Consider next a rigid ideally plastic matrix containing inclusions that are rigid and spherical. Several predictions are shown in Figure 8 and compared with the results of cell calculations obtained by the finite-element method (these results are taken from the work of Suquet, 1993a, but similar results were obtained earlier by Bao et al., 1991). The nonlinear rigorous HSZ upper bound overestimates the numerical results (as consistent with its status of an upper bound for all composite sphere assemblages). Again, the second-order theory is in very good agreement with the numerical results, at least for moderate volume fractions. A rapid increase in the flow stress is observed in the numerical calculations when the volume fraction of inclusions exceeds 0.2. This effect, which is not captured by the theoretical predictions, can be attributed to the difference in critical volume fractions for dense packing in the cell calculations and in the models. For identical spheres in a cylinder (cell calculations), dense packing is attained for c(*) = 0.66, and

Nonlinear Composites

269

FIG.8. Rigid-plastic material containing a randomly isotropic distribution of rigid spherical inclusions. Overall flow stress as a function of the volume fraction of rigid inclusions c(*). Comparison of various predictions obtained by the secant, variational, and second-order procedures with numerical results obtained by the finite element method (FEM). The secant (SE), variational (VE) and secondorder (SOE) estimates all use the lower Hashin-Shtrikman bound (HS-) to estimate the effective stiffness of the associated linear comparison composite. The variational upper bound (VB+) makes use of the Herve-Stolz-Zaoui upper bound (HSZ+) for isotropic composite-sphere assemblages. Also shown is the Reuss lower bound (V-(R-)).

.if'

the flow stress increases rapidly when the volume fraction approaches this critical value, whereas the dense packing of inclusions is 1 for the theoretical (HS-type) predictions. Finally, the predictions of the secant method (in its usual form) are also included for comparison. It is observed that they overestimate quite significantly the numerical predictions. The corresponding estimates of the incremental method become unbounded in this case and are therefore not shown.

3. Power-Law Polycrystals Polycrystalline materials undergoing power-law creep have been considered by Hutchinson (1976) in the context of the incremental method, by Dendievel et al. (1991) and Willis (1994) in the context of the Talbot-Willis procedure, and by deBotton and Ponte Castaiieda (1995) in the context of the variational method using a linear comparison composite. Using the translation method, Kohn and Little (1997) have also obtained some interesting results for certain model problems, including a generalization of the Keller result for two-dimensional symmetric polycrystals. Although comprehensive comparisons are not yet available,

270

Pedro Ponte CustuAedu and Pierre Suquet 3.2, . . .

, . . . , . . . , . . . ,

. .

.

,

m = I/n FIG.9. Bounds and estimates for power-law polycrystals. Effective flow stress as a function of the exponent of nonlinearity ni. Rigorous variational upper and lower bounds of Voigt (VB+(V+)) and Reuss (VB-(R-)) types, respectively, are shown highlighted by open triangles. VB+(HS+) is a rigorous upper bound for all isotropic polycrystalline materials. The rigorous upper bound of Dendievel et al. (1991) (squares) deduced from the Talbot-Willis variational principle and the prediction of the incremental model of Hutchinson (1976) (open circles) are also plotted for reference. Reprinted from deBotton and Ponte Castaiieda (1995) with kind permission from The Royal Society.

Figure 9 provides a comparison, for uniaxial tension, of these various estimates with the classical Taylor upper and Sachs lower bounds, as also determined by Hutchinson (1976) for power-law polycrystals. The crystals have been taken to have face-centered-cubic symmetry, and the polycrystal has been assumed to exhibit no texture. The dependence on the creep exponent m = l / n is studied. It is seen from this figure that the HS bounds of deBotton and Ponte Castafieda and Dendievel et al. (1991) yield very similar results, although the former results appear to be a little more restrictive than the latter. However, the HS upper bounds do not appear to improve very significantly on the classical Taylor bound, especially in the perfectly plastic limit, where they appear to approach the Taylor estimate. Furthermore, interestingly, the HS bounds are rather close to the SC estimates of Hutchinson (1976), which in turn also appear to approach the Taylor bound in the perfectly plastic limit. This last result is consistent with the earlier observation that the incremental SC estimate approaches the classical Taylor upper bound in the perfectly plastic limit. Again, keeping in mind the observations of the earlier subsection on power-law composites, it may have been expected that the SC estimates would violate the HS upper bounds in this case as well. However, that this

Nonlinear Composites

27 1

is not the case is probably explained by the fact that the HS bounds can be far from optimal for N-phase composites in general, and for polycrystals in particular. In this connection, it is relevant to mention that recent results (Ponte Castaiieda and Nebozhyn, 1998) for the model two-dimensional, ideally plastic polycrystals considered by Kohn and Little (1997) show that, at least for this special case, the HS upper bound is indeed quite weak relative to the Kohn-Little bound, especially for large grain anisotropy. On the other hand, new self-consistent estimates that have been obtained using the variational procedure of deBotton and Ponte Castaiieda (1995) not only show a significant improvement over the HS upper bound for large grain anisotropy, where they satisfy the Kohn-Little bound, but in addition the new self-consistent estimates provide an improvement over the Kohn-Little bound for small grain anisotropy, where they satisfy the sharper Taylor and HS bounds. Work is in progress to further clarify these points, as well as to compute second-order estimates for this important class of materials.

4. More General Types of Composites The various methods can be applied to predict the effective stress-strain response of composites comprising phases with more general behavior than pure power law. Several applications of the variational method to composites with at least one linear phase have been made. These include Ponte Castaiieda (1991b, 1992a) for elastic particle-reinforced composites, deBotton and Ponte Castaiieda (1992) for laminated materials, and Talbot and Willis (1991) and deBotton and Ponte Castaiieda (1993) for fiber-reinforced composites. Comparisons with FEM calculations were carried out by Li and Ponte Castaiieda (1993, 1994), Suquet (1993b,1996a), and Aravas et al. (1995) for particle- and fiber-reinforced, showing in general a good agreement between the predictions and the FEM results. Unfortunately, second-order predictions are not yet available for these more general classes of composites. Comparisons between the classical methods, the variational method, and FEM calculations is presented next.

Elastic particles in a power-law matrix. Comparisons can also been made when the phases are power-law materials with different exponents. The case of spherical linear-elastic inclusions in a power-law nonlinear matrix has been considered, for instance, by Suquet (1996a), which, in addition, illustrates the use of the generalized self-consistent scheme to evaluate the overall stiffness of the comparison solids. Because no explicit result is known (to the authors) for the generalized self-consistent scheme when the phases are anisotropic, the incremental estimate and the second-order estimate could not be used, and only the secant and the variational method are shown in Figure 10 and compared with numerical

272

Pedro Ponte Castafieda and Pierre Suquet

c

(1)

00

0.0

0.2

0.4

0.6

0.8

1.0

EI FIG.10. Two incompressible power-law materials following (2.7) with different exponents. Linear elastic particles dispersed in a nonlinear matrix. Data for the matrix (M): 0;'' = 1, n ( ' ) = 10 and for the particles (P):':0 = 5, = 1. Volume fraction of the inclusions is c ( ~ )= 0.3. Overall response of the composite subjected to uniaxial tension, as predicted by the secant estimate (SE), the variational estimate (VE), and FEM calculations on an axisymmetric cell. The effective stiffness of the linear comparison solid is evaluated with the generalized self-consistent scheme (GSC) for both theoretical estimates. Reprinted from Suquet (1996a) with permission of Kluwer Academic Publishers.

results obtained by cell calculations. The agreement of the variational estimate is seen to be very good, whereas the secant method once again significantly overestimates the stiffness of the composite. Metal-matrix composites with spherical reinforcement. The specific composite considered here consists of spherical elastic particles (phase 2) with material properties

E ( 2 )= 400 GPa,

v(*) = 0.2,

dispersed in a nonlinear matrix (phase 1) governed by a 52 deformation theory,

(7.39)

Nonlinear Composites

273

The material properties for the matrix are

E ( ' ) = 75 GPa, a y ( p ) = a0

+ Apa,

a0 = 75 MPa,

v ( l ) = 0.3,

A = 416MPa,

a = 0.3895.

The overall elastic stiffnesses used in the theoretical predictions were computed by the Hashin-Shtrikman lower bounds, the reference material being the matrix, with isotropic secant characteristics in the secant methods, and anisotropic tangent moduli in the incremental procedure. FEM calculations on an axisymmetric cell (similar in spirit to those of Bao et al., 1991) were performed using the flow theory (7.40) corresponding to (7.39). The applied loading is a uniaxial tension along the axis of symmetry of the cell. The results of the predictions are shown in Figure 11. As already noted, the prediction of the incremental procedure is excessively stiff. The two other schemes (classical secant method and variational estimate) are in good agreement with the FEM computations. The prediction of the variational estimate seems to slightly underestimate the stiffness of the composite. This is because the Hashin-Shtrikman lower bound was chosen to estimate the elastic properties of the linear comparison composite, which is expected to lead to an underestimate for the effective response of the periodic cell materials considered in the FEM simulations, at this

400 I

I

i

c

/

300

200

100 I I

0'

0.0

c'z'=0.3 0.02 E

I

0.04

FIG. I 1 . Metal-matrix composite under uniaxial tension. Spherical elastic inclusions dispersed in a nonlinear matrix. The pure matrix (M) is governed by a J2 deformation theory. The volume fraction of inclusions d2)= 0.3. Overall response of the composite, as predicted by the secant estimate (SE), the variational estimate (VE), the incremental estimate (IE), and the incremental model (7.42) (IM). The microstructure being particulate, the effective stiffness of the linear comparison solids is calculated with the Hashin-Shtrikman lower bound (HS-). Reprinted from Suquet (1997a) with permission of CISM.

274

Pedro Ponte Castaiieda and Pierre Suquet

volume fraction of inclusion. (As already mentioned, these cell materials percolate at 66% volume fraction of inclusions.) It is expected that better agreement between the numerical results and the variational estimate would have been obtained if the generalized self-consistent scheme had been used (as illustrated in Section VII.D.4). (Note that there is an additional result, denoted IM(HS-), in this figure, which will not be discussed until Section VILE.) Metal-matrix composites with aligned discontinuous reinforcement. The material system for this case is similar to that of the previous case, except that the reinforcement is not spherical in shape, but elongated in the form of “chopped fibers.” The fibers are aligned and distributed isotropically in the transverse direction, which leads to transverse isotropy for the composite. Following Christman et al. (1989), the elastic particles are compressible with = 450 GPa, u(*) = 0.17, their shape is cylindrical with aspect ratio w equal to 5, and they appear in 13.2% volume fraction. Since the HS estimates (6.6) for linear composites with aligned ellipsoidal inclusions will be used to estimate the effective behavior of the nonlinear composites, it may be appropriate to use slightly larger aspect ratios w to be able to model the additional plastic constraint in the matrix produced by the sharp comers in the particles. The matrix is characterized by 52 deformation theory (7.39), with E ( ’ ) = 73 GPa, u ( ’ ) = 0.33, and with a different power-law form for CTY (with exponent n = 7.66; see Li and Ponte Castafieda, 1994). The resulting variational estimates are compared in Figures 12a and b with numerical simulations by Tvergaard (1990) and Hom (1992), for tension along and transverse to the fibers, respectively. (Note that the simulations of Tvergaard made use of an axisymmetric unit cell, whereas those of Hom made use of full 3-D FEM calculations on cubic unit cells.) The figures show that, accounting for the uncertainty in the aspect ratio of the fibers, the variational estimates are fairly accurate for both axial and transverse tension. As emphasized by Li and Ponte Castafieda (1994), the variational procedure has the advantage over the numerical simulations that other more general loading conditions can be treated with equal ease. Such results show dramatic differences in their predictions of the effect of particle shape on the four different modes available, including shear transverse and along the fibers.

E. AN INCREMENTAL ELASTOPLASTIC MODELBASED ON THE VARIATIONAL PROCEDURE A criticism that can admittedly be raised against the variational procedures that have been developed here is that they rest, from the very beginning, on the assumption that the material behavior of the constituents derives from a potential, which is not the case for most nonlinear (usually elastoplastic) materials.

275

Nonlinear Composites 0.8

'

=33

(GPa)

.

'

'

"

i

'

'

'

'

'

"

"

n = 7.66 c ( ~=)0.13

"

'

'

c.- A - .

_.-.-.

'

'

~

-.-.

'

'

-.*.-.-.-.0

+

+---- ------

.. t---_ _ - - - _ - - -- - - - < -.; .,k;--'/

0.6 -

-. -.

O

I .

/

/

.z /

' 8

'

/

/I

0.4

_____w

= 6.25 w = 7.0 -Matrix (Al) 0 Horn E M (overlapping) A Horn FEM (side-by-side)

0.2

"

0 (b)

0.01

0.02

0.03

0.04

0.05

E22

F I G . 12. Variational estimates of the Hashin-Shtrikman type for particle-reinforced metal-matrix composites. In the context of the variational estimates, the particles are elastic, spheroidal (with three aspcct ratios w ranging between 5 and 7.5), aligned, and dispersed randomly with transverse isotropy in the metal matrix. The effective stress-strain relations are shown and compared with the numerical results of Tvergaard (1990) and Hom (1992). The fibers in the numerical simulations are cylindrical, with aspcct ratio 5, and are distributed periodically. a) Uniaxial tension along the fiber direction. b) Tension transverse to the fiber direction. Reprinted from Li and Ponte Castafieda (1994) with kind permission from ASME International.

276

Pedro Ponte Castaiieda and Pierre Suquet

A partial answer to that criticism is that, at least for certain loading conditions of real interest, it is possible to use a deformation theory of plasticity instead of a flow theory to describe the behavior of the constituents. This substitution is rigorous only when the loading is radial and monotonic at every point x in the volume element V, but it may also be appropriate for small deviations from proportionality (Budiansky, 1959). The assumption of proportionality is rarely met and deviations from radial paths are likely to be the rule. However, numerical simulations of the transverse response of nonlinear matrices reinforced by aligned continuous fibers suggest that, even though local deviations from this assumption are actually observed and affect the local stress and strain fields, there seems to be little influence on the overall stress-strain response of the composite under monotonic overall loading. That means that using a deformation theory for the constituents can be a good approximation for composites subjected to an overall monotonic radial loading, such as uniaxial tension. Note that, although this model does not strictly apply for general loadings, its predictions for those loadings for which it is admissible are much more accurate (Suquet, 1997a) than those of schemes allowing for more general loadings, such as the incremental method or the transformation field analysis (Dvorak, 1992). However, the use of a deformation theory for non-monotonic loadings is not appropriate and the use of flow theory is required. Then the variational method does not apply, strictly speaking, but can still give useful insight into how to construct approximate effective constitutive relations expressed in terms of two thermodynamic potentials, the free energy for reversible effects and the dissipation potential for irreversible phenomena (Rice, 1970; Mandel, 1972; Germain et al., 1983). An example is given below for metal-matrix composites, in which an approximate incremental model is proposed to describe the effective behavior of the composite. The matrix phase is phase 1. Its behavior is elastic-plastic with isotropic hardening, the plastic properties being given by a J2 flow theory:

I : &d)'

p=0

when

aeq= a y ( p ) ,

when

a,, < a y ( p ) .

Here o y ( p ) is the flow stress of the matrix, which depends on the accumulated plastic strain p ,

Nonlinear Composites

277

and h is the hardening modulus h ( h = af.(p)).The flow stress is related to the stored energy by

The Helmholtz free energy of the matrix, 'FI, consists of a part that can be recovered by unloading, the elastic energy, and another part that is not recoverable simply by unloading and is stored in the material, called the stored energy: X ( E , EP,

1 p ) = - ( E - E P ) : L('): ( E - E P ) 2

+ rp(p),

P

p(p) =

ay(p)dp.

The particles are assumed to be linear-elastic, spherical in shape, and randomly dispersed in the matrix. The range of volume fractions typically encountered in such metal-matrix composites is 10-30%. The overall hardening of the composite is, in general, rather complex and is due first to the hardening of the matrix itself, and second to local residual stresses caused by the incompatibility of local plastic strains. The elastic energy of these residual stresses contributes to the overall stored energy. The effective elastic-plastic behavior of the composite can be rigorously written with an infinite number of internal variables (Suquet, 1987), namely the field of local plastic strains. Except for very particular microstructures (e.g., laminates), for which the number of internal variables rigorously reduces to a finite number, this general result is of limited practical use. The situation is similar to the one encountered earlier in the discussion of the local problem in nonlinear elastic materials that required an approximation of the secant tensors by piecewise constant tensors. A simple approximation consists of assuming a priori the form of the overall hardening of the composite and then estimating accordingly the overall stored energy. To illustrate this type of approximation, a simple model will be constructed to describe the overall isotropic hardening of the composite. To this end, it is sufficient to estimate the overall stored energy of the composite. This estimation is based on the observation that one can distinguish three regimes in the deformation of the composite:

1. Elastic regime: The plastic strains in the matrix are smaller than the elastic strains. 2. Elastic-plastic regime: The elastic and plastic strains in the matrix are of the same order. 3. Plastic regime: The elastic strains in the matrix and in the inclusions are smaller than the plastic strains in the matrix. The elastic regime can be handled by any linear theory appropriate for the microstructure of the composite providing the overall stiffness Leffof the composite

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Pedro Ponte Castaiieda and Pierre Suquet

and, consequently, its overall elastic energy. The elastic-plastic regime is ignored, for simplicity, in the present model. The plastic regime is handled by considering the particles as rigid inclusions in a plastic matrix with hardening. The overall stored energy of the composite is estimated by considering that the matrix is a nonlinear elastic material with a strain energy density (deformation theory of plasticity with elastic deformations neglected). This last problem has been considered in Section VI1.B. When the composite has overall isotropy, the overall stored energy potential can be estimated by

(7.41)

where pgff is the effective shear modulus of a linear composite made up of an incompressible matrix with shear modulus containing rigid inclusions. The expression (7.41) makes use of the fact that the overall strain reduces to the overall plastic strain in the plastic regime E z EP and E& = P. The Helmholtz free energy of the composite is then estimated via

pt)

1 xeff(E,E P , p ) = - (E - EP) : ILeff : (E - EP) 2

+ Qeff(p).

The thermodynamic forces associated with the internal variables EP and P are derived from the free energy (see Germain et al., 1983):

xc--axeff (E, EP, P ) = Leff: (E - EP), aEP In turn, the evolution of the internal variables is governed by the associated thermodynamic forces and follows the normality rule,

Under the a prori assumption that the overall hardening of the composite is of the isotropic Von Mises type, Feff is given by

F f f ( X , R ) = C,,

+ R.

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Nonlinear Composites Finally, the proposed effective constitutive law for the composite reads

E =E" +EP,

E" =MIeff: X, (7.42)

Ep

= 0 when

C,, < aFff(P),

where

This approximate model requires only one constant ( D in (7.43)), which is deduced from a linear theory.

Discussion. First, the predictions of this model under monotonic loading are shown in Figure 11. The agreement with the FEM calculations is seen to be good. Second, to further check the capability of the model to account for unloading, loading through one cycle has been considered. The secant method and the variational method are not appropriate for this type of loading. The incremental method was not considered, since its predictions for monotonic tension were observed to be inaccurate. The predictions of the approximate model (7.42) and of FEM calculations after one cycle are shown in Figure 13. Again, the predictions of

-0.08

-0.04

0.0

0.04

0.08

FIG. 13. Same data as in Figure 11. Cyclic uniaxial tension. Volume fraction of inclusions c(*) = 0.3. The inclusions are linear elastic. The matrix is governed by the J2 flow theory with

isotropic hardening (7.39). Comparison between numerical results obtained by the finite-element method (FEM) and the incremental model (7.42) (IM). Reprinted from Suquet (1997a) with permission of CISM.

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Pedro Ponte Castafiedaand Pierre Suquet

the approximate model are satisfactory. The overall hardening of the composite is rendered accurately, except for the part of the stress-strain curve where a Bauschinger effect is observed on the FEM calculations (yielding in compression). For relatively large strain in cyclic loading, this effect is of relatively little importance. For cyclic loading at low levels of plastic strains, this effect would play a more significant role and the approximate model would be less satisfactory. This observation is consistent with the approximations made when neglecting the regimen in which elastic and plastic strains in the matrix are of the same order.

VIII. Concluding Remarks This paper provides a review of three different methods that have been developed over the past 12 years to estimate the effective behavior of nonlinear composite materials with random microstructures. The first method, due to Talbot and Willis (1985), is based on a nonlinear extension of the Hashin-Shtrikman variational principles. The second method, due to Ponte Castaiieda (1991a, 1992a) in the context of nonlinear isotropic composites, and to Suquet (1993a) for powerlaw composites, makes use of new variational principles involving a “linear comparison composite.” The second method has also been shown, by Suquet (1995), to exhibit an alternative representation in terms of a “modified secant procedure.” These two methods have the advantage that they can give rigorous bounds in at least one direction: the first delivers bounds of the Hashin-Shtrikman type incorporating two-point statistics; the second can generate bounds and estimates of any type directly from corresponding bounds and estimates for the linear comparison composite, including bounds of the Beran type. However, the bounds and estimates that are generated by these two methods for nonlinear composites are exact only to first order in the contrast of the phases, even when the corresponding linear estimates are known to be exact to second order in the contrast. For this reason, a third method was developed by Ponte Castaiieda (1996a), which also uses a linear comparison composite, although of a different type involving the tangent moduli of the phases, instead of the secant moduli. This “second-order” method has the capability of generating nonlinear estimates that are exact to second order in the contrast and that are thus in agreement with the asymptotic results of Suquet and Ponte Castaiieda (1993). It is emphasized that these second-order estimates are not bounds in general. Finally, it was shown by means of some examples that these three new methods significantly outperform the classical incremental and secant methods, which have been shown to violate rigorous bounds. Furthermore, these new methods deliver results that are in good agreement with existing numerical simulations, with the second-order procedure perhaps yielding the most

Nonlinear Composites

28 1

accurate results, at least for the special cases that have been studied so far. Comparisons with experimental work are, of course, much more difficult, but at least qualitative agreement has been obtained in some cases, such as the prediction of the “bimodal” character of yields surfaces for fiber-reinforced metal-matrix composites (Dvorak et al., 1988). In spite of the significant progress made in recent years, much work remains to be done, particularly in terms of handling complex constitutive behaviors. The above-mentioned methods have been developed in the context of nonlinear elastic or nonlinearly viscous constitutive models, for which there are well-established homogenization frameworks involving variational representations for the relevant effective energy-density functions and dissipation potentials. Extensions to more general types of constitutive behaviors can be accomplished at least approximately, as the example in Section VI1.E shows for a metal-matrix composite with a matrix phase characterized by flow theory of plasticity. Work is also in progress to understand the strong coupling between elastic and nonlinearly viscous effects. At the more theoretical end, the question remains as to whether true second-order bounds, that are exact to second-order in the contrast, can be developed for nonlinear composites. (Recall that the second-order procedure does not give bounds.) This question is compounded with the difficulty involved in determining the “other bound,” although Talbot and Willis (1994, 1997) have made significant progress along these lines. Finally, another important issue in which progress has been made (Ponte Castaiieda and Zaidman, 1994; Kailasam et al., 1997a, b; Kailasam and Ponte Castaiieda, 1997) is in terms of handling microstructure evolution, when the composites are subjected to finite deformations, such as the ones that are typically present in metal-forming operations.

IX. Appendices A. POTENTIALS, CONVEXITY, CONCAVITY AND DUALITY 1. DeJinitions A scalar valued function g defined on a vector space X with values in (-m, +m], is said to be convex when

Given an arbitrary function g, defined on a vector space X , its convex dual (or polar function) g*, which is defined on the topological dual X * of X , is given by

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282

(Ekeland and Temam, 1974; Van Tiel, 1984) g*(x) = s u p b ' y - g(x)}. X

Note that g* is a convex function (even when g is not convex). When g is convex (and lower semicontinuous), the bidual g** of g is g itself, g(x> = g**W = SUPb * Y - g*(y)). Y

If, in addition, g is differentiable, the following assertions (i), (ii), and (iii) are equivalent: ag (i) y = - (x), ax

ag*

+

-

(iii) g(x) g*(y) = x y. (y), aY When g is not differentiable, the above relations are to be understood in the sense of subdifferentials. The dual of a sum of two convex functions is not the sum of the two dual functions, but their inf-convolution, (Sl

(ii) x =

~

+ g2)*(y) = glVgz(Y) = z1+z2=y inf g;(zl) + gZ(z2).

643)

The concave dual function of an arbitrary function f defined on X is f*(Y) = i n f b . y - f ( x ) I .

(A4)

Note that when f is concave, -f is convex, so that all definitions or results valid for convex functions can be translated into similar results for concave functions. 2. Strain-Energy and Stress-Energy Functions Assume that the strain-energy potential w is a positive convex function, such that

w(0) = 0,

lim

Iel++m

W(E)

= +cc.

(A5)

Assume, in addition, that w may be written in the form W ( E ) = F ( E ) ,where P = ; E @ E and where F is a concavefunction defined on the vector space of symmetric fourth-order tensors Q . The dual function of F (in the sense of concave functions) is defined as

F,(lL,) = inf(IL :: Q - F ( e ) } . e

(A6)

Note that F* is negative (take Q = 0in (A6)) and that F* (L) = -cc when L is not positive definite. Indeed, assume that IL has a negative eigenvalue, i.e., that there exists EO such that EO : IL : EO 5 0. Then, taking Q = t2eo @ EO in the definition of

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Nonlinear Composites

F* and letting t go to 00,we obtain (by virtue of the growth condition (A5)) that F,(L) = -CO. Since F is concave, F is the dual of F,, or

F ( e ) = inf (L:: Q - F*(L)}.

('47)

L>O

We claim that the dual potential w* of w can be written as w*(a) = G(ar), with ar = iu €4 u,where G is a convex function defined as G(J) = SUP

{IL-'

:: J + F*(L)}.

L>O

To prove this result, note that

It follows from (A7) that (with

E

= ; E €4

E)

Then

1

w * ( a ) = supsup 1( T : E - 2- - - E : L : E + F * ( L ) ) L>O

E

[-1

= sup L>O 2

(T

: L-': (T

+ F * ( L ) ) = lL>O sup {L-':: a~ + F*(L)} = G(ar).

(A9) equation Note that G is defined as the supremum of linear (therefore convex) functions of s. It is consequently a convex function of J. 3. Isotropic Constituents Let F be given in the form

F ( Q ) = 3kJ :: Q + f

(i R :: IE) when K ::

F ( I E )= -00 By definition, the concave dual of F is

F,(L) = itf (IL :: Q - F ( Q ) } K::e>O

otherwise.

Q

>_ 0,

Pedro Ponte Castaiiedu and Pierre Suquet

284

The optimality conditions for the problem (A10) can be expressed with a positive Lagrange multiplier h

4 3

4 3 h20,

IL = 3kJ + - f ' ( - R :: e)IK+hIK, R::ezO,

hR::e=O.

('411)

It follows from the optimality conditions (A1 1) that IL is necessarily an isotropic tensor,

4

IL = 3kJ + 2 p R , 2 p = ?f'(JK

:: e) + h .

Note that p is positive, (recall that f' is positive, since f is an increasing function). Therefore,

Finally,

F*@) =

{ f*(ip)

when

IL = 3kJ + 2pK,

p > 0,

otherwise.

--oo

(A13)

4. Crystalline Materials Consider first the stress potential for one slip system: G(k)(3) =

{

g(k)(2M(k):: 3)

when M(k) :: 3 2 0 ,

+Go

otherwise.

The convex dual of G(k)is, by definition,

GTk,(M) =

SUP

{M :: s - G ( ~ ) ( s ) )

3

M(k)::310

=

sup

{M :: s - g(k)(2M(k):: 3 ) ) .

S

M(k,::SzO

The optimality conditions for the problem (A14) can be expressed with a positive Lagrange multiplier h, = 2g;,)(2qk) :: 3 ) M ( k )

MI(,) :: s 3 0 ,

h 2 0,

+ hM(k), hM(Q :: s = 0.

('415)

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285

Since M is necessarily proportional to M ( k ) ,

Finally: GTkj(M)

=

{ +oo

gTk,(a) when M = 2aMTk),

a > 0,

otherwise.

Next consider the case of a single crystal, where K

k= 1

Since G is the sum of convex functions of s, its dual is the inf-convolution of the corresponding dual functions:

where the infimum is over the a:;; such that

B. DERIVATION OF THE POTENTIAL WITH RESPECTT O A PARAMETER The derivation of the overall energy of a composite with respect to a parameter is used in various circumstances to obtain expressions for the second moment of the strain in each phase of a linear composite or for the small-contrast expansion of the effective potential of a nonlinear composite. We give here a general result applying to linear composites and to nonlinear composites as well.

Pedro Ponte Castaiieda and Pierre Suquet

286

Consider a composite governed by a pair of dual convex potentials w ( x , E , t ) and u (x,a,t ) depending on a parameter t. Then the localjelds Et and afand the overall potentials depend on t :

It also follows that

To prove this result, let i t denote the derivative of et with respect to t . Note that i , = E ( u j ) is a compatible strain field and its average is zero (since E does not depend on t ) . Differentiating (Bl) with respect to t yields

By the Euler-Lagrange equations associated with the variational principle (B 1)(1, the stress field a, = ( t , e t ) satisfies the equilibrium equations div(at) = 0 in V. According to Hill’s lemma,

2

(at : i t ) = (at)(it)= 0. This completes the proof of (B2),. The proof of the other equality is similar.

1. Application to Second Moments of the Strain in Linear Composites The result just derived can be used to obtain expressions for the second moments of the strain fields in the individual constituents of linear composites. Consider:

Then

and, according to (B2),,

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Nonlinear Composites Thus the second moment of the strain field in phase ( r ) is given by

After rearrangement,

Similarly,

2. Second Moment of the Shear Stress Consider now:

au ( t ,

-

at

fJt)

= c(')u : M(" (k) . u3 '

@(t,

1 2

E) = - c : laeff :c.

Then, according to (B2)6,

3. Average Strain Due to Piecewise Constant Polarization Fields Finally, consider:

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Pedro Ponte Castafieda and Pierre Suquet

Then

This completes the proof of (5.27).

C. PTENSORS 1. Spheroidal Inclusion in an Isotropic Material Assuming that the matrix material is isotropic with bulk and shear moduli k(O) and p(O),respectively, and that the inclusion is spheroidal (i.e., ellipsoidal with circular cross section) with length-to-diameter aspect ratio w,the P tensor exhibits transversely isotropic symmetry, so that it may be written, using the notation of Walpole (1969, 1981), in the form

where (Eshelby, 1957)

+

+

2[4 - 3h(w) - 2w2]p(0) 3[2 - 3h(w) 2w2 - 3 ~ ~ h ( w ) ] k ( ~ ) 8( 1 - w 2 ) p ( 0 )(4p(O) 3k(O)) (C1) In these relations, (0)

Pp =

h(w)= h(w)=

+

w[arccos(w) - w % / i - T Z ] (1 - w2)3/2

w [ w d m- arccosh(w)] (w2 -

1)3/2

for w 5 1, for

w 2 1.

Asymptotic expressions for the above P tensor in the limits as w -+ 0 and 00 have been given by Willis (1981). These are useful in the computation of the effective modulus tensors for the cases of rigid disks and cracks. More general expressions,

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289

assuming transversely isotropic behavior for the matrix material, have been given by Laws and McLaughlin (1979). When the matrix material is also incompressible, the above tensor simplifies and can be given the spectral decomposition

In this relation, IE [PI, IE In], and IE [dl are projection tensors, physically corresponding to transverse, longitudinal and axisymmetric shear (see deBotton and Ponte Castaiieda, 1992,1993),which are defined by

where aij = ninj and Bij = & j - ninj, with n denoting the axis of transverse isotropy. The coefficients p p ) , and correspond to the three possible modes of shear transverse to the fibers, shear along the fibers, and axisymmetric deformation, respectively, and they are given by the expressions

FA'',

2. Spherical Inclusion in an Anisotropic Material with Special Symmetiy Assuming that the modulus tensor of the matrix phase exhibits the material symmetry

+

+

= 3k(O)J 2p(O)IF 2h(O)IE,

where the tensors J, IE, and F are orthogonal projections defined by relations (2.24), (5.14),and (5.15), respectively, and assuming that the inclusion shape is spherical, so that the shape tensor Z = I, the associated tensor )'()'€I can also be written in the form

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Pedro Ponte Castafieda and Pierre Suquet

and

-=-I 1

1

2k(,O)

6n

/Ed I+I

p(0)

+ $(A(O)

.t12- a(O)(P - E d - e l 2

-

p(O))(lEd .,$I2 - a(O)(( . E d - 0 2 )

d s( P ) ,

(C5) with =

3k(0)+ p(o) 3k(0) + 4p(o)

'

These relations are due to Ponte Castaiieda (1996a, 1997a) and Ponte Castafieda and Nebozhyn (1997). When the matrix phase is incompressible (k(O) + OO), the above results for p(,O' and A!) can be simplified to give

and where 8 is the angle defined by (Kachanov, 1971) where r ( 0 ) = p(O)/AC0)

which therefore depends on the determinant of the strain. The functions a and B are, in turn, defined by the relations

29 1

Nonlinear Composites 2.0

71

A

C 1.8

n=+m

1.6 1.4

1.2 1.o

0.8 0.6 0.4

0.2

1

0.0 0.0

0.1

0.2

e

0.3

0.4

0.5

= n and of the loadF I G . 14. Constant C (C9) as a function of the exponent of nonlinearity ing parameter 8 . Reprinted from Suquet and Ponte Castaiieda (1993) with permission of the French Academy of Sciences.

and

where

is the integral introduced by Suquet and Ponte Castaiieda (1993). For high nonlinearities (large values of r(O)),C depends strongly on the third invariant of E d (ore), as shown in Figure 14. Finally, note that the corresponding two-dimensional version of the above result, which is useful in the analysis of fiber-reinforced microstructures, may be obtained formally by making the replacements

Note that these results are independent of the determinant in this case.

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Pedro Ponte Castaiieda and Pierre Suquet

D. A BRIEFREVIEWOF OTHERSCHEMES 1. Secant Methods The starting point of all secant methods is the “local” problem to be solved for the local stress and displacement fields u and u:

u = L,(x): E(x),

div(u) = 0,

where the secant tensor L,depends on x through the strain field E(X) or through ~ ( xif) the form (2.17) is assumed for the strain-energy. Clearly L,ycan vary from one point to another, and this nonlinear problem is as difficult to solve as a linear problem with infinitely many different phases. An approximation is required to make further progress. The approximation for secant methods consists of replacing the secant tensors L,(x) with tensors that are constant over each phase:

(x) = L(‘),

in phase r.

In addition, it is reasonable to assume that the tensors L(‘)are given by the constitutive relations of phase r evaluated at some “effective strain” in charge of picking up the main features of the strain field in phase r. Assuming for a while that this effective strain is known, the approximate version of the local problem reads

a(x)= L(‘): E(X) 1 E = - (VU VU‘), 2

+

in phase r,

u E K(E).

div(u) = 0,

(D2)

For simplicity, the same notations u, u,E are used to denote the local field solutions of (Dl) and (D2), although it should be clear that these fields are different in general. In the rest of this appendix we consider only the solutions of (D2). Given the tensors L(’),the problem (D2) is now a classical one for a linear-elastic material. Note, however, that these tensors themselves depend on the strain field E (through the effective strain), which itself depends on the tensors L(“), s = 1, . . . , N . The problem is therefore nonlinear, but instead of having infinitely many nonlinear problems to solve (at each point x), there are “only” N nonlinear problems to solve in each phase r. In the most commonly used secant method (called classical hereafter), the effective strain of phase ( r ) is the average strain of this phase, E(‘) = (@)(’I, which can be expressed in terms of the overall strain E by means of the strain concentration tensor A(‘),

293

Nonlinear Composites Therefore the classical secant method may be summarized as follows:

1. A linear theory providing an expression for Leffand the N strain concentration tensors A(r)in each phase as functions of the secant tensors L(')Is=~,...,~ and of the microstructure.

2. The resolution of N nonlinear problems for the N unknown secant tensors L(r)(~('1): g ( r ) = A(r) . L'" = J$)(gW), . E, A@) = A(r)(L(\), " s = 1, . . . , N ) .

(D3)

3. Once the N nonlinear problems (D3) are solved, the overall stress-strain relation, given by

2. Incremental Method General procedure. The constitutive law (2.1) of the individual constituents may be alternatively written in the incremental form, u = Lt(x,E) : i,

a2w

L,(x,e) = -(x,E). ae2

Then the local problem, in incremental form, reads U

= L,(x): i(x),

1 i= - (vu 2

+ vuf),

div(u) = 0,

u

E

Ic(E).

(D6)

The tangent tensors Lr(x) can be different from one point to another, since they depend on the strain field E(x). Again, an approximation must be introduced to simplify the problem, and the tangent tensors Lt are replaced by tensors L:r), which are constant in each phase. These tensors are computed from the exact expressions of the tangent tensor in each phase ( r ) evaluated at some effective strain for this phase. The most obvious choice (and the one that has been uniformly adopted) for the effective strain of phase r is the average strain over this phase,

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Pedro Ponte Custuiiedu and Pierre Suquet

The local problem now reduces to u = L(') . i ( x ) ,

1 i = -(Vu 2

div(u) = 0,

+ Vu'),

u

E

K(E). (D8)

It is a linear problem for the increments iand u , which can be determined with any linear theory appropriate to the morphology of the composite and capable of predicting the effective properties of anisotropic linear composites. At each time t , the average strains E.(r) and the tangent tensors L(') are known. The overall elastic tangent tensor Leffis computed, and the overall constitutive law is found in incremental form as

2 = Leff(E): E.

(D9)

The increments of average strain in each phase are computed by =A (') : E,

where the tensors A(') are the elastic strain concentration tensors associated with the stiffness tensors L(').The average strains E ( " ) are then updated, and the procedure continues step by step. Under certain conditions, the above relations (D9) are integrable in time, and the overall constitutive law can be expressed as a relation (nonlinear) between stresses and strains. But nothing in the procedure guarantees that this integration is possible, and, when it is so, it is not clear that the resulting constitutive equations derive from a potential.

Isotropic composites. When the individual constituents are isotropic with a strain-energy given by (2.4), the tensor of the tangent moduli IL.' has the form (5.13) at each point x in the r.v.e.:

Lt(x) = 3kJ

+ 2P'F + 2hE,

Note that not only the coefficients and h, but also the tensor E depends on x. In addition, Lfis generally anisotropic (except when the strain is purely spherical). The linear theory used to derive the effective tangent stiffness must be able to predict the overall behavior of anisotropic phases, even when the geometry of the constituents does not favor any particular direction. The Hashin-Shtrikman bounds (6.4) can be used to estimate Leff.A first difficulty then is to compute the tensor P (') from the general relations (6.2). In general this determination must be done numerically. For random composites, the formulae (C3), (C4), (C5) can

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295

be used. Another difficulty in the evaluation of (6.4) arises from the fact that the phases generally have different types of anisotropy. Indeed, the tangent tensors I,(') read = 3 k b - I ~+ 2 p ( r ) ~ ( r+ ) 2k(r)~(r),

. these computations simplify for composwhere IE(') = i E i )@ E i )Interestingly, ites with statistically isotropic microstructures. Then it can be assumed, following Hutchinson (1976), that the average strain deviators in each phase are parallel:

This last statement can be justified for spherical inclusions in a matrix, provided the loading applied to the composite is purely radial. It implies that the tensors IE(') are identical in all phases, i.e., that the tensors I,@) have exactly the same type of anisotropy and can be split on the same basis: J, IF, and IE.

Acknowledgments The authors are grateful to Professor J. R. Willis and A. Zaoui for many insightful discussions and valuable comments. They are also indebted to J. C. Michel and H. Moulinec for providing some of the numerical results presented here. The work of PPC was supported by the National Science Foundation (grants MSM88-09177, DMR-91-20668, and CMS-96-22714), the Air Force Office of Scientific Research (grant 91-0161), the Office of Naval Research (grant N00014-96-10681), and the Aluminum Company of America. The work of PS was supported by the Centre National de la Recherche Scientifique.

References Aravaa, N., Cheng, C., and Ponte Castaiieda, P. (1995). Steady-state creep of fiber-reinforced composites: Constitutive equations and computational issues. Internat. J. Solids Structures 32, 22 192244. Avellaneda, M. (1 987). Iterated homogenization, differential effective medium theory and applications. Comm. Pure Appl. Math. 40, 527-554. Bao, G., Hutchinson, J. W., and McMeeking, R. M. (1991). Particle reinforcement of ductile matrices against plastic flow and creep. Actu Metall. Muter: 39, 1871-1882. Bensoussan, A., Lions, J. L., and Papanicolaou, G. (1978). Asymptotic analysis forperiodic structures. North-Holland. Amsterdam.

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ADVANCES IN APPLIED MECHANICS, VOLUME 34

The Mathematical Foundation of Plasticity Theory WE1 H. YANG The University of Michigan Ann Arbor; Michigan

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.303

I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.304

11. Minkowski Norms and Holder Inequality . . . . . . . . . . . . . . . . . . . . . .

307

............................

308

IV. Constructing the Dual Norm . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

309

V. Application to Plasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3 11

111. Generalized Holder Inequality

VI. A Duality Theorem for Plane Stress Problems . . . . . . . . . . . . . . . . . . . 313

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. 315

Abstract Supporting the mathematical theory of plasticity, two pillars constituting the modeling of yield behavior are the convexity and normality conditions on a yield function. The models so established have been time tested to hold for a wide class of ductile materials in many practical applications of the theory. Their logical basis was the belief that a material does not release energy during plastic deformation (nonnegative dissipation). Even though the theory is sound, the lack of a mathematical proof on normality still causes some researchers to call it a postulate. In this paper, we shall dismiss this notion of assumption by introducing a generalized Holder inequality. The normality relation becomes a requirement for the inequality to be sharp (equality inclusive). This inequality also reveals the primal-dual relation of stress and strain rate. Even before this connection of the mathematical and physical implications, different duality relations were used in many known minimax theorems in plasticity. We shall claim that convexity, normality, and duality, all properties of the generalized Holder inequality, complete the foundation for the constitutive modeling of the mathematical theory of plas303 ISBN 0-12-002034-3

ADVANCES IN APPLIED MECHANICS. VOL. 34 Copyright Q 1998 by Academic Press. All rights of reproduction in any form reserved. 0065-2165/98$25.00

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Wei H.Yang

ticity. By using these models, the minimax formulations of plasticity problems can be derived in a systematic and unified approach.

I. Introduction Convexity and normality are the two pillars of a constitutive model that is the basis of the mathematical theory of plasticity (Hill, 1950). The yielding behavior of metals has been modeled satisfactorily by convex yield functions more than a century ago (Tresca, 1864,1868). Such models remain valid, even in light of new materials and experimental results. Although it was conjectured earlier (Prandtl, 1924; Reuss, 1930), a logical basis of normality was not in place until 1959 (Drucker, 1959). Based on the existing foundation, we shall add another pillar to complete this useful constitutive model. First, we shall present a yield function f as a norm (or a seminorm) on the 3 x 3 symmetric stress matrix B. An initial yield criterion may be modeled by

f (c)= llall - 0 0 5 0 ,

or

l b l l 5 009

(1)

where 00 is a material constant. Both the form of the norm and the material constant are allowed to vary with plasticity deformation history to model subsequent yield behavior. This representation not only gives a sense of bounded stress, but will also lead to a foundamental inequality that encompasses the Cauchy-Schwarz and Holder inequalities as special case. These inequalities pertain to the inner product of vectors, matrices, and functions. We shall restrict our discussion to finite dimensional spaces that involve only vectors and matrices. The upper bound of an inner product is expressed in terms of dual norms of vectors and matrices. Although the Cauchy-Schwarz inequality applies only to Euclidean norms, the Holder inequality extends the applications to a family of Minkowski norms. Norms that model yield behavior are generally non-Euclidean. The inner product in plasticity involves the stress and strain rate matrices. The generalized Holder inequality for such an inner product may take the form

where the colon denotes the inner product operator between two matrices and the subscripts of the norms, ( p ) and ( d ) , suggest the primal-dual relation. A primal norm is determined to fit experimental data. Its dual norm is determined mathematically to establish the theorem of generalized Holder inequality. We shall first

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introduce the background leading to the theorem, then present its application to plasticity. The well-known normality relation in plasticity between the strain rate and stress becomes the natural sharpness condition of this generalized Holder inequality. This new inequality is fundamental to all minimax (duality) theorems in plasticity. A special case for plane stress problems will be presented as an example. The familiar Cauchy-Schwarz inequality for the Euclidean vector space is commonly stated as

where x, y are vectors in Rn; T transposes a vector, and clidean norm. The equality holds if y=ax,

aER,

11 . 112 denotes the Eu(4)

or the two vectors are colinear. The inequality (3) is often used in the upper bounding process of a mathematical analysis. A “sharp” upper bound that includes the equality case is vitally important in the field of functional analysis and its applications. Obviously, a function that is bounded above has a finite supremum. The supremum of a function is contained in the range of a sharp upper-bound function. Therefore, a search for the least upper bound will recover the maximum of the original function. This indirect method of finding the maximum of a function will fail if its upper-bound function is not sharp. The Cauchy-Schwarz inequality does not hold in a general non-Euclidean space. Holder introduced an extension so that a modified inequality is valid in a vector space in which a family of Minkowski norms (Birkhoff and MacLane, 1953) is defined. The colinearity condition (4) for sharpness must also be modified. We shall use a simple example to illustrate these points. Consider first the norm i n R 2 , Ilxllm = max(lx11, Ix21}.TwospecificvectorsxT = (1, 1) andy’ = (1, 1) produce the inner product xTy = 2. This inner product cannot be less than or equal to llxllmllyllm = 1. Now let y be measured by another norm, llylll = Iy1( 1 ~ 2 1 It . is well known that lx‘yl I IlxmIIIIyII1 for all x, y E R2,and that equality holds under a certain condition that, in general, is not the colinearity of x and y. This can be illustrated in geometric terms. Let

+

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Clearly, all such vectors lie on two “unit circles,” one in the shape of a square for x and the other in the shape of a diamond for y, as shown in Figure 1. The well-known inequality T

Ix YI I llXllo0llYlll = 1

(6)

holds for any x and y defined in (5). Here, the vectors x and y are said to be a pair of dual variables. Consider a specific vector, x=(l

a)?

o
(7)

The vector y in the direction of this x has the form T

so that it has unit length as defined in (5). The inner product of these two colinear vectors can be computed to yield xTy = (1 +a2)/(1+ a ) < 1.

(9)

Hence the sharpness condition in (4) is not valid in general. The intuition that an inner product of two vectors attains a maximum (or minimum) when they are colinear needs qualification. The sharpness condition for the dual vectors defined in ( 5 ) does exist and arises from certain specific pairing other than the colinearity of the two vectors. The pairing depends on the norm measures defined. We shall explain such pairing in a slightly more general setting than the 1-norm and 00norm considered so far.

FIG .

I . Unit circles for vectors in R2with different norm measures.

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11. Minkowski Norms and Holder Inequality

x

The family of Minkowski norms (Birkhoff and MacLane, 1953) for a vector R"is defined by

E

(called a p-norm), which includes the familiar cases p = 1,2, and 00. A pair of norms, II . [Ip and 11 . [Iq, in this family are said to have a dual relation (Birkhoff and MacLane, 1953) if (11) The Holder inequality holds for any pair of such dual norms so that lXTYl

I IIXllplIYlly.

It is well known that the equality case holds if either yj = a)xi)p-'sign(xi) or = alyilqp'sign(yj), a E R,1 I p , q 5 00, i = 1, 2 , . .., n. This sharpness result can be obtained by

Xi

Y = aVllxllp

or x = aVlIYIIq,

(13)

where V is the gradient operator. When operated on a differentiable function of n variables, V produces a gradient vector in Rn.A gradient vector is normal to the level sets (contours) of the norm function. Thus the expression in (13) will be called the normality relation. The vectors satisfying (13) belong to a dual pair. To avoid the issue of differentiability of certain norms, we postpone the discussion on the cases ( p , q = 1,00) in which the norms are Co functions. We shall show the equality case of (12) under one of the normality relations of (13) by first choosing a p-norm (1 < p < 00) for x and then obtaining the components of y by differentiation,

where k > 0 is chosen as the proportional factor, and the range of the sums over j and the index i are implied to span from 1 to n. Using (14), we can form the q-norm of y from its components and, with some simplification, obtain

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which gives the proportional factor k an explicit expression. Again, using (14) and (1 9 , we can produce the inner product for the pair of dual vectors,

The equality is thus obtained and the normality relation is the desired sharpness condition. The absolute bound on xTy is not needed because k is chosen to be positive. Although the crucial relation (1 1) is only alluded to here as a reference (Birkhoff and MacLane, 1953), it will be made evident during the construction of dual norms in a later section. Inequalities (3) and (6) are special cases of (12). The normality relation between dual vectors is not restricted to the family of Minkowski norms. General non-Euclidean norms have a dual structure for pairing vectors that participate in an inequality more encompassing than that of Holder.

111. Generalized Holder Inequality All norms share a common property as convex, nonnegative, and homogeneous functions of degree one. One may arbitrarily define a norm as long as it satisfies the conditions

for all a E R and x, y E R". The condition (i') is omitted for the definition of a seminorm. Usually, the definition of a primal norm (or seminorm) arises naturally from a specific application. A dual norm must be matched to the primal norm so that a theorem for the generalized Holder inequality (Clarke, 1983) may be stated below.

THEOREM.For any two vectors x,y E R", where x is measured by a properly dejined primal norm (or seminom), (1 . there exists a dual norm (or seminorm) 11 . 11 ( d ) such that the inequality

holds. The case of equality is attained when the normality relation

is satisjied.

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The theorem, of course, covers the original Holder inequality (12) as a special case. A proof of the theorem and the method of construction for a dual norm are given in Yang (1991) for differentiable as well as Co norm functions. We shall review the dual norm construction and provide an example in plasticity.

IV. Constructing the Dual Norm The specific form of Ilyll(d) can be determined from a given l l ~ l l ( ~If) .the primal norm is given as a set of experimental data defining the “unit sphere,” as may be the case in an engineering problem, then a local gradient can be computed approximately at each data point. These gradient vectors will trace the “unit sphere” of the dual norm. This numerical method, although practical, may not be a satisfactory demonstration of dual norm construction. We shall give a close-form example. Let the primal norm be a C’ function such that its first derivatives can be computed everywhere. Dividing (19) by llyll(d), then the equation represents a map from x to y. If I ( ~ l l (is~ )strictly convex, the inverse map exists and eq. (19) can be solved for the components of x in terms of those of y. By taking the (p)-norm of x from its components and setting it to unity, an expression for llyll(d) is obtained in terms of the components of y. If Ilxll(p)contains a linear portion, the points on the linear portion map to a single point on llyll(d). In such cases, the map is no longer one to one, but construction of dual norm can still proceed. In a previous section we have verified the Holder inequality (12) without questioning the origin of the dual relation (1 1) of the Minkowski family of norms. For a given primal norm IIxIIp (1 < p < GO), we shall now derive the form of its dual norm llyll(d) without resorting to (11). Rewriting (14) by letting llxllp = 1 and k = llyll(d), we have

from which we may solve for

It is an easy matter to form

(JXII(~)

from the components xi and to obtain

Wei H. Yang

310 From the above equation,

is obtained to give the explicit form of Ilyll((/)in terms of yi and the definition of the primal norm. Now letting p / ( p - 1) = q , we confirm the dual relation (1 1) and conclude that q=- P P-1 is the dual norm for the primal norm lIxllp, 1 < p < 00.Construction of the dual norm for the other non-Euclidean C’ primal norms is analogous. The cases p = 1, 00 correspond to Co norms that are not differentiable in the usual sense at certain places of the independent variable. They can be regarded as the limiting cases, and the inequality (6) is also confirmed from the above analysis with q = 00, 1 obtained for the corresponding dual norms by taking limits from the p-norms in C’ . Although there is no mathematical difficulty in demonstrating the generalized Holder inequality and its normality relation for Co norms, it is desirable to offer an interpretation for the theorem at those points where the norm function is not differentiable. We shall call those points the vertices of a norm. Consider again the example in R2 shown in Figure 1. The gradient of JIxlloo has only four distinctive values, (1,0), (0, l), (- 1 , O ) and (0, - l),each evaluated along a respective edge, D A , A B , B C , and C D , on the unit circle of the primal norm, as shown in Figure 2(a). These four values are shown as four points ( A ’ ,B’, C’, and D’in Figure 2(b) on the “unit circle” of the dual norm, llyll(d) = 1, yet to be constructed. Because the dual norm must be a convex and continuous function, these four points must be connected. Let us connect the four points by straight lines to form a diamond, A’B’C’D’. Then no points of the “unit circle” should fall inside the diamond, or

F I G . 2. Duality and normality of 1-norm and m-norm.

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the dual norm function would be nonconvex. There exist, of course, convex functions passing through these four points but outside the diamond. We shall show that they cannot be the dual norm function either. Because duality is symmetric, the dual norm of the dual norm is the primal norm, and the symmetric normality relations are given in (1 1). The gradient of the dual norm on the “unit circle” llyll(d) = 1 must fall on the unit circle (the square A B C D ) of the primal norm. The diamond, satisfying this condition, is the only correct dual unit circle. The gradient of a Co norm function at the vertices is not unique and is interpreted as a point-to-set map. This generalized gradient (Clarke, 1983) takes the form of triangular fans, as shown in Figure 2, in which the lengths of all gradient vectors are proportionally drawn.

V. Application to Plasticity The concept of a norm is not restricted to vectors. There are matrix norms (Householder, 1954), function norms, and operator norms (Royden, 1988). In mechanics, variables may appear as matrices or matrix functions. A matrix norm has the same properties as that of the vector norms. The norms defined on stress matrices in the theory of plasticity are mathematical models of yield behavior based on experimental results and certain physical principles (Yang, 1980a, b). In plasticity, the natural primal variable is the stress denoted by u E R 3 x 3a, real symmetric 3 x 3 matrix representing the state of force per unit area at a point in the material. It may vary from point to point in a domain. It is called the stress field (a matrix function) in a body. Because no real material is infinitely strong, the strength of a material can be modeled by a bound, IIc II 5 co,presented in (1). The specific form of the norm is called the yieldfunction. The best known yield function is the von Mises yield function (Hill, 1950). To shorten the discussion, but still keeping all of the essentials relevant to the present exposition, the von Mises yield function is stated in a subspace of plane stress where an element is a 2 x 2 symmetric stress matrix

which represents a state of stress in a sheet of material located in the x, y plane of a Cartesian coordinate. The von Mises yield function can be stated in two equivalent forms,

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where a1 and a2 are the eigenvalues of the plane stress matrix in (25), and 11 . IIv denotes the von Mises norm. Another yield function, named after Tresca (1864), is physically more precise but is used less because of its nonsmoothness. When applied to the plane stress matrix, it takes the form

where the Tresca norm IIa IIT can also be expressed in terms of the stress components. One may not find these norms in a mathematics book, because they are derived from physical considerations. Nevertheless, they are valid norms or seminorms according to the conditions in (17). The dual variable in the context of plasticity is the strain rate, E , also a 2 x 2 symmetric matrix for the plane stress case. The inner product (a,r ) of the two matrices appears frequently in the field of mechanics. From a physical principle of nonnegative dissipation, Drucker (1959) had reached the conclusion that the plastic strain rate matrix is a constant multiple of the gradient of the yield function arranged in the form of a matrix, that is,

where the gradient is taken with respect to each of the stress components in (25) and arranged in a matrix form. This normality relation in plasticity is the sharpness condition of the generalized Holder inequality. What was not well understood in plasticity is that a plastic strain rate matrix and the stress matrix must also satisfy the inequality (2). The dual norm on strain rate was never introduced. Now the generalized Holder inequality gave the theory of plasticity a complete foundation. For the von Mises and Tresca primal norms, the corresponding dual norms on the plastic strain rate E in terms of its eigenvalues r1 and r2 are

116111 = max

{lei I , I E ~ I ,

+

I E ~ E~I},

respectively. They are derived from the corresponding primal norms in (26) and (27) by the constructive process described earlier. Because II . IIT is a Co norm, its gradient should be understood in a generalized sense for the construction of its dual I1 . I l l . For a graphic presentation of the results, the eigenvalues of the plane stress matrix ( a l , a 2 ) and that of the plastic strain rate matrix ( ~ 1 ~, 2 are ) regarded as

Mathematical Foundation of Plasticity Theory 11€11* = 1

IlOll" = 1

IIEIIL

=1

11611T

313 =1

FIG.3 . Geometric representation of primal and dual norms.

vectors in R2.The unit circles for the forms are shown in Figure 3, where the primal norms are shown in solid lines and the dual norms are in broken lines.

VI. A Duality Theorem for Plane Stress Problems Limit analysis for plane strain problems seems to dominate plasticity literature, only because a method of characteristics known as the slipline method (Hill, 1950) was developed. Under the new light of duality theorems, all such problems can be formulated and solved by computational optimization techniques. We depict the plane stress problems to demonstrate how the generalized Holder inequality can lead to a duality theorem. The plane strain problems can be treated in the same manner. It is well known that a stress distribution that satisfies the equilibrium equation, the yield criterion in a domain D , and the static boundary conditions on a part of the boundary aD, belongs to the set L of lower bound solutions (Yang, 1987). We may write L = S r l C, where S denotes the statically admissible set and C denotes the constitutively admissible set of the stresses. Considering the load factor, h E R,h 3 0. We seek the largest possible value of h. This limit analysis problem can be stated in the language of optimization as maximize subject to

h(a) V . 6 =0

a.n=ht 60, llallv I

in on

D aD,

(30)

where V. is the two-dimensional divergence operator applied to the plane stress matrix; n is the outward normal vector on the boundary of D ; t is a constant traction vector (preferably normalized) prescribed on a D,. The statement in (30)

Wei H.Yang

3 14

forms the primal problem for which a unique A,,, = h* exists. The load factor h now has the form of a functional. The problem (30) has a dual whose minimum is equal to h*. To formulate this dual problem, we begin with the weak equilibrium equation,

u.(V.o)dA=O

VUEK,

SD

where u is an arbitrary function in the kinemtically admissible space K C R 2 ( D ) , which consists of all admissible velocity functions. Integrating (31) by parts and using the kinematic boundary condition on the complement to aD, (i.e., a D = aD, U aDk) and the static boundary condition in (30), one obtains an equivalent variational statement of equilibrium,

Lo:cdA=h

1,

t.udS

where c = (Vu+VuT) is the 2 x 2 strain rate matrix. Because u and, implicitly, E appear homogeneously in (32), we may scale u by a constant without altering the value of h. It we choose the integrals in (32) to be positive, the boundary integral can assume the value + I (normalization by scaling). Hence the functional h is equal to the domain integral on the left-hand side of (32). The primal problem (30) can be restated and the value of h bounded as follows:

. where the sequence of inequalities yields the sharp upper functional ~ ( u )We shall seek u E K to minimize this upper-bound functional. Cesari and his coauthors (Cesari et al., 1988; Cesari and Yang, 1991) have identified the correct function space where a minimizing u exists and yield the duality theorem: minp(u) = h* = maxh(o). ueK

U€L

(34)

Numerical solutions of plane stress problems using (34) were presented by Huh and Yang (1991). Similar duality theorems solved the problems of plane strain and plates (Liu and Yang, 1989; Yang, 1987).

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References Birkhoff, G and MacLane, S. (1953). A survey of modern algebra. Macmillan, New York. Cesari, L., Brandi, P., and Salvadori, A. (1988). Existence theorems for multiple integrals of the calculus of variations for discontinuous solutions. Ann. Mat. Pura Appl. 152(4), 95-1 21. Cesari, L., and Yang, W. H. (1991). Serrin integrals and second order problems in plasticity. In: New solutions in differential equations and dynamic systems. Royal Society of Edinburgh, p. 1 17A. Clarke, F. H. (1983). Optimization and nonsmoorh analysis. Wiley, New York. Drucker, D. C. (1959). A definition of stable inelastic material in the mechanics of continua. J. Appl. Mech. 81, 101-106. Hill, R. (1950). The Mathematical theor): ofplasricify. Clarendon Press, Oxford. Householder, A. S. (1954). On norms of vectors and matrices. ORNL Rep. 1759. Huh, H., and Yang, W. H. (1991). A general algorithm for limit solutions of plane stress problems. Internat. J. Solid Structures 28,6. Liu, K. H., and Yang, W. H. (1989). Upper and lower bound solutions of an extrusion problem. Numer. Methods Indus. Form. Proc. 89. Prandtl, L. (1924). Proceedings of the 1st International Congress of Applied Mechanics, Delft, The Netherlands. Reuss, A. (1930). Z. Angew. Math. Mech. 10,266. Royden, H. L. (1988). Real analysis, 3rd edn. Macmillan, New York. Tresca, H. (1864). C. R. Acad. Sci. Paris 59. Tresca, H. (1868). C. R. Acad. Sci. Paris 64. Yang, W. H. (1980a). A generalized von Mises criterion for yield and fracture. J. Appl. Mech. 47, 297-300. Yang, W. H. (1980b). A useful theorem for constructing convex yield functions. J. Appl. Mech. 47, 301-303. Yang, W. H. (1987). A duality theorem for plastic plates. Acta Mech. 69. Yang, W. H. (1991). On generalized Holder inequality. Nonlinear Anal. 16(5).

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ADVANCES IN APPLIED MECHANICS. VOLUME 34

Forced Generation of Solitary-Like Waves Related to Unstable Boundary Layers OLEG S . RYZHOV and ELENA V. BOGDANOVA-RYZHOVA Department of Muthemutical Sciences Rensseluer Polytechnic Institute Troy. New York

I. Introduction: Historical Perspective . . . . . . . . . . . . . . . . . . . . . . . . . A . Two Routes to Transition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B . Multistructured Boundary Layers . . . . . . . . . . . . . . . . . . . . . . . . C . Soliton Emission in Forced BDA and KdV Systems . . . . . . . . . . . . . . I1. TheTripleDeck . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A . General Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B . Governing Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C . Particularcases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

318 318 320 323 326 326 329 332

I11. The BDA System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 335 A . Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B . Free Oscillations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 C . Some Characteristic Features of Forced Oscillations . . . . . . . . . . . . . . 346 349 D . Weak Disturbances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Slow Solitons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352 F. The First Bifurcation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 361 G . Gradual Evolution of Disturbances . . . . . . . . . . . . . . . . . . . . . . . 366 H . TheSecondBifurcation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I . Disturbance Generation by Cavities . . . . . . . . . . . . . . . . . . . . . . . 371 IV . TheKdVSystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 376 A . Crossflow Instability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Description of Free Oscillations in Terms of Elliptic Functions . . . . . . . . 381 C . Some General Properties of Forced Oscillations . . . . . . . . . . . . . . . . 384 386 D . Stability Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E . Slow Disturbance-Generation Process . . . . . . . . . . . . . . . . . . . . . . 389 F . Bifurcation and Gradual Evolution . . . . . . . . . . . . . . . . . . . . . . . . 393 V . Solitons and the Onset of Random Disturbances . . . . . . . . . . . . . . . . . . 403 A. Randomization Triggered by a Harmonic Source . . . . . . . . . . . . . . . . 403 B . Formation of Solitons inside Erratically Distributed Signals . . . . . . . . . . 408

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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ADVANCES IN APPLIED MECHANICS. VOL . 34 Copyright 0 I Y Y X by Academic Press . All rights of reproduction In any form reserved . (X)h5-2165/98$25.00

318

Oleg S. Ryzhov and Elena V. Bogdunovu-Ryzhovu

1. Introduction: Historical Perspective A. TWO ROUTESTO TRANSITION In an incompressible, steady, two-dimensional boundary-layer flow on a flat plate, instability evolves in the form of Tollmien-Schlichting (TS) linear eigenmodes if the Reynolds number exceeds a certain critical value. A linear stage of the wave development can be kept approximately two-dimensional over a long distance, provided that a disturbing source (a vibrating ribbon, as a rule) is carefully controlled during measurements. The first manifestation of nonlinearity is fairly weak and goes hand in hand with three-dimensionalization of the velocity field (see, for example, Schlichting, 1955). The vortex loops resulting at a later stage from the breakdown of the two-dimensional TS wavetrains appear in a staggered array. This is typical of the so-called N-route to transition experimentally observed by Kachanov et al. (1977), Saric et al. (1981), and Corke (1990) in wind-tunnel tests with artificially excited mild disturbances. The mechanism of the N-breakdown is related to the parametric resonant amplification of background subharmonic modes as they interact with an exponentially growing primary TS wave. The possibility that this scenario can become operative in viscous shear flows has been theoretically predicted by Craik as far back as 1971 and indicated by Smith and Stewart (1987) by extending the weakly nonlinear theory. Its basic concepts have been advanced in general terms by Landau (see, for example, Landau and Lifshitz, 1944) and worked out in great detail by Stuart (1960). Another explanation for the same data is due to Herbert (1988), who exploited the Floquet approach in his analysis of the resonant-triad interaction. The importance of a critical layer in the interaction process of the parametricresonance type was emphasized by Goldstein and Lee (1992) and further elaborated by Wundrow et al. (1994), as applied to a pair of oblique modes of small amplitude. In the latter case the fundamental has a good chance of becoming nonlinear within its critical layer before it is influenced by the subharmonic. For a review of different weakly nonlinear mechanisms, including wave/vortex interactions, see Cowley and Wu (1993). The most striking feature of current developments in weakly nonlinear stability theory is that the growing-wave amplitudes are determined from integral-differential equations with quadratic-to-quartic-type nonlinearities (Goldstein, 1994, 1995). With a stronger disturbing source and, accordingly, larger input oscillations, the N-route to transition gives way to the K-regime originally discovered in famous experiments by Klebanoff and his colleagues (Schubauer and Klebanoff, 1956; Klebanoff and Tidstrom, 1959; Klebanoff et al. 1962). Recent observations

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by Kachanov et al. (1989)revealed in the second scenario of transition the existence of an essentially nonlinear two-dimensional stage of TS wave amplification, which precedes a strong three-dimensionalization of the velocity field that begins to play an important part at some position farther downstream. When the TS wavetrain enters this stage, the nearly harmonic shape of a signal is heavily distorted, and each oscillation cycle on the velocity oscilloscope traces contains a sharp spike (or flash), the magnitude of which can amount to as much as 3040% of the velocity at the outer edge of a boundary layer. The thatching tendency of vortex loops before breakdown turns out to be completely suppressed, and they emerge in streamwise rows featuring the K-route to transition. Earlier attempts to shed light from the theoretical side on the mechanism of spike generation in the K-regime depended on the concept of local secondary high-frequency (LSHF) instability of shear flows (Betchov, 1960;Tani and Komoda, 1962;Greenspan and Benney, 1963;Landahl, 1972).The essence of this mechanism lies in the rapid growth of high-frequency fluctuations under the influence of instantaneous inflectional mean-velocity profiles that arise and die out locally in time and space in the flow field due to the amplification of a primary low-frequency TS wave. For almost 30 years this simple idea dominated in providing guidelines for the mathematical treatment of narrow flashes registered on oscilloscope traces. Experiments of Nishioka et al. 1980)on channel-flow disturbances seemed to confirm the LSHF instability approach, in general, and a criterion put forward by Landahl(1972), in particular, in spite of the fact that the K-route to transition in a Poiseuille flow is unlikely to be the same as in a boundary layer on a flat plate. The next step has been taken by Borodulin and Kachanov (1988,1990),who showed that the mechanism of LSHF instability really took place in the K-regime of breakdown; however, this was not the immediate cause of the spike generation. What is more, high-frequency unstable oscillations take place in a near-wall region, whereas the spikes prove to be more elevated above a solid surface and move toward the upper reaches of the boundary layer as their amplitude increases in the course of propagation downstream from an outer source. The two disturbances in question are inherently different and separated in space. Careful processing of experimental data led Borodulin and Kachanov (1988,1990)to conclude that the spikes are almost certainly of soliton nature, although the type of boundary-layer solitons was not identified in wind-tunnel tests. More specifically, Borodulin and Kachanov (1988)claimed that “Despite the existence of the rather strong dispersion of the instability waves . . . the spikes do not disperse but, on the contrary, focus in narrow flashes and propagate steadily downstream within the boundary layer almost without change of their shape and amplitude.” Finally, on the basis of these and some earlier observations, a remarkable statement was made in the

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same paper: “It is highly probable that the behavior of the spikes . . . can be described within the framework of a theory of solitions.” The hypothesis set forth was discussed in a number of subsequent investigations summarized by Kachanov (1991, 1994). Thus the soliton nature of the spikes on the velocity oscilloscope traces was perceived by experimentalists quite independently of the progress in nonlinear stability theory.

B. MULTISTRUCTURED BOUNDARY LAYERS On the theoretical side, the idea of a multistructured boundary layer appeared to be especially suitable for investigating stability properties of viscous flows. It goes back to two papers by Goldstein on the near wake behind the trailing edge of a flat plate (1930) and separation from a smooth surface (1948). To make the mathematical procedure easier, Goldstein (1930, 1948) subdivided the boundary layer itself into two sublayers with different properties. As sometimes happens, the full importance of this idea remained unappreciated for many years by theoreticians immersed in work on similar problems. Only much later did Stewartson (1969) and Messiter (1970) breathe new life into Goldstein’s work by reformulating the original Prandtl approach to the boundary-layer theory. As a matter of fact, this turned out to be a crucial point, because the pressure gradient in the system of parabolic equations derived by Prandtl ceased to be a known quantity obtainable from a solution for the potential flow field; on the contrary, in the modern theory it is subject to simultaneous evaluation with the velocity vector components due to the process of viscouslinviscid interaction. An analogous concept, and just at the same time, was advanced by Neiland (1969) and Stewartson and Williams (1969) in their efforts to shed light on the main features of supersonic boundary-layer separation. In connection with the latter topic, mention should also be made of Lighthill, who recognized as far back as 1953 the mathematical background behind the upstream influence reported in observations on the shockwavehoundary -layer interaction. The work outlined above is concerned solely with steady phenomena; no timedependent problems were considered by the inventors of the triple-deck theory describing the boundary layer with the self-induced pressure gradient. About 10 more years had flown by before Smith (1979) and Zhuk and Ryzhov (1980) independently showed that the viscouslinviscid interaction process is capable of including instability in predictable properties of shear flows, the eigen solutions to the linear version of the theory being nothing more or less than the asymptotic forms of TS waves. This discovery is nontrivial insofar as the original parabolic boundary-layer equations due to Prandtl do not admit eigenmodes at all for flows

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moving forward (reversed motions may exhibit instabilities). Since that time the triple-deck theory has played an important part in the inquiry into conditions that are at the heart of the stability loss inherent in various types of viscous flows, as well as in efforts intended to reveal essential mechanisms controlling the nonlinear stages of disturbance development and propagation prior to transition. However, the underlying scheme is steadily becoming more intricate and refined as the disturbance amplitude grows above a certain threshold value. The first analysis of larger pulsations (as compared to those adopted within the triple-deck scheme) has been reported by Zhuk and Ryzhov (1982) and later on by Smith and Burggraf (1985). They independently arrived at the conclusion that the next, truly nonlinear 2D stage of the wave motion in the Blasius boundary layer on a flat plate obeys an integral-partial differential evolution equation introduced into mathematical physics by Benjamin (1967) and Davis and Acrivos (1967) and identified at present with their names. The BDA equation controls the instantaneous displacement-thickness oscillations in an additional adjustment sublayer positioned between the main and lower decks. The wave process as a whole is driven by purely inviscid interactions taking place in the upper deck and the adjustment sublayer. However, no attempt was made in either paper to provide a link between this discovery and experimental data known at that time from numerous wind-tunnel tests (Schubauer and Klebanoff, 1956; Klebanoff and Tidstrom 1959; Klebanoff et al., 1962) and to assess the significance of the LSHF instability concept as applied to the K-route to transition. Nevertheless, the theory based on the BDA model unambiguously pointed to the fact that weakly nonlinear notions lose their meaning as the number of frequency and wavenumber harmonics tends to infinity and the amplitudes of all of the successive modes become comparable prior to a strong three-dimensionalization of the velocity field. The LSHF instability approach turns out to be invalid before K-breakdown, with a sharp spike imbedded in each oscillation cycle, can be reached. To the contrary, the N-route to transition with a tendency for the vortex loops to be formed in a staggered array is adequately predicted using weakly nonlinear description since only the fundamental and a pair of oblique modes are at the bottom of the parametric-resonance amplification (Craik, 1971; Smith and Stewart 1987; Herbert, 1988; Goldstein, 1994,1995). Theoretical indications to the soliton nature of 2D large-sized disturbances in the Blasius boundary layer on a flat plate came from a computational work by Ryzhov and Savenkov (1989, 1991) on the essentially nonlinear wave-packet development under the classical triple-deck scheme. When processing computed skin-friction distributions they observed extremely stable negative spikes within several central oscillation cycles of a modulated signal. Positive wings of the same

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cycles in the skin-friction distributions were prone to the influence of short-length wiggles giving rise to the rapid distortion and breakdown of the wave packet. In the papers cited the negative spikes were for the first time clearly identified with BDA soliton-like structures. Further evidence for the soliton nature of 2D large-sized disturbances propagating through the Blasius boundary layer stemmed from Ryzhov (1990) who made use of one-periodic three-parameter solution found by Benjamin (1967). It was shown that this solution tends to a linear TS wavetrain as the disturbance size gets indefinitely small. Evidently, a match with the earlier triple-deck stage is achieved in this way. In the opposite limit of large amplitudes, one-periodic solution in question defines a soliton travelling against non-zero background perturbations. However, the most important conclusion ensues from the spectral decomposition of the solution in a Fourier series. In full accord with aforementioned measurements of Borodulin and Kachanov (1988,1990) which comprise about 20 modes, the amplitudes of the successive Fourier components constitute a geometrical progression. Moreover, in the theoretical representation all the modes are in phase and this prediction again agrees well with experimental data from Borodulin and Kachanov (1988,1990). The theory developed implies, in essence, that the BDA solitons are nothing but nonlinear TS eigenmodes. A detailed comparison of theoretical concepts based on the homogeneous BDA equation (Ryzhov, 1990) and results of wind-tunnel measurements (Borodulin and Kachanov, 1988,1990) is made in Kachanov et al. (1993). This comparative study confirms that an essentially nonlinear stage of the TS wavetrain development behind a vibrating ribbon comes first under carefully controlled test conditions whilst three-dimensionality begins to play an important part at some position farther downstream. According to observations, LSHF instability coupled with the parametric resonant amplification of a great many background subharmonic modes are likely at the heart of three-dimensionalization of the velocity field. However, the 2D behaviour of disturbances at the initial nonlinear stage is clear cut in experimental distributions exposed and these distributions adhere to the BDA system. Close agreement between predictions within the framework of the BDA equation and data from extremely precise measurements provides solid grounds for the mathematical model to be exploited in research on transitional boundary-layer flows. The comparative study by Kachanov et al. (1993) leaves no questions that the famous spikes featuring each oscillation cycle on the velocity oscilloscope traces of K-route to transition in the Blasius boundary layer are of the BDA-soliton nature. As applied to hydrodynamic stability theory, the celebrated Korteweg-de Vries equation have been brought into use in the same papers by Zhuk and Ryzhov

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(1982) and Smith and Burggraf (1985) in connection with some specific 2D motions of a viscous fluid. This arises also in an analysis of jet-like near-wall crossflow disturbances developing in a steady 3D boundary layer and propagating in the spanwise direction (Ryzhov and Terent’ev, 1995,1996). Again, the triple-deck regime of viscoushnviscid interaction gives way to a truly nonlinear soliton stage if the wave amplitude attains sufficiently large magnitudes. A new adjustment sublayer emerges to separate the main and lower decks. The disturbance pattern within the adjustment sublayer proves to be inviscid and drives the oscillation process as a whole. Thus, KdV solitary waves appear as nonlinear crossflow eigenmodes, much as BDA solitons serve to represent nonlinear TS eigenmodes developing in the streamwise direction. No wind-tunnel measurements have been conducted so far to substantiate the existence of the solition stage in jet-like crossflow disturbances in a straightforward way. Nevertheless, the success scored in treating the spikes on the oscilloscope traces characteristic of K-breakdown in terms of BDA solitons makes the relevance of similar concepts with regard to nonlinear crossflow eigenmodes in a general 3D boundary layer to be quite plausible.

c. SOLITON EMISSIONIN FORCEDBDA A N D KDV SYSTEMS Until recently, only the homogeneous versions of both BDA and KdV models to examine the propagation of nonlinear solitary-like wavetrains were studied in different branches of physics. For this reason the work done is confined mostly to free oscillations in boundary-layer flows, leaving aside an important issue of their generation by external disturbing agencies. General properties of the solitonemission process are hardly amenable to analysis by habitual mathematical tools, such as conservation laws, pole expansions in a complex plane, inverse scattering transforms, Lax pair, etc. (see, for example, Drazin and Johnson, 1989; Ablowitz and Clarkson, 1991). In point of fact, the simplest one-periodic and soliton solutions are utilized at present in describing the velocity fields of free oscillations. If a forcing term enters the right-hand side it makes all of the powerful techniques mentioned inapplicable to the two evolution equations in question. Even solitons do not strictly satisfy the inhomogeneous models with an arbitrary excitation included. The lack of an adequate theory explains the fact that the disturbance generation governed by the forced BDA as well as KdV equations is scarcely investigated. The first effort to fill this gap (at least partially) was mounted with regard to the inhomogeneous KdV system by Akylas (1984), Cole (1985), Wu (1987) and Camassa and Wu (199 la, b) in their analysis of forced solitary waves in a shallow water channel, as well as by Grimshaw and Smyth (1986) who considered res-

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onant flow of a stratified fluid over topography. The forced KdV equation finds also important use in modelling such atmospheric processes as the generation of the waves behind a mountain ridge, or such oceanic events as Rossby waves and tidal flows over sills. In all these environments we are naturally led to a problem of solitary-like waves emitted and sustained at nearly resonant conditions. The basic mechanism underlying the remarkable phenomenon in question allows a non-stationary response, in the form of a sequential upstream generation of KdV solitons, to a forcing excitation stationary in character and held close to resonance. On the other hand, stable stationary solutions of the forced KdV equation prove also to be in existence Camassa and Wu (1991a, b). An analogous property is inherent in the inhomogeneous BDA system introduced somewhat later by Grimshaw (1987) in connection with resonant forcing of coastly trapped disturbances and by Mitsudera and Grimshaw (1991) while examining effects of radiative damping on resonantly generated internal gravity waves in the atmosphere. Results of the computation based on this system are also available in Zhuk and Popov (1989). Again, upstream advancing solitons emitted at nearly resonant conditions by a steady forcing agency are the most conspicuous outcome of the work under discussion. As for the disturbance patterns downstream of the forcing, predictions ensuing from the earlier analysis turned out to be far less lucid, though solitary-like structures were identified here in some regimes. It cannot be said that experimental verification of the soliton-generation theory exposed above has been carried out on a scale allowing an exhaustive comparison to be made. Nevertheless, solitary-like disturbances typical of theoretical findings were present in experiments by Baines (1984) with two-layer flow over topography and registered by Farmer and Denton (1985) in tidally provoked stream over a sill. More recent data of careful measurements of Lee et al. (1989) of water-wave characteristics show a broad agreement with various physical models including that leaning upon the forced KdV equation. Much less evidence for the relevance of the BDA soliton-emission process to naturally occurring phenomena is reported so far. Christie (1989) advances convincing arguments in favour of the BDA nature of travelling disturbances in the lower atmosphere. However, the origin of internal atmospheric solitary waves is associated by Doviak and Christie (1989) with frequent thunderstorms. Thus an initial-value problem has to be posed for the homogeneous BDA equation to theoretically elucidate conditions leading to their excitation. A mechanism revealed in the context of the forced version of the BDA model to continuously feed the soliton emission by a steady disturbing source still calls for direct tests. In the context of the boundary-layer nonlinear stability theory, both the forced BDA and KdV systems are studied in depth by

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Bogdanova-Ryzhova and Ryzhov (1995a, b, 1996). Distinctions between their work and the aforementioned analysis arise from a definition of an external agency entering the right-hand side of equations. If a study is pursued in terms of boundary-layer flows, a hump or dent typically serves as a disturbing source. This is important since for different environments, disturbing sources of the other kind may come into play. In addition, the same disturbing source operating in different environments can yield different right-hand-side terms of the inhomogeneous BDA and KdV equations. The definition adopted in the boundary-layer theory results in specific similarity laws peculiar to streamwise and crossflow disturbances. On the assumption that the shape of an obstacle does not change in time, its area (mass) occurs as a single similarity parameter in the former case, whereas the moment of the hump/dent area (mass) plays the same role in the latter case. Insofar as disturbing sources can be disparate in nature, a variety of similarity laws are intrinsic to solitary-like wave generation in deep and shallow water as well as atmospheric, oceanic, and other environments. Once the similarity parameter is a key element in mathematical modeling of the disturbance-radiation process, it would appear natural to inquire into changes that may occur in wave systems, both upstream and downstream of an obstacle, when the similarity-parameter magnitude varies in a broad range. The program is realized in Bogdanova-Ryzhova and Ryzhov (199Sa, b, 1996), and the results obtained disclose certain similarities and distinctions inherent in the two forced models. First of all, the disturbance generation proves to be an essentially nonlinear process, no matter how small a value of the similarity parameter. Slow BDA and KdV solitons are the characteristic property of the subcritical regime I coming to an end as the similarity parameter (proportional to the hump mass or the moment of the hump mass, respectively) attains some critical value. With a dent, the emission process evolves smoothly without giving rise to sharp changes in the wave pattern. The first bifurcation in the forced BDA system brings about a specific regime with nearly limit-cycle-type oscillations in the immediate vicinity of the hump (Bogdanova-Ryzhova and Ryzhov, 199Sa, 1996). As a consequence, slow solitary-like waves typical of the subcritical regime I give way to fast solitons radiated upstream and gradually evolving downstream from the last cycles at the rear of the nearly linear oscillatory motion in the supercritical regime 11. Another consequence from a passage of the similarity parameter through the first critical value is an abrupt increase in the disturbance amplitude. However, it becomes less than half as low as the size of each peak in vigorous pulsations at the crest of the hump. Thus fast solitons discharged to a fluid by the even stronger wave motion over an obstacle are the most conspicuous feature of the supercritical regime 11,

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which continuously turns to the subcritical regime I11 at the threshold of the second bifurcation in the forced BDA system. Upon passing through the second critical value of the similarity parameter, the nearly periodic regime close to the hump collapses into irregular pulsations with erratic sequences of amplitudes and reference times. Chaotic behavior becomes much more pronounced in the new supercritical regime IV as the similarity-parameter magnitude grows further on. A bifurcation of the first type separates the subcritical regime I from the supercritical regime I1 and triggers the nearly periodic emission process in the forced KdV system as well (Bogdanova-Ryzhova and Ryzhov, 1995b). Limit-cycle-type oscillations occurring in the two forced models bear close resemblance creating striking parallels between them. The basic mechanism underlying the manifestation of the periodically produced solitary-like waves can be attributed to their excitation as nonlinear eigenmodes in both systems. On the other hand, the shapes of the corresponding limit cycles in the phase plane display some intrinsic characteristics depending on the model in question. These distinctions are likely to be responsible for the absence of the second bifurcation in the forced KdV system, where the supercritical regime I1 persists without developing smoothly into subcritical regime 111, to terminate in the erratic generation of disturbances peculiar to the supercritical regime IV (at least in a similarity-parameter range studied). The compound BDA-KdV system exhibits some features that are completely different from those inherent in both parent BDA and KdV models, taken separately. This new system admits of very fast solitons arising amid and from the “foam” of erratically distributed signals behind the disturbing hump. 11. The Triple Deck

A. GENERAL DESCRIPTION As has been mentioned in the Introduction, the concept of soliton-bearing systems when applied to boundary-layer flows derives from wind-tunnel tests with roots stretching back into mid-1950s and 1960s (Schubauer and Klebanoff, 1956; Klebanoff and Tidstrom 1959; Klebanoff et al., 1962). In those early measurements with artificially excited disturbances, the K-route to laminar-turbulent transition was observed for the first time in a Blasius boundary layer. The K-type of breakdown was clearly shown to be characterized by the occurrence, on the velocity oscilloscope traces, of strong short-time flashes imbedded in each oscillation cycle, upon an initially harmonic TS wavetrain entering the essentially nonlinear stage of its development. The size of the spike typically reaches about 3040% of the velocity at the outer edge of the boundary layer. Reliable data on the spike

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location were obtained in more recent replicas of the aforementioned experiments by Borodulin and Kachanov (1988,1990). They conclude that the spike originates within the lower part of the boundary layer and then moves toward its upper edge as the disturbance amplitude increases. The distortion of the signal shape beginning from a nearly linear monochromatic motion up to the appearance of the short-scaled large-sized flash-spike within each period of the fundamental wave is demonstrated in Figure 1, taken from Kachanov et al. (1993), where data of extensive measurements of Borodulin and Kachanov (1988, 1990) have been summarized. The negative flashspike stands out sharply against the gently sloping positive wings of much lower amplitude. On the basis of their observations, Borodulin and Kachanov (1988) claimed that the behavior of the spikes is highly likely to follow a theory of solitons. However, the type of solitons remained to be specified. Theoretically, the first indication of the soliton nature of nonlinear large-sized disturbances came from a numerical study of wave packets within the framework

x' = 330 rnrn

0

1

-T' 2

1'

F I G . I . Formation of the flash-spike in the experiment as a function of the distance x * from the leading edge of a flat plate (from a discussion in Kachanov et al., 1993, based on observations by Borodulin and Kachanov, 1988). Normal-to-wall coordinates are taken in measurements to correspond to the maximal spike magnitude. Reprinted courtesy of Cambridge University Press.

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of the triple deck (Ryzhov and Savenkov, 1989, 1991). This asymptotically valid structure was invented by Stewartson (1969) and Messiter (1970) for removing a singularity arising in the classical boundary-layer flow at the trailing edge of a flat plate. An extension of the theory by Smith (1979) and Zhuk and Ryzhov (1980) makes it possible to inquire into the linear as well as the nonlinear stability of the steady motion of a viscous fluid adjacent to a solid surface, on the assumption that the Reynolds number R takes on sufficiently high values. In what follows, the fluid is assumed to be incompressible and of density p * . The Reynolds number is defined as

R=

p* U& L*

w*

’

where U& designates the velocity of an oncoming stream, p* is the viscosity coefficient, L* stands for the reference length (a distance from the leading edge of a body, for instance), * is used to indicate dimensional quantities, and 00 relates to the condition at infinity. The introduction of a small parameter E = R-’/* is at the heart of a rational analysis developed in terms of the method of matched asymptotic expansions (see, for example, Cole, 1968). To make the general picture of the nonlinear disturbance evolution clearer, let us begin with the triple-deck stage applied to an initially steady 3D boundary layer. The groundwork of an approach given below relies on a uniformly valid model recently advanced by Ryzhov and Terent’ev (1995, 1996) for achieving a unified treatment of various eigenmodes with both the moderate and large wavenumbers. This model opens the door to introducing the BDA and KdV equations in the context of nonlinear hydrodynamic stability theory. To be specific, we assume the solid surface to be a swept flat plate that can involve a small local roughness as a disturbing source. Experimentally, the crossflow in the near-wall region originates because of an almost constant pressure gradient imposed from outside with a displacement body on top. The infinite swept condition, with no variations in the stationary pressure distribution as well as external velocity field in the spanwise direction, is accomplished by inserting appropriately contoured end plates (Saric and Yeates, 1985; Reed and Saric, 1989). A schematic of the triple deck is shown in Figure 2, where the primary streamwise flow U:(y2) and spanwise crossflow W,*(y2) are defined in a sense most commonly in use among experimentalists. Unstable oscillations in the near-wall viscous sublayer I11 are driven by a strong self-induced pressure gradient stemming from the process of viscoushnviscid interaction with the potential velocity field in upper deck I. Most of the boundary layer in the main deck (deck 11) plays a passive role in matching the instantaneous displacement thickness created by

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FIG.2. Schematic of the triple deck, showing the primary streamwise flow and spanwise crossflow in an oncoming 3D boundary layer.

rotational disturbances in the lower deck to the potential pressure response in the upper deck (Stewartson, 1969; Messiter 1970). The instantaneous displacement thickness is to be evaluated simultaneously with the velocity field in the near-wall viscous sublayer 111. This feature makes the triple deck dissimilar to the classical boundary-layer theory of Prandtl.

B. GOVERNING EQUATIONS Let t* be the time; x*,y * , z* designate the Cartesian coordinates; u * , v " , w* represent the corresponding velocities; and p* denotes pressure. We suppose the x*-axis to be aligned with the local direction of an external potential flow at the outer edge of the boundary layer, and the z*-axis determines the direction of crossflow (Figure 2 ) . An estimation for the time adopted in the triple-deck scheme is O(e2),the local streamwise and spanwise lengths are both O ( e 3 ) ,whereas a distance along the normal coordinate y* proves to be O ( d ) within the near-wall sublayer. Thus the streamwise as well as the spanwise scales of the triple deck are short compared to the 0 (1) scale, over which the base steady flow varies but

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is large compared to the O ( E ~boundary-layer ) thickness. The near-wall viscous sublayer is 0 ( E ) as thin as the oncoming 3D boundary layer. Accordingly, in the near-wall sublayer, an appropriate scaling of independent variables is given by (2.la)

and the expansions for desired functions read u* =

U & , E ~ ; / ~ U ‘ , v* = U&E3ti’4Uf,

W*

= ~ & & T ; ’ ~ w ’ , (2.2a,b,c)

(2.2d)

p*=p&++*u,E *2 2 tw 112p I ,

to leading order (Stewartson, 1969; Messiter, 1970; Smith, 1979; Ryzhov, 1980). An absolute value tw of the wall shear is included in (2.1) and (2.2) to rule out this entity from a set of governing equations and boundary conditions. Upon substituting (2.1) and (2.2) into the original system of Navier-Stokes equations, we arrive at the Prandtl equations

a v f awl -au’ + + = o , azf ax‘ ayf

auf

-+u

at’

awl

-+u at’

auf auf 7+v’-++f-

ad

aY‘

azf

awl

awl

ax

,awl

7+v’-++’ax aYf

az‘

(2.3a)

=

apf a 2 d --+ax’ ay2’

=

--+-

ap’

azf

a2wf ayf2’

(2.3b) (2.3~)

where both components ap‘lax‘ and ap‘laz‘ of the pressure gradient in a plane parallel to a solid flat plate are to be evaluated simultaneously with the velocity field. Since the pressure variations across the near-wall sublayer are negligible, we put ap‘lay’ = 0, in keeping with the conventional version of the triple deck. No additional higher-order terms depending on the small parameter E enter (2.3). An interaction law must be specified at this point to express the self-induced pressure pf as a function of the instantaneous displacement thickness 6’ = -A’. This law comes from a consideration of the disturbance patterns in the outer potential region and most of the boundary layer, and the subsequent matching of the two oscillation fields with that obtainable from solving (2.3) supplemented

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with pertinent boundary conditions (see subsequent equations). However, unlike the conventional triple-deck approach, Ryzhov and Terent’ev (1995, 1996) also propose to retain in the interaction law the key correction term and write down a desired relation as

where the coefficient

is the momentum thickness based on the boundary-layer crossflow Wo = W l / U& (see Figure 2). The second term on the right-hand side of (2.4) can be omitted in an analysis of oscillations with moderate values of the streamwise and spanwise wavenumbers when it becomes 0 ( E ) small. In this case the interaction law reduces to the form typical of the conventional version of the triple deck. However, if short-wavelength disturbances are under discussion, then a term with the derivative a2A’/azf2overtakes the integral term in (2.4), giving rise to a spectacular manifestation of the specific jetlike crossflow instability well known from wind-tunnel tests (see, for example, Reed and Saric, 1989). We emphasize that centrifugal forces arising because of the large curvature of stream surfaces in the main deck (deck 11)are of crucial importance for supporting the self-induced pressure and driving the viscoushnviscid interaction process in a 3D boundary layer of the general kind. The instantaneous displacement thickness 6’ = -A’ entering both terms on the right-hand side of (2.4) also appears in the limiting conditions U’ - t,yy’

-+ txA’(t’,x’,z f ) , tx 2 +t:

= 1,

W ’- t z y ’

as y’+

+ tzA’(t’,x’, z’),

GO,

(2.6a, b, c)

for velocity components in a horizontal plane at the upper reaches of the near-wall sublayer. These result from matching a solution sought to that for main deck I1 and render the formulation of the problem in question complete if no-slip conditions Uf

=o,

?Jf

=

~

ay:, at‘ ’

w’= o

at

y f = y L ( t ’ , x’,z f >

(2.7)

are taken into account. A function y ; is supposed to be nonzero only in some domain of the (x’,z’)-plane, thereby defining the shape of a local roughness on an otherwise flat plate.

Oleg S. Ryzhov and Elena K Bogdanova-Ryzhova

332

C. PARTICULAR CASES In what follows two particular cases are of special interest. The first of them relates to 2D TS waves propagating in the Blasius boundary layer. Under these circumstances we need to put w‘ = a/az‘ = t, = D,, = 0 along with tx = 1 in the governing equations (2.3), interaction law (2.4), (2.5), limiting conditions (2.6), as y’ + 00,and no-slip conditions (2.7). Allowing for the independence of the instantaneous displacement thickness from the spanwise coordinate, the interaction law becomes

The second case is based on short-wavelength oscillations nearly in the direction of crossflow Wo. On suitable rescaling of both the independent variables and desired functions, we are left with

-aa +Vy ff- = oawf , azf

(2.9a) (2.9b)

where the self-induced pressure,

p =--

a2A’

(2.10)

azi2 ’

is created by centrifugal forces due to warping of stream surfaces, mainly in the spanwise direction (Ryzhov and Terent’ev, 1995, 1996). The x’-momentum equation turns out to be of higher order and for this reason separates from (2.9). Similar to simplifications underlying the first case dealing with TS waves, (2.9) and (2.10) lay the groundwork for examining predominantly 2D jetlike crossflow disturbances. What is more, there exists an exact analogy between the disturbed crossflow motion and steady as well as unsteady phenomena in a near-wall viscous jet studied in Smith and Duck (1977) and Ryzhov (1982). The limiting and boundary conditions for (2.9) with p f defined by (2.10) read:

w’ - y’ + A f ( t l ,z’),

as

y’ -+ 00,

(2.1 1)

on the strength of (2.6b) and I

= -ay:,

I f (2.12a, b) w‘ = 0 at y’ = yL(t , z 1, atf ’ where t, # 1 is ruled out as the result of an additional normalization.

2,

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333

Indirect clues to the formation of soliton-like structures came first from a computational study by Ryzhov and Savenkov (1989, 1991) of an essentially nonlinear wave packet developing in the Blasius boundary layer. The disturbance was supposed to be induced by a small jet blowing from a narrow slot in a flat plate. Results based on the computation of a potential vortex or sound pulse interacting with a local roughness on an otherwise surface are available in Ryzhov and Timofeev (1995). A schematic of the sound pulse/local hump interaction can be seen in Figure 3. The sound-pulse-pressure distribution, (2.13) far upstream of the hump, is presented in Figure 4, < I is the streamwise coordinate in a moving frame of reference. An equation (2.14) with a = 1, prescribes the hump contour. In this particular example the sound pulse is fairly weak, namely, a value pdax of the excess pressure in its peak equals 0.1. Nevertheless, the interaction process terminates in the generation of an extremely rapidly growing modulated signal, the shape of which downstream of the obstacle is displayed in Figure 5 fort’ = 4.5(T: denotes the wall shear stress less some initial value). It is evident that the high-amplitude wave packet already suffers strong nonlinear distortions at this stage. The parts of two central cycles with negative wall shear are narrower as compared to their wings, where the frictional intensity is positive. The pulsation swing in the negative phases of each

Sound ___c

I

Oncoming SVeam

_____c.

_---

II /

pulse

F II

”-

-

“ “ I

I

Potential flow

I1

Boundary layer

E l

Wall sublayer

&3 II

L

/

/

j-3i

-

€4

_I___-

E3

*

FIG.3. Schematic diagram (not to scale) of the sound pulseflocal hump interaction. The region centered around a hump consists of three decks (I, 11, III), giving rise to a strong streamwise gradient of self-induced pressure.

334

Oleg S. Ryzhov and Elena b! Bogdanova-Ryzhova

FIG.4. Variation of the excess pressure with distance (‘ in an incident sound pulse specified by (2.13) in a moving frame of reference, far upstream of the hump (2.13): p:,, = 0.1, w’ = 5.765.

cycle is greater than that attained in the positive phases. Analogous deviations from the initially near-harmonic form can be seen in the experimentally recorded development of a TS wavetrain in Figure 1. The shape of central cycles is attributed by Ryzhov and Savenkov (1989,1991) and Ryzhov and Timofeev (1995)

F I G .5. Wall-shear-stress distribution in a wave packet generated by the sound pulse, shown in Figure 4, when inpinging on the hump (2.13): f’ = 4.5.

Forced Generation of Solitary-Like Waves

335

to the soliton nature of nonlinear disturbances in the Blasius boundary layer and tied in with the BDA evolution system. This conclusion puts on a firm footing the aforementioned observations made by Borodulin and Kachanov (1988, 1990) in connection with processing experimental data. The next step is to develop a theory of boundary-layer solitons directly based on nonlinear wave equations.

111. The BDA System A. FORMULATION This section is confined to truly nonlinear disturbances propagating through the Blasius boundary layer. We start from the system of Prandtl equations (2.3), assuming that w’ = a/&’ = 0. If the limiting conditions at the outer reaches y’ -+ 00 of the near-wall viscous sublayer (labelled I11 in Figure 2) are supplemented by a constraint for the vertical component of velocity, then (2.6) becomes U’ - y’

-+ A’(t’,x’),

(3.la) (3.lb)

with allowance made for r, = 0 and rx = 1. It might be well to mention that (3.lb) is automatically met if u’, u’, p’, and A’ satisfy both (2.3a,b) and (3.la). Nevertheless, (3.lb) plays an important part in the following analysis. The no-slip conditions at a solid surface y’ = yk(t’, x’) and the interaction law are given by (2.7) and ( 2 . Q respectively. Let us direct our attention again to the velocity oscilloscope traces presented in Figure 1. Mild and moderate distortions experienced by an initially almost monochromatic TS wavetrain at an earlier nonlinear stage of propagation downstream fall within the triple-deck scheme, as clarified above. However, at a later, truly nonlinear stage of the disturbance development, each oscillation cycle is shaped into a narrow, high-amplitude negative spike and much broader positive wings, sketched in Figure 6. Accordingly, to be consistent with experimental evidence, the theoretical treatment of the later stage should incorporate all of these features. First of all, one more small parameter, A, is needed such that E << A << 1. Guided by the disturbance pattern in Figure 6, let us suppose that within the spike zone the relative pressure variations are of size A* (rather than E * , as in the triple-deck theory). Then the viscous near-wall region subdivides into two sublayers with essentially different properties. The new four-deck structure

Oleg S. Ryzhov and Elena V. Bogdanova-Ryzhova

336

.....

~

E3

~

I

I

I

adjustment sublayer

4

t €4

I

,I

*'

€3

FIG 6 Schematic of the intermediate (adjustment) sublayer emerging within the triple-deck structure at the truly nonlinear stage of the TS wavetrain development

for the wave motion is depicted in Figure 6 by dashed lines, and the new intermediate (adjustment) sublayer is indicated by the shaded area. Inside this sublayer, (2.1) and (2.2) are no longer valid; an appropriate rescaling of independent variables is (3.2a, b, c) The corresponding rescaling of desired functions giving rise to 0 (A2) pressure variations reads

f

a

u =-u, E

A 3 V'=(;)

A 2 V,

PI=(--)

p,

A A ' = - E- .

(3.3a,b,c,d)

Since the intermediate sublayer is significantly shorter and thicker than the initial near-wall deck, the term with viscous tangential stresses in (2.3b) becomes negligible, and we are left with the inviscid governing equations (Zhuk and Ryzhov, 1982; Smith and Burggraf, 1985)

au

av

-ax+ - =aoy , au

au

-+u-+vat ax

au ay

(3.4a)

aP =--,

ax

(3.4b)

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337

where p = p ( t , x ) , in view of a p / a y = 0. Thus the adjustment sublayer is akin to a nonlinear critical layer next to a solid wall. As far as the excess pressure p is concerned, it is related to the instantaneous displacement thickness 6 = - A through the integral (2.8) after replacement of x’ and A’ by x and A , respectively. As is evident from (3.2), in the limit A + 1, the thickness of the adjustment sublayer is of the same order as that of the initial boundary layer, and its length becomes comparable to the thickness. According to (3.3), both components of the velocity vector and the pressure then tend to grow to 0(1) quantities (in nondimensional terms). In other words, this limit points to a nonlinear stage governed by the full system of the Euler equations, with the normal pressure gradient necessarily taken into account. At the outer reaches y --+ 00 of the adjustment sublayer, the limiting conditions (3.1) still hold true if t , x , y and u , u , p , A are introducedin place oft’, x’, y’ and u’, u’, p’, A’, respectively. A remarkable property of these limiting conditions is that they furnish an exact solution to the system of equations (3.4), regardless of the dependence of p on A . All that remains to be done is to meet the boundary conditions at the bottom of the adjustment sublayer. For this purpose the new nearwall viscous sublayer within the spike zone must to be considered. The normalto-wall coordinate here, in the lower deck, is rescaled as

(cf. 3.2c), showing that the near-wall deck becomes significantly thinner than that intrinsic to the original triple-deck structure. The oscillation parameters are defined by

(3.6a, b, c, d) They satisfy the classical boundary-layer equations of Prandtl, with the excess pressure PYd

= P ( t ,x )

expressed in terms of the given displacement thickness -Atc, = - A ( t , x ) by the integral (2.8). As usual, the no-slip conditions are prescribed at the wall. The two solutions sought must be matched in a region where the intermediate adjustment sublayer and the near-wall viscous sublayer overlap (see, for example, Cole, 1968). The corresponding procedure is discussed in detail by Zhuk and Ryzhov (1982) and Smith and Burggraf (1985); however, the disturbance pattern

338

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

in the near-wall deck is beyond the scope of this review. The simple result of matching, (3.7) provides a missing boundary condition for the adjustment sublayer involving inviscid wave motion. With (3.7) imposed, the boundary-value problem for the adjustment sublayer becomes closed. The significance of (3.7) is easily perceived if one allows for the fact that the viscous sublayer below is of the classical Prandtl type, characterized by a pressure distribution known in advance. Thus the adjustment sublayer plays an active role in determining the large-sized wave development, and the near-wall viscous sublayer proves to be more passive (at least up to a certain moment when it can experience a singularity). Substitution of (3.la,b) into (3.7) yields a forced integral-partial differential evolution equation:

dX.

(3.8b)

The corresponding homogeneous equation, (3.9) was first derived by Benjamin (1967) and Davis and Acrivos (1967) and, in the context of boundary-layer flows, appeared in Zhuk and Ryzhov (1982) and Smith and Burggraf (1985). As mentioned above, no attempt has been made in the two latter papers to establish a link between this discovery and experimental data of a kind illustrated in Figure 1. Many general properties of (3.9), including conservation laws, pole expansions in a complex plane, inverse scattering transforms, Lax pairs, etc., are currently being studied in depth (see, for example, Drazin and Johnson, 1989; Ablowitz and Clarkson, 1991). On the contrary, almost nothing is definitively known about the inhomogeneous version (3.8) of the BDA equation. We suggest that both the homogeneous and inhomogeneous BDA systems can be used as the basis for the theoretical description of the generation and the subsequent development of soliton-

Forced Generation of Solitary-Like Waves

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like structures in the form of narrow spikes typical of the transitional boundary layer observed experimentally. Certainly, this raises the question of whether the BDA model is trustworthy, as applied to the nonlinear stability analysis.

B. FREEOSCILLATIONS To justify the reliabilty of the BDA model for predicting the spike-soliton properties of a laminar boundary layer at the threshold to transition (as documented in Figure 1 and further illustrated by Figure 6), it is not necessary to consider the general theory of solitons. Instead, we may confine ourselves to a simplest oneperiodic solution to (3.9) derived by Benjamin (1967). This traveling-wave-type solution,

k

w

A=-+ k

-

(1 -

2k(l , 1 - A,cos$

c = k x - wt,

(3.10)

depends on three arbitrary constants w , k and A,y(0 < As < 1). In the limit, as the amplitude parameter A,y+-0, the Benjamin solution must be matched with a linear solution for the boundary layer with zero background perturbations, which holds at the triple-deck stage. The match is easily attainable at the specified conditions, since (3.10) exhibits harmonic behavior:

A = 2ASkcosc

w

+ O(A’),

-

k

- k = 0,

(3.1 la, b)

with A, tending to zero. On the other hand, it is known that the asymptotics of the first root of the dispersion relation connecting the frequency w’ with the real wavenumber k’ of TS waves satisfies (Zhuk and Ryzhov, 1983) 2

a’ = k’

+(1 + i) + . . . 2 4

3

(3.12)

in the limiting case k’ -+ 00. This is precisely the root to controling initial amplification of linear disturbances, the later development of which has been traced in Section 11. Let us take into account the renormalization of the frequencies w’ = ( A / E ) ’ w and wavenumbers k‘ = (A/E)k arising from (3.2a,b), in line with the analysis of the adjustment sublayer. Then (3.12) reduces to (3.11b) within an accuracy adopted above for traveling waves in the boundary layer with no initial background perturbations. Following Ryzhov (1990), we turn now to the spike stage of the TS wavetrain propagation, assuming the relation w = k2 to be valid also for nonlinear pro-

340

Oleg S. Ryzhov and Elena ci Bogdanova-Ryzhova

cesses.' In point of fact, this assumption is not essential for the analysis set forth below, however somewhat simplifies it. Then (3.10) can be written in the form of a Fourier series as

where the entity (3.14) has clear physical sense and is directly measurable in the experiment. A comparison of the properties ensuing from the theoretical consideration of the problem with the wind-tunnel observations by Borodulin and Kachanov (1988, 1990) is at the heart of the rest of this section. However, it is necessary to keep in mind that the application of the two-dimensional theory requires care when it is compared with three-dimensional tests. On the other hand, the spatial character of the disturbance pattern apparently does not play a dominant role in the first stages of their truly nonlinear development. According to recent findings of Kachanov et al. (1989) pertinent to the K-route to transition, strong nonlinear distortions in the shape of a TS wavetrain come first, whereas an essential threedimensionalization of the velocity field becomes noticeable at some position farther downstream. The application of the two-dimensional theory is restricted just to these stages of the spike formation. As known, the spikes appear finally as narrow three-dimensional structures (see, for example, Kachanov, 1991, 1994). A qualitative comparison of the asymptotic results with the experimental data can be carried out without solving the BDA equation. Different normalizations of the normal-to-wall coordinate, cast in (2.lc), (3.2c), and (3.5), show that the subdivision of the near-wall viscous sublayer, which governs the amplification of the self-excited TS wave, does not take place if A = E . One may conclude from this point that the spikes are formed from the initially harmonic oscillations and the near-wall viscous sublayer is the site of their formation, at the tripledeck stage. Next, (2.2), (3.3), and (3.6) also show that the amplitudes of velocity components and pressure have the same order of magnitude throughout the lower deck, remaining unsplit in the case of A = E . The asymptotic treatment of the later development of the nonlinear process, as will be recalled, depends on the experimentally established fact that the spike ' A nonlinear dispersion relation connecting the frequency w and wavenumber k with the amplitude parameter A, is most likely to be derivable from a consideration of a thin near-wall viscous sublayer defined in (3.5) and (3.6).

Forced Generation of Solitary-Like Waves

34 1

occupies only a short portion of each oscillation cycle. This feature, expressed by A >> E , entails two direct conclusions being in a qualitative agreement with the wind-tunnel tests (Ryzhov, 1990). First, since the new intermediate (adjustment) sublayer is thicker, on the strength of (3.2c), than the initial near-wall zone of the self-excited wave, the spikes move away from the wall and toward the upper reaches of the boundary layer as A grows, possibly with reversed flow if A becomes large enough. The same behavior was observed in the experiments. As was clearly shown by Borodulin and Kachanov (1988,1990), the disturbances can divide, in keeping with the theoretical prediction, into two different (upper and lower) types, which have essentially distinct properties. The upper group of signals starts to move away from the wall, giving rise to the spike. The lower group continues to propagate near the wall and produces the typical inflexional instanteneous mean-velocity profiles studied in the LSHF approach. Second, as a consequence of the formation of the adjustment sublayer, a distinction appears between the phase velocity c* = w * / k * of disturbances propagating through it and the phase velocity c’* = a’*of TS waves traveling in the initial near-wall viscous sublayer. In view of (3.2a,b), the former phase velocity has a typical value c* M AU&. As for the latter phase velocity, it obeys an estimate c’* EU& on the strength of (2. la, b). As mentioned above, the flow field within the near-wall sublayer confined to the spike zone is described by the Prandtl equations, with a pressure distribution known in advance if A >> E . Therefore, such a zone cannot serve as a site where the self-excited oscillations originate; it plays a passive role (up to the moment when a singularity comes into operation). Thus amplification of disturbances is accompanied by acceleration of the spike relative to the waves that move within the entire near-wall viscous sublayer. An analogous behavior is found in the experiments. The upper signals, shaped into the spikes, accelerate as they elevate away from a flat plate. As reported by Borodulin and Kachanov (1988, 1990), the speed of the spikes increases by a factor of almost 2 during their formation in the K-route to transition. Qualitative comparisons of the theoretical and experimental results are made in more detail by Kachanov et ul. (1993). We present here only two experimental dependences, showing the spike elevation from a wall (Figure 7a) and its acceleration with the amplitude growing downstream from a disturbing source (Figure 7b). Both are in excellent agreement with the above statements. Following Ryzhov (1990) in quantitative comparisons of predictions from the asymptotic theory with experimental evidence, we notice first of all that the amplitudes of the successive modes in the spectral decomposition (3.13) decrease, in keeping with a geometric progression law in which the common ratio is fixed by

-

Oleg S. Ryzhov and Elena V. Bogdanova-Ryzhova

342

560

(a)

x‘ (rnrn)

760

(b)

FIG. 7. Spike-soliton parameters from a discussion in Kachanov et al. (1993), based on measurements by Borodulin and Kachanov (1988). a) Spike elevation y* from a wall. b) Spike nondimensional speed, c * / U&, Reprinted courtesy of Cambridge University Press.

(3.14). Furthermore, all of the modes in (3.13) are in phase. In this connection, let us apply again to the corresponding conclusions drawn by experimentalists. According to the observations of Borodulin and Kachanov (1988, 1990), there exists “a surprisingly strict hierarchy of harmonics in terms of the frequencies, especially . . . in the stage where the spikes appear and acquire their shape” and “the amplitudes of harmonic pulsations decay in almost rigorous conformity with a geometric progression law.” The common ratio q determined from the windtunnel tests embracing about 20 (!) successive harmonics varies in the range 0.4-0.8. It is remarkable that the stage under discussion extends in the experiment up to x * x 410-420 111111, where the oscillation swing amounts to as much as 25-30% of the velocity at the outer edge of the boundary layer. The valleys of the nonlinear waves recorded on the oscilloscope traces coincide with each other; therefore the phases of the Fourier modes in the spectral decomposition of the signal are synchronized, in agreement with the theoretical inference. Furthermore, the shape of an oscillation cycle in the process of spike formation is determined by the parameter A,\ entering (3.13), (3.14). Different curves in Figure 1 may be viewed as corresponding to different values of this parameter. For example, (3.13), (3.14) correlate very well, for A,\ = 0.65 (Figure Sa), with the trace obtained by Borodulin and Kachanov (1988,1990) at x * = 410 mm and the normal-to-wall position y* = 2.6 111111, where the spike has maximum magnitude (Figure 8b). To continue quantitative comparisons, let us introduce, after Kachanov et al. (1993), the mean value (3.15)

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FIG.8. Quantitative comparison from a discussion in Kachanov et al. (1993) of the forms of the BDA one-periodic solution (3.10), A, = 0.65 (a) and a velocity oscilloscope trace due to Borodulin and Kachanov (1988) (b). x* = 410 mm, y* = 2.6 mm. Reprinted courtesy of Cambridge University Press.

of the disturbance over an oscillation cycle, and a width t o= It2 - c11/2n

= cos-'(q)/n

(3.16)

of the spike defined by the values c 2 and of the local coordinate [ in the moving frame of reference at the points where A(c) = A'. Next we consider the other two form parameters,

A+ = max(A(0) - A'

and

A- = min(A(c)) - A',

which are a maximum positive instantaneous deviation from the mean value and a minimum negative deviation from the mean value, respectively. Expressed in terms of A,, they become

- AS)'I2 as A, -+ 1. The maximum whence A+ + 2k and A- + -2&k/(l and minimum instanteneous deviations give a magnitude

1 2k A, Am = -(A+ - A-) = 2 (1 of the disturbance conveniently used in processing experimental data (Borodulin and Kachanov, 1988,1990). The limiting value A- is indicative of the spike soliton formation (see below). To compare theoretical predictions with experimental data, it is necessary to match the calculated amplitudes with those measured in the wind-tunnel tests. Let u *' be the velocity disturbance obtainable from observations. Then the only matching coefficient,

344

Oleg S. Ryzhov and Elenu K Bogdunova-Ryzhova

FIG. 9. Further comparison from a discussion in Kachanov er al. (1993) of dependences of nonlinear eigenmode parameters on the disturbance magnitude Am = 4c.i' - k) in the theory and experiment. Theoretical curves are derived from the BDA one-periodic solution (3.10); experimental points are due to Borodulin and Kachanov (1988). The downstream direction in the experiment is shown by arrows. a) Spike width 50. h) Maximal positive, and negative, lA-1, disturbance deviations. Reprinted courtesy of Cambridge University Press.

A+,

is chosen to be equal to 0.09 by Kachanov et al. (1993). Therefore new definitions of amplitudes become 2 = BrnIAllk for the theory and 2 = u*'/ U& for the experiment.* It is seen from Figure 9 that the process of spike formation through a certain stage of the disturbance development is well described quantitatively by the theoretical results. As mentioned previously, this truly nonlinear stage is extended, in the observations reported by Borodulin and Kachanov (1988, 1990), up to x* % 4 1 0 4 2 0 mm, where the oscillation swing (in Figure 1) amounts to as much as 25-30% of the velocity U& at the outer edge of the boundary layer. The parameter As reaches maximum values of about 0.67 at the end of the quasi-twodimensional region. The downstream direction is shown in Figure 9 by arrows pointing to rapid deviation of all three parameters, from the corresponding theoretical curves past x* % 420 m. The discrepancy between the predicted and measured values is connected with a strong three-dimensionality in the physical flow at later stages of its evolution. This three-dimensionalization of the velocity field derives from the resonant amplification of definite spatial spectral modes, which acquire, at the later stages, fairly large amplitudes comparable with twodimensional components in Fourier decompositions of the signal. However, threedimensional waves are far beyond the scope of the present review. We may no-

A

*The necessity for ,!Int to be introduced in the comparison becomes clear from the basic scalings (2.1), (2.2), and (3.2), (3.3).

Forced Generation of Solitary-Like Waves

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tice only that the spike width t obecomes much smaller than the one calculated in the framework of the BDA model (Figure 9a). Besides, it is interesting that the essentially three-dimensional stages are characterized by significantly weaker maximum positive deviations but stronger maximum negative deviations (Figure 9b). A passage to a limit k -+ 0, A, -+ 1 with w / k being kept fixed in the periodic solution (3.10) implies, in effect, the occurrence of a soliton within each oscillation cycle. Let (1 - A:) 1I 2 / k = co, co = const; then the Benjamin solution becomes

A+,

1 A=c+-co

A-

4c0

c;

+ (x - ct)2 '

co > 0,

(3.18)

where c = w / k is the normalized phase velocity of a traveling wave. An obvious condition for background perturbations to vanish is c = --cil. As might be expected, the common ratio q in (3.14) tends to 1 in this limit; therefore the spike-soliton width t oshortens to zero in view of (3.16). The limiting mean value A' -+ c i l of the signal comes from (3.15). The maximum positive deviation is A+ -+ 0, in accordance with (3.17a), whereas the minimum negative deviation grows as A - -+ -21/2cO1, on the strength of (3.17b). The latter limiting value has already been shown to hold for the periodic solution (3.10), provided that A, -+ 1. We are now in a position to make an important remark on the solutions of the homogeneous BDA equation that are related to the stability of boundary-layer flows. The one-periodic solution (3.10) can be regarded as a nonlinear eigenmode, to represent an initial TS wavetrain entering the truly nonlinear stage of its development. Nonlinear eigenmodes are a new concept intrinsic to soliton-bearing models; they play a key role in the analysis of wave systems generated by an external source and advancing downstream as well as upstream. The soliton solution (3.18) is an eigenmode of a completely different kind; it has no counterpart in the conventional stability theory (see, for example, Drazin and Reid, 1981). No counterpart of this solution arises in the triple-deck approach controlling the earler nonlinear stage discussed in Section 11. A disturbance originally introduced into the Blasius boundary layer in the pulse mode turns into a modulated wavepacket almost explosively (see Figure 5). However, at the later, truly nonlinear stage governed by the BDA model, the pulse-mode disturbance can exist in the form of a single soliton. In general, the disturbance generation process initiated by a forcing agency gives rise to nonlinear eigenmodes of these two kinds that are excited in the fluid motion at some distance from a wall.

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

346

Certainly the question arises over the reliability of the description of the intricate laminar-turbulent transition process as drawn from the asymptotic theory. The above qualitative and quantitative comparisons with experimental data currently available were designed to show that the BDA soliton-spikes are really an integral part of oscillations in the quasi-two-dimensional region of the K-route to breakdown. Thus, with allowance made for three-dimensionalization of the velocity field farther downstream, the mathematical model put forward by Zhuk and Ryzhov (1982), Smith and Burggraf (1983, Ryzhov (1990), and Kachanov et al. (1993) and examined in many other works gives an adequate account of nonlinear phenomena at the threshold to transition, at least under carefully controlled test conditions (Borodulin and Kachanov, 1988, 1990). The “mass” of the algebraic soliton (3.18) advancing upstream against zero background perturbations is a steplike function defined through

M , = -4cL;

dx

1

+ c(x

-

= 2x - 4 tan-’[c(x - c t ) ]

(3.19)

Cf)*

and tends to 4n, as x + 00, independent of the phase velocity c = -cC1 < 0. This property finds use when the disturbance emission by an external source is analyzed. Evidently, the BDA solitons can move downstream only in the case characterized by the existence of initial depression in the displacement thickness 6 = -A producing a negative background 60 = - ( c c;’). The mass of the soliton sweeping downstream against this negative background remains the same as in (3.19).

+

c. S O M E CHARACTERISTIC FEATURESOF FORCEDOSCILLATIONS We begin by extending the one-periodic solution (3.10) by Benjamin (1967) to the inhomogeneous BDA model (Bogdanova-Ryzhova and Ryzhov, 1995a). Let the forcing term on the right-hand side of (3.8a) be f = i3 P l a x , where a periodic function

P =

a1

1 - A, cos

-

a2 2( 1 - A,scos

c)2’

< = kx - wt

(3.20)

depends on five arbitrary constants w , k , A,, a ] ,and a2. There then exists a periodic solution A,=bl-

b2

1 - Ascost’

(3.21)

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with coefficients bl and b2 given by

(3.22a)

If a1 = a2 = 0 in (3.20), i.e., the forcing agency becomes zero, we find from (3.22) the same values of bl and b2 as those entering the one-periodic solution to the homogeneous BDA equation. An algebraic soliton corresponding to (3.18) can be introduced by passing, in (3.20)-(3.22), to a limit as k -+ 0, A, + 1, with w

-

k

2 1/2

= c,

(1 - A,)

k

a2 k2(1 - A:) = c2

a1 CI _ -_

= co,

k2- 2’

being kept fixed. The final result reads

P =

1 co

A, = C + -

c1

c;

+ (x - ct)2

2c&

-

+ 2co[l + (1 + c2)’/21 Cl

[c;

-

+ (x - ct)2]2’ 2CO[l

c;

+ (1 + c2)1’21.

+ (x

-

ct)2

(3.23)

(3.24)

With the phase velocity c = 0, (3.23) and (3.24) provide a steady solution depending only on x. No steady solution is allowed within the homogeneous BDA model, since co = -c-l + 00 in (3.18) if initial background perturbations are zero. In the general case, let the forcing f ( t , x) be expressed through the Hilbert integral (3.8b) of a2yw/ax2,where y , = y,(t, x) stands for the local roughness shape. On the assumption that both the forcing and the corresponding solution vanish sufficiently fast as x -+ 00, a relation

d X = 0,

M = l o o ( - A w )dx

(3.25)

holds, which implies the mass conservation law M = MO = const. Since A , = y , - 6, the mass of disturbances induced by an external agency is at any time equal to the mass of this agency itself. Hence we have 00

6 ( t , x) dx = S(0, x)

+

348

Oleg S. Ryzhov and Elena K Bogdanova-Ryzhova

provided that y,(0, x ) = 0. The general problem on conservation laws inherent in the BDA equation is considered, for example, by Drazin and Johnson (1989) and Ablowitz and Clarkson (1991). The mass of a soliton propagating against zero background perturbations, fixed by means of c1 = -2(1

+ cco)[l + (1 + c2)'/2],

+ +

is M , = 2 n [ l (1 ~ 2 ) ' / ~where ], c2 can take arbitrary values. In the absence of forcing (cl = c2 = O ) , we obtain M , = 4n,in line with (3.19). As typical of many physical processes, a similarity law plays a vital part in mathematical modeling of the disturbance generation in boundary-layer flows (Bogdanova-Ryzhova and Ryzhov, 1995a). To derive this law, it will suffice to mention that the homogeneous BDA equation is invariant against a group of affine transformations t + p 2 t , x -+ p x , A + p - ' A . In what follows, the forcing is specified as yw = a g ( t / t o ) h ( x / b )with a time-dependent multiplier g = 0 if t 0. Three arbitrary constants to, b, and a are the characteristic time, the reference length, and the amplitude of an outer source. As for positive t , we assume g to be a monotonically increasing function on the interval 0 < t < to, becoming g = 1 with t 3 to. Let us choose /3 = b and apply the affine transformation mentioned to both (3.8a) and (3.8b). The resulting model reduces to

<

aA aAw -+Aw---!!! ax at

- 1 --

n

/m

a2A,/ax2dx

x - ~

-m

Q

t

O0

d2h/dX2 dX. x - x

(3.26)

The two similarity parameters Q = a b and TO = to/b2,appearing here in place of the original three parameters to, b, and B ,define the similarity law for all t and x . It is worthy of note that Q has a very simple physical meaning, being proportional to the area (mass) of an obstacle on an otherwise flat surface. Furthermore, at any sufficiently large moment t >> TO,the motion must become effectively independent of the second parameter TO,owing to the fact that g = 1 in view of our assumption. Thus the only similarity parameter Q , the mass of the disturbing obstacle, turns out to control distinctive features of the oscillation pattern at later stages after switching on the forcing source. Because of the specific form of a function f in (3.8b), the similarity law is presented in terms peculiar to the nonlinear wave generation in a boundary layer. Insofar as disturbing agencies can be disparate in nature, a variety of similarity laws feature the disturbance emission in different environments (deep water, atmospheric and oceanic phenomena). We leave aside an in-depth discussion of

Forced Generation of Solitary-Like Waves

349

similarities that arise from forcing indicated by Grimshaw (1987) and Mitsudera and Grimshaw (1991) for such environmental conditions.

D. WEAKDISTURBANCES Once the similarity parameter Q is a key element in mathematical modeling of the disturbance-radiation process, it would appear natural to study the changes that occur in wave systems both downstream and upstream of an obstacle when Q is continuously growing. To be specific, we set g = t / t 0 (in original variables). So both downstream- and upstream-propagating wave systems evolve from the initial data A, = 0. The shape of a local roughness is prescribed (again in original variables) as -b < x < b.

<

whereas h = 0 for both x -b and x 3 b. Evidently, we have a hump provided that CJ > 0 and deal with a dent if CJ < 0. Computationally, it proved to be convenient to choose to = 1 and b = 3.5. Within these limitations, the results of an extensive study by Bogdanova-Ryzhova and Ryzhov (1995a, 1996) are set forth below for a broad range of the similarity parameter taking on positive as well as negative signs. Let us begin with weak disturbances generated by an obstacle whose area (mass) Q +. 0. Under these circumstances, the natural way to proceed is to derive an analytic solution to (3.26) in the form of an asymptotic expansions in powers of Q, namely,

A, = Qg(t)h(x)

+ QA1 ( t , + Q2A2(t,x >+ . . . . X)

(3.27)

The functions A 1, A2. . . . , are determined by linear equations that can be easily treated by using a standard technique of Fourier transforms. The first one is (3.28) where an overbar is used to define a Fourier transform, (3.29) of h(x). Similar definitions enter the sum

(3.30)

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

350

representing the second function, where the first term

dk,

X

-

h2 =

3 n 4 sink k(n2 - k2)(4n2- k2)

(3.31)

(3.32)

is of main concern, and the second term

plays a relatively insignificant role in developing asymptotics of A2 for large t and x . Figure 10 shows the displacement thickness 6 = - A = - A , y w , calculated by using the first- and second-order approximations of the asymptotic expansion (3.27) for Q = 0.35 at t = 100, r = 400, and t = 700 (dotted lines), as well as the corresponding numerical solutions (solid lines) within the framework of the nonlinear model (3.26). It is pertinent to note that the pseudo-spectral method of Burggraf and Duck (1982), based on applying a fast Fourier transform, appears to be extremely efficient for solving the forced BDA equation numerically.

+

FIG.10. Instantaneous wave patterns predicted by second-order accurate asymptotic analysis and calculated numerically for Q = 0.35 at r’ = 100, 400. and 700.

Forced Generation of Solitary-Like Waves

35 1

This method has been implemented throughout the computations in BogdanovaRyzhova and Ryzhov (1995a, 1996), under discussion here. A quantitative agreement between the two solutions in Figure 10 proves to be surprisingly good, in spite of the fact that a value Q = 0.35 is not small enough for asymptotic theory. However, the agreement tends to deteriorate with time in the near-hump region, where nonlinear effects build up and gradually spread in both directions, downstream and upstream. To substantiate the importance of nonlinear effects in the wave-emission process provoked by an arbitrarily weak disturbing obstacle with Q << 1, we need an asymptotic representation of the solution for large times and distances. As is known, the far-field 1x1 += 00 is obtainable on the assumption that Ikl -+ 0. In that case, (3.28) and (3.29) reduce to a standard integral (Abramowitzand Stegun, 1964) (3.33) Of the two terms, A21 and A22, entering the sum (3.30) for A2 we may confine ourselves to the former, in view of the above comment about the possibility of disregarding the latter in developing asymptotics for large t and x . As for the first term, it takes the form (3.34) ensuing from (3.31) and (3.32) and can be explicitly expressed through another standard integral (Abramowitz and Stegun, 1964): (3.35) The final results, obtainable from (3.33), (3.34), and (3.35) with the constraint that a self-similar variable

v=- I x I

1/2nt

>> I ,

(3.36)

whereas x < 0, read

(3.37a, b) Comparing (3.37a) with (3.37b) leads to a conclusion of conceptual importance: the asymptotic solution (3.27) cannot be uniformly valid everywhere and breaks -Qt, where the linear and down in a region centered around the front x f U

-

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

352

quadratic terms become of the same order of magnitude. An analogous statement holds true with regard to a downstream advancing wave system, with the far field being defined by the same constraint (3.36) as applied to x > 0. In compliance with the above conclusion, the mass M; ( t ) of disturbances upstream of the obstacle may be represented by means of

-/

0

MiT

[ - Q A l ( t , x ) - Q2A2(t,x)- . . . l d x = Qml

+ Q2m2v‘+... ,

--oo

where ml = 0.25, m2 = 0.043. The most interesting point here is that the leading term of the asymptotic expansion (3.27) does not cause an increase in the mass deficit behind the local obstacle situated at x = 0. While the total mass of oscillations, as predicted by (3.25), remains constant over the entire interval -00 < x < 00, the correction function A2(t,x ) provides permanent “pumping” of the mass from the region x > 0 into the region x < 0, thereby initiating the eventual onset of the essentially nonlinear stage, regardless of the sign of Q. A fairly long period T * required for the pumping process to terminate in the nonlinear motion is estimated in terms of Q through (Bodganova-Ryzhova and Ryzhov, 1996)

T* = con~tlQl-~,

(3.38)

i.e., T * -+ 00,as lQ*l -+ 0. The asymptotic solution (3.27) breaks down well before the time t becomes as long as indicated in (3.38).

E. SLOWSOLITONS Numerical data available in Bogdanova-Ryzhova and Ryzhov (1995a, 1996) furnish information in favor of the asymptotic analysis of mass pumping, leading to an estimate of the characteristic time T * given in (3.38). From these data we can also draw firm conclusions about the onset of slow solitary-wave radiation downstream and upstream from an obstacle in the subcritical regime I. However, it is necessary to keep in mind that the task of numerically tracking the wave-system evolution within the framework of the full nonlinear model (3.26) becomes extremely complicated as I Q I + 0. For this reason we begin by presenting the instantaneous displacement-thickness distributions for Q = 0.9 illustrated in Figure 1la. Up to t = 6000, the wave patterns computed have the form of a quasisteady peak above the hump and an oscillatory tongue spreading downstream; both features are already familiar from Figure 10. According to the asymptotic approach, a nonlinear part of the solution starts developing in a region centered around the front x f u moving upstream with a small constant velocity behind the

Forced Generation of Solitary-Like Waves Q-1.5

Q10.9

1

1-6000

1-4000

1-5250

1-3500

t=4500

1-3000

1-3750

1=2500

1=mo

1=2000

1-2250

1-1500

6 1=1000

1=1500

-0.05 : o0 0

500

Y & ! ! E500 L l

1000

0

1000

X

(4

353

X

(b)

FIG. 1 1. Instantaneous wave patterns for small (Q = 0.9) and medium-sized ( Q = 1.5) humps. a) The upstream separating front x f u is still indistinguishable, and downstream front xfd is clearly seen to propagate at the constant phase speed. b) An upstream soliton breaks away from the obstacle, and a downstream solitary-like wave is simultaneously built up at t = Tjt > 4000 (Tjt N 5000 from resuts not shown).

linear disturbances. There appears a similar front x f d sweeping downstream. The upstream front is indiscernible in the displacement-thickness distributions under discussion, whereas the downstream front can be identified with confidence. However, the nonlinear stage becomes conspicuous only when the first soliton emerges ahead of the hump, much later than the nonlinear solution actually sets in between the two fronts. The onset of this event is clearly defined in Figure 1lb, where all of the curves are computed with Q = 1.5. An upstream soliton is seen to be shaping at t = T t ,where Tit > T* defines the incipient transition time, and simultaneously a solitary-like wave appears in the downstream direction. As we may 5000 for Q = 1.5. Thus the occurrence infer from further computation, of separating fronts propagating with constant speeds is an intrinsic property of the disturbance-emission process. However, the weaker the external source is, the more time the nonlinear fronts need to be formed, eventually giving rise to slow solitons.

Oleg S. Ryzhov and Elena b! Bogdanova-Ryzhova

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Examination of the mass

[,a ( t ,x ) d x -b

M-b(t) =

(3.39)

radiated upstream of the hump --oo 6 x 6 -3.5 turns out to be a pertinent means for numerically estimating a value of the characteristic time T *. The behavior of M - b ( t ) responds to the arrival of a separating front by changing the sign of the second derivative d2M-b/dt2 just at that moment T* which marks the end of a linear stage of evolution and the onset of essentially nonlinear motion. Calculated values of T* are plotted in Figure 12 in terms of log T*versus - log Q for humps with Q > 0. It is seen that, to within the accuracy of the numerical error, all of the points collapse into a straight line, with the slope being equal to 3. This is precisely the same relationship as the one given in (3.38) on the basis of asymptotic analysis. An approximate value of the incipient transition time T,, > T* can be found from a condition M-h (T,r ) % 4n. Since the nonlinear wave pattern only starts forming in Figure Ilb, where Q = 1.5, a larger value of the similarity parameter must be taken to elucidate the slow soliton emission by a steady obstacle. However, the process in question strongly depends on whether a hump or a dent is chosen as a disturbing source. With this reservation in mind, we continue the above analysis for humps with Q > 0, and present in Figure 13 the displacement-thickness distributions for Q = 3.92. In full accord with the previous results displayed in Figures 10 and 11, the disturbance field downstream of the local obstacle begins with a long oscillatory “tongue” of small amplitude. This is a common feature of the phenomenon, whatever the value of Q. As in Figure 1Ib, the oscillatory motion ter-

8

7.5

’+ 7 0 -0 6.5

.. 0

6

L’

. .*

.

0

I

-0.7

-0.6

-0.5 -0.4 -0.3

-0.2

-0.1

0 -logQ

FIG. 12. Characteristic time T* as a function of the similarity parameter Q theoretically predicted by (3.38) for small humps with Q --f 0 (dotted line) and calculated numerically (asterisks) from a condition d2M-,,(T*)dt2 = 0.

Forced Generation of Solitary-Like Waves

355

Q=3.92

k350

-100

0

100

200

300

400

X

FIG. 13. Instantaneous disturbance patterns in the subcritical regime 1 ( Q = 3.92). Even at the threshold of the first bifurcation, only a few slow solitary-like waves are seen both downstream and upstream.

minates in solitary-like waves; however, a short intervening region occupied by mild pulsations of a transitional type comes to light in between. A fairly long period T,, 300 of the first solitary-like wave formation still correlates well with the above prediction about the large magnitude of the characteristic time T * associated with weak perturbing agencies. The disturbance system as a whole is separated from the hump by a depression containing smooth variations of s ( t , x), which slowly spreads downstream. The depression area serves as a background for slow solitary waves to gradually evolve from the last cycles bringing up the rear of the modulated oscillatory tongue. To see this, let us recall the conclusion at the end of Section 1II.A that the BDA soliton can propagate in the direction of the oncoming stream only against negative background perturbations. If the background vanishes to zero, the phase velocity c becomes negative and downstream advancing solitons cease building up. Thus the formation of the depression area proves to be a necessary condition for solitary-like waves to arise at the tail end of the modulated oscillatory motion. This stage is not attained by oscillations shown in Figures 10 and 1la, because even the corresponding characteristic times T* < T,, are too large for the perturbing agencies involved.

Oleg S. Ryzhov and Elena V Bogdarzova-Ryzhova

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On the contrary, the flow pattern develops in a much simpler manner upstream of the obstacle. This region is of prime concern in various applications to atmospheric and oceanic sciences (Grimshaw, 1987; Christie, 1989; Mitsudera and Grimshaw, 1991) but does not play an important part in boundary-layer study. As we may conclude from distributions in Figure 13, the first solitary-like wave appears here at t = 550 in the well-shaped form, whereas the second is being generated just in the vicinity of the hump. At t = 750, the second solitary wave breaks away from the disturbing source. No oscillatory motion preceding these solitons originates in front of them. The amplitude of the leading solitary wave is approximately twice as large as the disturbance size immediately above the obstacle. As inferred from Figure 13, slow solitons under consideration, which travel in the opposite directions, downstream and upstream, emerge in pairs, although the time and place of their birth are hardly defined, because of the large period T x 300 of this event ( T proves to be approximately equal to the incipient transition time T,?). The way in which 6 varies in the hump region is crucial for the overall process of the solitary-wave emission. As shown in Figure 14, 6 0 ( t ) = 6 ( t , 0) drastically drops, shortly after triggering the external agency, and then gradually changes

.

I

3.93

6-

5-

- 40

uo"

3-

2-

I

L

3.92

: : J

0

100

200

300

400

500

600

t

FIG. 14. Displacement thickness So at the hump crest as a function of time t in the subcritical regime I ( Q = 3.92) and the supercritical regime I1 (Q = 3.93). Vigorous pulsations are created by the first bifurcation, occurring within an interval 3.92 < Q < 3.93.

Forced Generation of Solitary-Like Waves

357

around 60 x 0.5, which may be roughly regarded as a mean value. The slack run of 6 o ( t ) , with smooth variations confined to a very narrow band, is at the heart of the aforementioned large period T 300 of both the solitary-like wave evolution at the tail end of the oscillatory motion downstream and the soliton radiation upstream. The behavior of & ( t ) correlates well with the existence of a quasi-steady peak at the crest of the local unevenness that was seen to persist throughout the computation in Figures 10 and l l a for Q = 0.35 and Q = 0.9, respectively. In turn, because of the large T , the solitary waves discharged to the boundary layer in the opposite directions are of moderate amplitude and therefore move slowly both downstream and upstream. Small-amplitude pulsations over the hump as well as the generation of slow solitons are two distinctive features of the subcritical regime I.

F. THEFIRSTBIFURCATION The smooth evolution of wave systems suddenly comes to an end in an attempt to further increase a value of the similarity parameter beyond Q = 3.92. The flow field changes drastically, with Q growing within a narrow interval, 3.92 < Q < 3.93, where the first bifurcation takes place (Bogdanova-Ryzhova and Ryzhov, 1995a, 1996). The very existence of a threshold value Q = QT can be easily deduced from a consideration of the mass M-b = M-b(t) transported by the wave system upstream of the hump (--00 < x -3.5). As seen from the plots of Ik-b/4n computed on the basis of (3.39) and presented in Figure 15, a solution for Q = 3.92 inherent in the subcritical regime I with Q < QT suffers stability loss if the controlling similarity parameter increases by only 0.01 and becomes Q = 3.93. Obviously, a new solution arising from bifurcation must be endowed with completely different properties; this solution is typical of the supercritical regime I1 specified by Q > QT. According to computed results, bifurcation occurs at that instant that corresponds to the incipient transition time Ti, M 150. Thus the transition time shortens by a factor of 2 when passing from Q = 3.92 through the critical value Q = QT to Q = 3.93. This happens because an earlier (and weaker) phase of disturbance generation still belongs to the subcritical regime I; however, as soon as the mass of disturbances upstream of the hump amounts to about half of the mass of the BDA soliton, the process turns to the next (and more intensive) phase related to the supercritical regime 11. Noteworthy is the specific steplike behavior of a curve in Figure 15 drawn for Q = 3.93. Each step is associated with the birth of a soliton whose mass M rgrows, by virtue of (3.19), from 0 to 4n as a steplike function. So the number of steps determines the number of upstream emitted solitary waves. Hence it follows that the period T re-

<

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

358 10-

3.93

lo[ 98-

7Y

s t:

6-

4 5-

5:

433.92

21I

0-

I

I

t F I G . 15. The mass M - b transported by the wave system upstream of the hump as a function of time t in the subcritical regime I (Q = 3.92) and the supercritical regime I1 ( Q = 3.93).

quired for the production of a single solitary wave can be estimated as T x 18 (cf. T 300 if Q = 3.92). What this means is that the fast, rather than slow solitons are typical of the supercritical regime 11. On the strength of (3.18), the amplitude of the fast solitons grows proportionally with the absolute value of their phase velocity c, notwithstanding the fact that their mass remains the same. To further illuminate this statement, the instantaneous displacement-thickness distributions computed at different times with Q = 3.93 are displayed in Figure 16. As is apparent even at a glance, the disturbance patterns are characterized by much larger values of 6 ( t , x ) compared to the corresponding values in Figure 13. Accordingly, a great many solitary waves appear in both directions, downstream and upstream, and they propagate rapidly. However, an overall picture of oscillations bears close resemblance to that intrinsic to the subcritical regime I. The wave system downstream of the roughness remains more complicated and consists of a small-amplitude oscillatory tongue, a short zone of transitional-type pulsations, and solitary waves quickly evolving in the course of the transitional process. A depression region with smooth variations of 8 ( t , x) behind the obstacle again serves as a background, allowing solitary waves to be formed from the

Forced Generation of Solitary-Like Waves

359

Q=3.93

1

t=400

1

t=300

1 1

k250

4-

c; 2 -

1=150

3 0

FIG. 16. Instantaneous disturbance patterns in the supercritical regime I1 (Q = 3.93). Upon the first bifurcation, fast solitary-like waves of much larger sizes appear in place of slow solitary waves both downstream and upstream.

tail-end cycles of the modulated oscillatory motion. One more function of the depression is to compensate for the mass radiated upstream, ahead of the hump. We observe here only a “comb” of fast solitary-like waves that move against a clearly defined nonuniform elevation vanishing at infinity and rising toward the hump. Solitary waves within the comb are arranged in decreasing order of amplitude, where the leading peak is the highest one. The most crucial distinction between the two regimes superseding one another manifests itself in the behavior of disturbances immediately over the hump (-3.5 x 3.5). To shed light on the mechanism at the heart of the fast solitarywave production in the supercritical regime 11, let us come back to the plot of 60(t). As Figure 14 shows, the slack run of this curve when Q = 3.92 gives way, after the end of the incipient transition process, to vigorous peaky-type pulsations of a nearly constant period T x 18 if Q = 3.93. According to the above estimation, this time is required for the production of a pair of solitary waves moving in opposite directions. As a result, the amplitude of the leading solitary-like wave advancing upstream drops to less than half the size of each peak. Nevertheless,

< <

Oleg S. Ryzhov and Elena K Bogdanova-Ryzhova

360

this amplitude exceeds the amplitude of an analogous solitary wave in Figure 13 by a factor of about 4. Since the phase velocity increases proportionally with the amplitude of a BDA soliton, the propagation speed of solitary waves in the supercritical regime I1 is also enhanced several times, so that they are capable of advancing fast enough against the oncoming stream. Being reckoned from the depression level, the amplitude of the solitary-like waves sweeping downstream at the rear of the modulated oscillatory tongue proves to be of the same order as the amplitude of disturbances ahead of the obstacle. One more feature is recognizible and worthy of note in the run of the curve in Figure 14 for Q = 3.93 in connection with the overall evolution of the generation process: a sharp drop of 60(t) within each oscillation cycle experiences a barely perceptible kink before reaching the minimum value. To deduce fundamental properties of the nearly periodic process in the vicinity of the hump, Figure 17 provides its phase portrait in a plane (60, & = d6o/dt).

0=3.93 5r

0

1

2

4

3

5

6

7

&At) F I G . 17. Phase portrait of vigorous pulsations at the hump crest in the plane (So, 60) ( Q = 3.93). The formation of a near-limit cycle is its conspicuous feature.

Forced Generation of Solitary-Like Waves

361

We observe that vigorous peaky-type disturbances map onto a domain in the form of a narrow closed strip filled by oscillation coils. This loop-shaped domain involves a minute “eye” in its lower part, not far from the origin. The cause for the eye to emerge is directly related to the existence of a small kink in & ( t ) mentioned above. The oscillation process as a whole bears strong similarities to a limit cycle, but departs from this because the frequencies associated with coils inside the narrow band in Figure 17 are slightly varying. On the other hand, the BDA equation belongs to dynamical systems of Hamiltonian form with infinite degrees of freedom (Case, 1980). We address the nontrivial question of whether the dynamical systems under discussion can exhibit limit cycles, defined in the strict sense, among attracting sets. Mathematically speaking, the Hilbert integral on the right-hand side implies a pivot to multidimensional problems on the inverse scattering transforms, which have been poorly understood so far. For the results available at present, see Fokas and Ablowitz (1983) and Ablowitz and Clarkson (1991). G. GRADUAL EVOLUTION OF DISTURBANCES The flow field undergoes a smooth evolution without abrupt changes when the similarity parameter Q grows step by step but remains less than Q = Q2, a value defining the next bifurcation. So the continuous development of the oscillation pattern emerges from the supercritical regime I1 brought about by the first biand terminates in furcation, extends over a fairly wide range QT < Q < Ql, the subcritical regime I11 at the threshold of the second bifurcation (BogdanovaRyzhova and Ryzhov, 1995a, 1996). With the disturbing source specified above, Q; is fixed by inequalities 51.48 < Q; < 51.49. The wave-system properties are exemplified in Figure 18 by the instantaneous displacement-thickness distributions as functions of x at different t for Q = 25. Several other examples were computed by Grimshaw (1987), Zhuk and Popov (1989), and Mitsudera and Grimshaw (199 1) for forcing agencies of varying physical nature, falling, broadly speaking, under the scheme considered. There is a point to be mentioned in connection with these results, namely, the comb of solitary-like waves upstream of a hump creates an inherent positive background that is clearly discernible, even at the initial stages in Figure 18. This displacement-thickness elevation, serving as a base for the train of solitary waves to advance against the oncoming stream, arises in the supercritical regime I1 immediately after the first bifurcation and persits throughout the range QT < Q < Q; in question. The background is by no means uniform, and the amplitudes of solitary-like waves are equal, as might be inferred from Zhuk and Popov (1989), where the generation of nonlinear distur-

Oleg S. Ryzhov and Elena I? Bogdanova-Ryzhova

362

Q=25.

L t=27.75

:I

v

y

t=20.25

,

b12.75

60

0

-50

0

50

100

X

FIG. 18. Instantaneous disturbance patterns typical of the range Q ; < Q < Q; ( Q = 25). Solitary-like waves evolve rapidly because of the short period T of their generation.

bances in the Blasius boundary layer was reported. As in Figure 16, solitary waves within the comb are in an orderly fashion by their amplitudes, with the leading peak being the greatest one. The key element to controling the gradual evolution of the disturbance excitation comes from alterations occurring in the form of vigorous pulsations immediately over a local roughness. The process is best characterized by four plots given in Figure 19 for different Q. From a comparison between Figure 14 and the plots in Figure 19, we observe that a peak surmounting each oscillation cycle with Q = 3.93 is progressively increasing as the similarity parameter takes on successively larger values. The peak becomes very much more clear cut toward the end of smooth evolution, when Q amounts to 51.48. Accordingly, a nearly constant period of pulsations shortens from T x 18 to T 3.2, resulting in the production of solitary-like waves that move faster both downstream and upstream, because of the higher amplitudes. However, of conceptual significance is the development of a barely perceptible kink on the leeward slope of each peak in Figure 14. The kink grows and gradually transforms into a spike within an oscillation cycle, be-

Forced Generation of Solitary-Like Waves

8

Q=5.

I

363

25

20

-

6

15

z 4 m

10

2

5

"0

50

100

150

"0

t

20

Q=40.

Q=51.48

,il.1

1.11, 0' 0

(c)

10

20 t

40 t

30

0'

40

0

10

20 t

30

A 40

(4

FIG.19. Displacement thickness Sg at the hump crest as a function of time f for different values of Q. A small kink on the leeward side of a main peak is seen to be gradually transformed into a larger spike between two neighboring peaks as Q increases in the range QT < Q iQ;.

ing situated closer to the main preceding peak if Q -= 5 I .48. With Q attaining this critical value, this spike proves to be placed just in the middle of two neighboring peaks. The role of the spike is crucial for the subsequent bifurcation, because it cannot be shifted toward the windward slope of the next main peak. Regardless of the amplitude, each oscillation cycle gives rise to a solitary wave, carrying the mass M,T, x Ms = 4n in the region upstream of the hump. Simultaneously, a gently sloping disturbance with Mg,Td = -4n is brought into the depression zone extending downstream, where a new solitary wave is building up at the tail end of the modulated oscillatory motion. A new feature smoothly evolving in the phase portrait (60, &) of the nearly periodic process is recognizable in Figure 20, where four different values of Q are used. As in Figure 17, the process maps onto a domain in the form of a narrow closed strip filled by oscillation coils. However, a minute eye in its lower part

Oleg S. Ryzhov and Elena ! l Bogdanova-Ryzhova

364

Q=51.48

400

200 200 100

G

0

' a 0

00 U

-100

-200

-200 0

10

20

30

0

10

800)

(a

20

30

&O(t)

(4

FIG.20. Phase portraits in the plane (So. &), featuring the smooth evolution of vigorous pulsations at the hump crest in the range Q ; < Q < Q;. A thin, tiny band is clearly seen to form inside the primary large strip.

grows with Q increasing in the range Q ; < Q < Q; and turns to a thin loop, which transforms step by step into another extremely thin band imbedded in the primary, much larger-sized, closed strip. The origin of this tiny loop, finally becoming a small, thin band, takes root in the development of a kink, on the leeward slope of each peak, into a spike, located somewhere between two neighboring peaks in the distribution of 60 = 60(t). As a consequence, a double-loop-shaped domain serves as an image of the vigorous pulsation process at the threshold of the second bifurcation, when the supercritical regime I1 is superseded by the subcritical regime 111. There is one more vivid presentation of vigorous pulsations, confined to the immediate vicinity of the roughness and responsible for discharging solitary-like waves outside. The idea is to trace the trajectories of the displacement-thickness maximum, Gmax(t) = maxS(t, x),

-b

< x < b,

(3.40)

Forced Generation of Solitary-Like Waves

365

changing its position with time within the hump region. Accordingly, plots in Figure 21 are drawn in a plane (xmax, 6max), where Xmax depends on t and must be evaluated by using (3.40). These portraits of peaky-type pulsations are more responsive to variations in the similarity parameter. With a value of Q taken sufficiently low, a track produced by the displacement-thickness maximum is not closed and therefore is especially characteristic of a single cycle of soliton emission. Exept for an initial transient period, 6,, emerges on the windward side of the hump and moves downstream. On the leeward side of the obstacle, it makes a sharp turn and then advances upstream, rapidly growing in magnitude before reaching the roughness crest. Upon passing the crest, 6,, loses most of its intensity and leaves the hump region as the peak of a solitary wave discharged upstream. When the pulsation process is repeated, every subsequent trajectory turns out to be very similar to, but never the same as, the preceding one. This behavior conforms well to the nearly limit-cycle-type portraits in the phase plane (60,60). Q=5.

I

Q=25.

25 1

10

"

-2

0

-2

2

9 0

2

Xmax

(4

I

Q=40.

I

10 n

Q=51.48

9,

F I G . 21. Maps on the plane (xmax.amax) of the vigorous pulsation process at the hump crest, illustrating the salient properties of the solitary wave radiation in the range QT Q < Q;.

366

Oleg S. Ryzhov and Elena V. Bogdanova-Ryzhova

With moderate Q , the trajectories of, , ,a =, , ,a (xmax) shrink toward the hump crest and become closed. A solitary wave leaves the leading edge of the obstacle at the end of each cycle, but the intensity of 6, does not decay to some small value. Even though the pulsation cycles are not exactly the same, the amplitudes of upstream emitted solitary waves prove to be almost equal. This tendency persists up to the threshold of the second bifurcation, when another maximum of 6 comes into play. However, it appears during the first cycle, and only then does it escape from the obstacle region downstream, never to be formed again. Peaky-type pulsations in boundary-layer flows can eventually terminate in a strong singularity emerging in the near-wall tier at some finite instant (Smith, 1988). This singularity is associated in Peridier er al. (1991a,b) with the viscous sublayer eruption that is well known from visual observations in wind tunnels (Doligalski er al., 1994). Therefore, evolution of the oscillation cycle at the hump crest toward sharpening variations of S is highly conducive to the premature breakdown of laminar motion and accelerates the onset of transition in the presense of perturbing roughnesses characterized by large values of Q (we emphasize that the roughness height does not play a decisive role).

H. THESECOND BIFURCATION This bifurcation is the most dramatic feature inherent in the forced BDA model and is related to transition in the Blasius boundary layer (Bogdanova-Ryzhova and Ryzhov, 1995a, 1996). Similar to sharp alterations in the emission process produced by the first bifurcation, a new abrupt change in the overall disturbance pattern stems from an attempt to increase a value of the controlling parameter beyond the range considered in the foregoing section. The most straightforward way to reveal the second bifurcation is to compute again the mass M-b = M-b ( t ) transported by the wave system upstream of the obstacle. Figure 22 attests to a sudden jump in the mass-production rate if the similarity parameter Q = 5 1.48, characteristic of the subcritical regime 111, increases by only 0.01 and becomes Q = 5 1.49. This change can be attributed to the supercritical regime IV coming in place of the subcritical regime I11 at the incipient transition time Ti, zz 9. The value T,, proves to be larger than a span of three cycles of the subcritical regime 111, which sets in after triggering the perturbing source and persists until bifurcation. Thus the second bifurcation happens when three solitary waves are already radiated upstream and the fourth one is forming at the leading edge of the obstacle. Evidently, a solution describing the supercritical regime IV must be endowed with key properties very different from those intrinsic to the supercritical

Forced Generation of Solitary-Like Waves

367

t FIG.22. The mass Ik-b transported by the wave system upstream of the hump as a function of time t in the subcritical regime I11 ( Q = 5 1.48, thick line) and the supercritical regime IV ( Q = 5 1.49, thin line).

regime I1 and subcritical regime 111. Let us examine a new mechanism at the heart of the disturbance generation by steady humps with Q > Q;. We may visualize a more complicated motion in physical space from Figure 23, where the similarity parameter Q = 65. However, the wave pattern as a whole seems, at a glance, closely parallel to those arising in the supercritical regime I1 and subcritical regime 111, except for the much higher swing of oscillations (cf. Figures 16 and 18). As a matter of fact, a solitary wavetrain is seen to propagate upstream of the hump against an intrinsic positive background close to the obstacle leading edge, whereas the region on the leeward side involves a modulated oscillatory tongue, with a number of solitary-like waves arising at its tail end, as well as a depression zone spreading between the last of these waves and the hump. However, more careful inspection of Figure 23 discloses that solitarylike waves propagating downstream as well as upstream are nonuniformly spaced. Consequently, the peaks of disturbances within both wave systems appear in arrays that are not as well organized as the corresponding systems computed with smaller values of Q. The double-peaky large-amplitude burst over the hump at

Oleg S, Ryzhov and Elena V: Bogdanova-Ryzhova

368

G65.

t=14

X

t=10

O d

io' 0

20

40

60

X

FIG.23. Instantaneous disturbance patterns typical of the supercritical regime IV (Q = 65). Upon the second bifurcation, fast solitary-like waves are radiated and arranged within the downstream and upstream combs in arrays that are not well-organized.

t = 10 and t = 18 points to the same conclusion: it would not be possible at all if

Ql: < Q

Q;.

The occurrence of the double-peaky structure in the displacement-thickness distribution heralds a radical change in the type of vigorous oscillations within the hump location and in the overall disturbance-emission process, which is called into being by the second bifurcation. This statement is strongly substantiated by observing the behavior of & ( t ) with the same supercritical value Q = 65 as t increases. A remarkable alternation of main peaks and spikes peculiar to the subcritical regime I11 at the threshold of bifurcation, fixed by Q = 51.48, turns to a distribution in Figure 24 computed with Q = 65, where peaks and spikes accompanied by smaller kinks come in an erratic manner rather than apparently being governed by a rule. Sometimes spikes and kinks emerge one after another in the middle of two neighboring peaks, and what is more, each of them can be located on the windward side of a peak. Otherwise, two main peaks do not involve either a spike or a kink in between. The distinctions between spikes and kinks are

Forced Generation of Solitary-Like Waves

369

0=65. 45 40 -

35-

-

30 -

c

ao 2520

-

15

-

10 50

I

I

I

hardly discernible in many cases. The reference time of this aperiodic process reduces roughly to T % 1.5, compared with a nearly constant period T 3.2 of oscillations in the subcritical regime I11 with Q = 5 1.48. Some further growth in the amplitude of 6 0 ( t ) is also observable but does not manifest itself in dramatic form. Accordingly, the phase portrait of the process in the plane (60, &) is radically modified from narrow closed strips in Figures 17 and 20 associated with the disturbance generation in the range QT < Q < Q; to a wide domain in Figure 25 drawn for Q = 65. Large-sized coils produced by peaks fall within a broad band, where they intersect with each other; smaller loops due to spikes and kinks are superimposed near the origin. As a result, a double-loop-shaped region typical of plots in Figure 20 transforms into a unique domain filled by coils of different sizes, which provides a map of the supercritical regime IV. So the nearly periodic process over the hump featuring the subcritical regime I11 collapses into

Oleg S. Ryzhov and Elena I? Bogdanova-Ryzhova

370

Q=@.

I 0

I

5

10

15

25

20 &J

30

35

1

I

40

45

(1)

F I G . 25. Phase portrait of vigorous pulsations at the hump crest in the plane (So, 8 0 ) typical of the supercritical regime IV ( Q = 65). A broad band features radical alterations brought about by the second bifurcation in the limit-cycle-type process.

irregular pulsations with erratic sequences of amplitudes and characteristic times when passing through a bifurcation value Q = Q;. As for the nature of the sequences intrinsic to the supercritical regime IV, no decisive conclusion may be inferred on the basis of the results obtained thus far. However, a sharp broadening of the phase-plane image of an oscillation process from a narrow strip to a wide band usually points to the rise of chaotic elements in the dynamical system under discussion. The change of the phase portrait of vigorous oscillations over the hump is reflected in profound alterations of the wave motion in a plane (xmax, Amax). Along with the nearly cyclic behavior of Amax embodied in closed trajectories of Figure 21, initiation of one more local maximum on the leeward side of the hump is clearly seen in Figure 26. Instead of leaving the obstacle downstream, in the supercritical regime IV it moves upstream and disappears near the leading edge, shortly after radiating a solitary-like wave; then this second maximum reemerges

Forced Generation of Solitary-Like Waves

37 1

1

-2

-1

0

1

2

3

xmax F I G . 26. Map on the plane (xmax, ),,S of vigorous pulsations at the hump crest, illustrating initiation of chaotic elements in the boundary-layer flow (Q = 65).

on the leeward side of the roughness. The process as a whole does not obey an apparent rule, and the alternation of cyclically moving maxima and additional local peaks in the displacement-thickness distribution is likely to occur in an erratic manner. Thus two distinctive wave motions coexist close to the hump, giving rise to solitons that differ substantially in their amplitudes and phase velocities. It is just the birth of two alternating disparate maxima that provides the clues to understanding irregular wave patterns both downstream and upstream of the hump in Figure 23.

I. DISTURBANCE GENERATION BY CAVITIES Solitary-like wave emission peculiar to cavities, characterized by Q < 0, is in most respects different from that considered above for humps with Q > 0, even though there are features in common to both cases (Bogdanova-Ryzhova and Ryzhov, 1996). First of all, the amplitude of waves in the two systems ra-

Oleg S. Ryzhov and Elena K Bogdanova-Ryzhova

372

diated in opposite directions, downstream and upstream, continuously grows as Q decreases from zero, without being subject to radical changes through bifurcations at some critical values of the similarity parameter. The generation process goes smoothly and the disturbance amplitudes never become significantly larger compared to the sizes of pulsations developing inside a cavity. This property explains the absence of the first bifurcation. The mass-production rates in Figure 27 are convincing testimony to the general statements advanced without proof. Next, from the steplike run of all the curves associated with upstream soliton radiation, we may conclude that the incipient transition time Ti, as well as the period T of an individual disturbance birth shorten in relation to the corresponding quantities typical of humps with the same absolute value of Q . Further evidence can be picked up by comparing two plots in Figure 28 that exhibit the instantaneous displacement-thickness distributions for a hump with Q = 25 and a dent fixed by Q = -25. We see a much greater number of solitary waves emitted by the dent, although the specific comb-like arrangement of their peaks downstream and upstream of the roughness is inherent in both disturbance

0

10

15

20

t

25

30

35

27. Mass M - b transported by the wave system upstream of the dent in a broad range of 0. No bifurcation occurs in the gradual evolution of the disturbance+excitation process.

FIG.

Q

5

i

373

Forced Generation of Solitaly-Like Waves 0=25

-100

-50

0

50

100

50

100

X

(a)

Q=-25 10

-

X

c

z

5

o -5 I

-100

-50

0 X

(b) F I G . 28. Comparison of the instantaneous disturbance patterns generated by a hump and a dent of equal mass (1 Ql = 25) at the same time ( t = 30). A strong negative peak centered around x = 0 separates the depression area from the front part of the dent.

patterns under comparison. Regardless of the sign of Q , any one of these waves is, in effect, a nonlinear eigenmode of the homogeneous BDA model defined by its intrinsic amplitude and phase velocity, but carrying the same mass 4n. A distinctive feature of disturbances created by the dent derives from a strong negative quasi-steady peak in front of the short depression area. The boundary layer becomes significantly thinner within the peak zone at the bottom of the dent. Unlike the process associated with humps, the disturbance radiation by dents is sustained via strong pulsations taking place at the leading edge x = -b of the roughness rather than occurring at its crest x = 0. The strong negative quasisteady peak in the displacement-thickness distribution serves to prevent the tail

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

374

end of the cavity from being involved into pulsation development. Therefore a function & b ( t ) = 8 ( t , -b), instead of & ( t ) = 6 ( t , O), proves to be more relevant as a dent characteristic. The behavior of this function, shown in Figure 29, reveals no kink forming on the leeward slope of any peak. So there is no reason for an event analogous to the second bifurcation to happen. From what has been said, it might be assumed that a typical phase portrait of the pulsation process in a plane (S-b, &, = dJ-b/dt) should be of the limit-cycle type. The phase planes shown in Figure 30 confirm this conclusion. What is more, all of the limit-cycle-type portraits computed for an extremely broad interval of Q < 0 consist of a single thin band and do not involve lesser loops, as was the case with regard to humps within the range QT < Q c Q;. The simplification of the phase portraits in Figure 30 stems from the absence of low-amplitude spikes alternating with neighboring main peaks in the distribution of 8-b = 8 - b ( t ) .

Q=-15.

&-3.

I

0

50

100

150

-2

200

'

20

0

t

40

t

Q=-25.

Q=-45. 15

10 10 c

v

0

5

5

Ld

0

0 0

10

20

t

30

40

-5

'

0

5

10

15

20

t

(a 29. Displacement thickness 6-h at the leading edge of the dent as a function of time the distributions, computed for a broad range of Q i0, consist of peaks only. FIG.

2.

Ail of

375

Forced Generation of Solitary-Like Waves Ck-3.

Q=-15. 20

1 0.5

10

0

0

-0.5

-10

5 2 'D

-1

-20

0

1 s-b(t)

2

-

3

2

0

2

4

6

8

s-b(t)

(a)

(b)

Q=-25.

0-45.

50

100 50

F; 2

0

0

'D

-50

-100

-50 0

(c)

5 6-b(t)

10

-5

0

5

10

15

s-b(t)

(d)

F I G . 30. Phase portraits in the plane (6-b. i - b ) featuring the smooth evolution of intense pulsations at the leading edge of the dent in a broad range of Q < 0. A single limit-cycle-type loop is intrinsic to the disturbance-excitation process.

As Figure 31 demonstrates, the pulsation crest Gmax(t) defined in (3.40) starts developing, being mild in size, upstream of the cavity bottom (x = 0) and sweeps a short distance downstream. Then it makes a sharp turn toward the leading edge, never passing through the central point of the dent. The amplitude of grows reaches the top height, not far from the leading as it moves upstream. As,,,a, edge, its intensity drops off slightly, and it leaves the cavity in the form of the peak of a solitary-like wave discharged against the oncoming stream. Then the cycle is repeated, but not in exactly the same way, because of deviations in successive traces. Solitary-like waves are radiated by a dent when amax is close to its top height, contrary to a hump, in which case the emission of a solitary wave occurs when , , ,a is about the minimum. For this reason trajectories in Figure 31 turn out to be disconnected (cf. Figure 21, associated with a hump).

376

Oleg S. Ryzhov and Elena V Bogdunova-Ryzhova Q=-3.

-3

Q=-15.

-2

-1

-2'

0

'

-3

-2

-1

0

-1

0

Xmax

Xrnax

Q=-25.

Q=-45. 15

J1~~'~~~111,1~11~~~1 ,

lo 5

~

0

0 I

-3

-2

-1

-5

0

-3

%ax

-2 %ax

(4

(4 FIG. 3 1. Maps on the plane (xmax, ),,,S

of intense pulsations at the leading edge of the dent, illustrating the salient properties of the solitary-wave radiation in a broad range of Q < 0. These pulsations are confined to the front of the dent, being isolated from its rear by a strong negative peak in the displacement-thickness distribution.

N.The KdV System A. CROSSFLOW INSTABILITY

A completely different scenario in which truly nonlinear disturbances are built up takes place in a 3D boundary layer in connection with crossflow instability (Ryzhov and Terent'ev, 1995, 1996). In this case the crossflow acts like a spanwise near-wall jet and excites initially linear, unstable eigenmodes that may be isolated from streamwise oscillations. The basic mechanism at the heart of the crossflow jetlike behavior stems from the pressure gradient, which strikes a balance with centrifugal forces in the main body of the boundary layer, because of the large curvature of stream surfaces. As for the integral term in the interaction

Forced Generation of Solitary-Like Waves

377

law caused by stream-surface slopes, it becomes negligibly small and drops out of (2.4) if a reference length in the spanwise direction falls to 0( ~ ~ ~ 1It’ is ) . remarkable that exactly the same interaction law and resulting scaling are pertinent to the viscous/inviscid interaction of a thin jet with a flat plate (Smith and Duck, 1977; Ryzhov, 1982).The near-wall jet bears a close resemblance to the crossflow of a 3D boundary layer in that their velocities decay to zero when approaching the upper reaches (however, the oncoming stream gives rise to the streamwise velocity of the boundary layer in question). Another example of an interacting boundary layer derives from a viscous flow past a flat plate mounted vertically in the gravity field and heated (Messiter and LiiiBn, 1976). Of these three types of disparate environmentalconditions, the 3D boundary layer involving crossflow as an intrinsic element is, certainly, of prime importance. Upon entering the truly nonlinear stage, disturbances in each of the fluid motions mentioned obey the celebrated KdV equation which was indicated by Korteweg and de Vries as far back as 1895 in the context of shallow water waves. The disturbance generation process provoked by an external forcing source consists predominantly of the excitation of nonlinear eigenmodes in the form of periodic cnoidal waves and KdV solitons. Let us proceed from a preliminary simplified version (2.9) of the Prandtl equations. Upon supplementing the limiting condition at the upper edge ( y + 00) of the near-wall sublayer (labeled I11 in Figure 2) by a constraint for the vertical component of velocity, we can recast (2.1 1) as W’

-yf

+ A’(t’,x’),

(4.la) (4.1b)

Again, if d,w’, p’, and A’ satisfy both (2.9) and (4.la), then (4.lb) is met automatically. The interaction law and the no-slip conditions at a solid surface y’ = yL(t’, z’) are given by (2.10) and (2.12), respectively. A further procedure in exploring a truly nonlinear stage of crossflow disturbances parallels that set forth above in connection with nonlinear waves propagating in the streamwise direction. The triple deck shown in Figure 2 transforms into a four-deck structure, since a new intermediate (adjustment) sublayer emerges to separate the main tier I1 from the viscous sublayer I11 within the narrow highamplitude-spike zone. As a result, an effectively 2D oscillation pattern takes on the form sketched in Figure 6, with z substituted for x (actually, the upper sublayer is missing from the disturbance field). The size of the spike is scaled in terms of a ratio A/&, where the second small parameter A >> E . Inside the adjustment

378

Oleg S. Ryzhov and Elena V. Bogdanova-Ryzhova

sublayer (2.1) and (2.2) fail; an appropriate rescaling of independent variables becomes (4.2a, b, c) The corresponding rescaling of desired functions leading to 0 (A4) pressure variations reads

(4.3a, b, c, d) It should be emphasized that the affine transformation (4.2), (4.3) differs from the one given by (3.2), (3.3) for truly nonlinear waves propagating in the streamwise direction. Insofar as the intermediate sublayer is much shorter and thicker than the initial near-wall deck, the term with viscous tangential stresses in (2.9b) becomes negligible and truncated equations (Ryzhov and Terent’ev, 1995, 1996)

-av + - aazw = o , ay aw

aw

-+v-+wat ay

aw aZ

(4.4a)

aP =--

az ’

(4.4b)

where p = p ( t , z ) on the strength of a p / a y = 0, control the inviscidhnviscid interaction process. Thus the adjustment sublayer in both extremes featuring 3D boundary-layer flows is akin to a nonlinear critical layer in the proximity of a solid wall. The excess pressure p on the right-hand side of (4.4b) is related to the instantaneous displacement thickness 6 = -A through (2.10), with z and A standing in place of z’ and A’, respectively. As (4.2) shows, in the limit A + 1, the adjustment sublayer becomes as thick as the initial boundary layer, whereas its dimension in the spanwise direction is comparable with the thickness. According to (4.3), the normal-to-wall and spanwise components of the velocity vector as well as the pressure tend to grow to 0 (1) quantities in this limit. Thus a nonlinear stage governed by the full system of the Euler equations, with the normal pressure gradient included, comes into operation. At the outer reaches ( y + co) of the adjustment sublayer, the limiting conditions (4.1) still hold true (with t , y , z and v , w ,p , A substituted for t’, y’, z’ and v ’ , w ’ , p’, A’, respectively) and define an explicit solution to the system of truncated equations (4.4), irrespective of the dependence of p on A . To meet the

Forced Generation of Solitary-Like Waves

379

boundary conditions at the bottom of the adjustment domain, we must introduce a thin near-wall viscous sublayer with the normal coordinate

within the spike zone. This sublayer is a continuation of the corresponding sublayer involved in the triple deck (Figure 6, with the upper sublayer missing). The oscillation parameters are given by

A 4

PI=

(1)P e d ,

A

(4.6a, b, c, d)

They satisfy the classical 2D boundary-layer equations in t , y e d , z , where the excess pressure p e d = p ( t , z ) is expressed in terms of the predetermined displacement thickness - A t d = -A(t, z ) by the second derivative (2.10). The no-slip conditions must be imposed at the wall. With the pressure distribution known in advance, the near-wall viscous sublayer plays a passive role. However, its solution is used in a matching procedure to derive a missing boundary condition,

for the adjustment sublayer containing predominantly inviscid motion. At a certain stage a strong singularity can develop within the near-wall sublayer and put an end to the asymptotic scheme adopted. As mentioned above, the disturbance pattern in the lower viscous deck is beyond the scope of this review. Substitution of (4.1) into (4.7) yields the forced KdV evolution system (4.8a) where A,,, = yw

+ A and (4%)

The corresponding homogeneous equation

was first derived by Korteweg and de Vries as far back as 1895 in connection with shallow water waves, and in the context of 3D boundary-layer stability (of

380

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

main concern here), this equation appeared in Ryzhov and Terent’ev (1995,1996). General concepts as applied to a wide variety of viscous shear flows are exposed in Zhuk and Ryzhov (1982) and Smith and Burggraf (1985). No attempt has been made so far to establish a link between this recent discovery and experimental data that are associated with truly nonlinear phenomena at the threshold to transition in a 3D boundary layer on a swept wing, rotating disk, or cone at incidence. All that is available at present relates to completely different environments. Thus, solitary-like disturbances typical of theoretical findings are definitely present in observations by Baines (1984) on two-layer flow over topography and recorded by Farmer and Denton (1985) in a tidal stream over a sill. Careful measurements of Lee et al. (1989) of water-wave parameters show a broad agreement with physical models including, in particular, the forced KdV equation. Drawing on a mathematical analogy that applies under various environmental circumstances, we suggest that both the homogeneous and inhomogeneous KdV systems can be employed as the basis for the theoretical description of the excitation and the subsequent development of nonlinear crossflow eigenmodes in the form of periodic oscillations and solitons. Three qualitative conclusions parallel those stated for the BDA model, they follow from the asymptotic analysis without solving the governing equations. First, different normalizations of the normal-to-wall coordinate, fixed by (2. lc), (4.2b), and (4.5), show that the subdivision of the near-wall viscous sublayer, which controls the size of the crossflow eigenmodes, does not occur if A / & = 1. Therefore this sublayer is the site of the spiky signal birth at the triple-deck stage. In line with (2.2), (4.3) and (4.6), the spanwise and normal velocities as well as the self-induced pressure are of the same order of magnitude throughout the lower deck, remaining unsplit in the case A / E = I. Second, the adjustment sublayer resulting from the later subdivision at the truly nonlinear stage is thicker, in view of (4.2b), than the initial near-wall zone of the crossflow disturbance. The adjustment-sublayer thickening implies, in point of fact, that the spike elevates from the wall toward the upper edge of the 3D boundary layer as A / & grows. The other part of the subdivided disturbance continues to propagate close to the wall. Third, a rise in the crossflow-disturbance amplitude with A / & increasing is accompanied by acceleration of the spike relative to the waves that move in the spanwise direction within the entire near-wall viscous sublayer. Together, these conclusions could form the groundwork for the first direct check in wind-tunnel tests upon the validity of the theory as applied to 3D boundary layers.

Forced Generation of Solitary-Like Waves

381

B. DESCRIPTION OF FREEOSCILLATIONS I N TERMS OF ELLIPTIC FUNCTIONS There is an extensive literature on the homogeneous KdV equation covering conservation laws, direct and inverse scattering, Lax pairs, Hirota function, pole expansions in a complex plane, Backlund transformations, and other general topics. All of these elegant and powerful mathematical techniques are far beyond the scope of the present paper; a recent book by Ablowitz and Clarkson (1991) and references therein are recommended for a comprehensive survey of their basic properties. However, the disturbance emission process controlled by an external forcing is hardly amenable to analysis by any of the aforementioned methods. Moreover, in the context of boundary-layer oscillations, one-periodic and soliton solutions seem to be of primary significance in representing nonlinear crossflow eigenmodes excited by steady obstacles. For this reason we confine ourselves only to a brief discussion of the simplest results related to cnoidal waves and KdV solitons. Let us consider a traveling-wave-type solution,

A = F(6),

6 = k z - wt,

(4.10)

to (4.9), with the first derivative d F / d < determined by a cubic polynomial,

3k2 (”,)?

= P ( F ) e F3 -3cF2+clF+c2.

Here c = w / k is the phase velocity, and c1 and c2 stand for two arbitrary constants of integration. Suppose their values to be chosen in such a way that

P = ( F - F l ) ( F - F2)(F - F3), where F1 > F2 > F3 are three distinct real zeroes of P . Then we have an expression

to implicitly define a desired solution (4.10) through an elliptic integral of the first kind. Making use of the standard notations,

in Abramowitz and Stegun (1964) allows us to reduce (4.1 1) to the form 0=

h --(c &k

- <3) =

(1 - rn sin2@)-1/2d@.

(4.13)

382

Oleg S. Ryzhov and Elenu K Bogdunovu-Ryzhova

This can be inverted, on the strength of (4.12a, b), to result in an explicit solution,

F = F2 - (F2 - F3)cn2 [

gKG<

- <3)

I m],

(4.14)

written in terms of the Jacobian elliptic function c n ( 0 1 m ) = cosq5, where the value of the parameter m comes from (4.12~). The zeroes F2 and F3 have a very simple physical meaning: the former fixes the background-perturbation level, and the difference F2 - F3 defines the amplitude of a cnoidal wave as reckoned from that level. Evidently, the phase is prescribed by a value of <3. The period of cn(O I rn) is expressed through the complete elliptic integral of the first kind, Ti2

(1 - m sin24)-'/2d@,

K ( m )=

obtainable from (4.13) by setting cp = n / 2 (Abramowitz and Stegun, 1964). Hence the wavelength becomes (4.15) and the wavenumber k in the original frame of reference ( t , z ) can be represented as

k = - - ( F I - F3). 2l F 3- Since the phase speed c = 1/3( Fl

(4.16)

+ F2 + F3), the oscillation frequency is given

by

k

+ + F3).

= ~ ( F I F2

(4.17)

In the limit of infinitesimal waves we have F3 -+ F2, and therefore rn + 0, cn (0 I m ) + cos 0. The general expression (4.14) takes on the form 1 A = F2 - -(F2

2

-

F3) C O S [ ~ ( ( ,$3)].

(4.18)

It can be seen that in view of (4.17), the frequency tends to w = F2k

+ -31 k(F1 - Fz),

and with allowance made for (4.16), this provides a dispersion relation, w = F2k +4k3,

(4.19)

Forced Generation of Solitary-Like Waves

383

for infinitesimal waves also derivable by substituting (4.18)into the homogeneous KdV equation. With initial background perturbations F2 = 0, (4.19) matches with the corresponding dependence in Ryzhov (1982) and Ryzhov and Terent’ev (1995, 1996) for TS waves at the linear triple-deck stage (where, in point of fact, the upper sublayer is absent from the disturbance pattern). Since K ( 0 ) = n / 2 (Abramowitz and Stegun, 1964), it follows from (4.15)that L = n,in agreement with (4.18). In the other limit of strong disturbances, F1 x F2 > F3 and rn -+ 1. Hence we can deduce that c n 0 = sech 0. As a consequence, the general expression (4.14) reduces to

A = F2

-

(F2 - F3) sech2

[iJ:-

- (F2 - F3)x - wt

]

(4.20)

where the frequency

= kF2 - -(F2 k - F3) = kF2 - 4k 3 , 3

(4.21)

since F2 - F3 = 12k2, by virtue of (4.16). This is the KdV soliton propagating against uniform background perturbations F = F2. It should be emphasized that according to (4.21),the phase velocity c = w / k becomes negative if the initial background F2 = 0. In this case the KdV solitons advance in the upstream direction, and their amplitude, wavenumber, and frequency are given in terms of the difference F2 - F3. The KdV solitons are capable of sweeping downstream solely against the background with sufficiently large 6 = -F2 < 0. As stated above, the same property is inherent in the BDA solitons. On the contrary, we see from the dispersion relation (4.19)that infinitesimal waves move downstream independently of their amplitude when F2 = 0. Likewise, infinitesimal disturbances governed by the BDA model also propagate in the downstream direction. Cnoidal waves and their low-amplitude as well as high-amplitude extremes are crucial elements of the generation process provoked by an external source. The mass of the KdV soliton advancing upstream against zero background perturbations depends on its size in the following manner:

J:

M,y = 24k = 12 -(F1 - F3).

(4.22)

The same mass is carried by the soliton (4.20) sweeping downstream against a background 6 = -F2 < 0.

384

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova c . SOME GENERAL PROPERTIES OF FORCEDOSCILLATIONS

Guided by statements set forth in Section III.C, we begin with extending the one-periodic solution (4.14) to the inhomogeneous KdV system. TJ this end, let the forcing term on the right-hand side of (4.8a) be aP/az, where a periodic function P = -alcn

2

c = kz - wt

(c I m ) - a2cn4 (c I m ) ,

(4.23)

depends on five arbitrary constants, w , k, m , a l , and a2. There then exists a periodic solution, A, = bl - b2cn2(c I m),

(4.24)

with coefficients bl and b2 given by (cf. (3.22a, b))

b2 = 6mk2[l

1)k3] -

(4.25a)

+ (1 + & ) l I 2 ] .

(4.25b)

If a1 = a2 = 0 in (4.23), i.e., the disturbing agency becomes zero, we find from (4.25) that bl

1 k

= -[w

+ 4(2m - 1)k3],

b2 = 12mk2 .

(4.26)

In view of (4.16) and (4.17), these are precisely the same values of bl and b2 as those entering the one-periodic solution to the homogeneous KdV equation written above in the form of (4.14). In the context of 3D boundary layers, an important case stems from a consideration of stationary roughnesses then w = 0 in (4.23). Background perturbations provoked by a stationary forcing of the form (4.23) are equal to bl =4(2m - l)k2 - a1 -, b2

(4.27)

where b2 is expressed in terms of k,m , and a2 by means of (4.25b). Thus we still have four arbitrary constants to describe steady crossflow disturbances. A solitary-like solution exponentially decaying at infinity immediately ensues from (4.23)-(4.25) by passing to a limit, m + 1. The final result reads P = -a1 sech2( - a2 sech4

e,

(4.28)

Forced Generation of Solitary-Like Waves

385

and

A, = c + 4 k 2 -

a1

6k2[1

+ (I +

[ + + 3)

- 6k2 1 $)li2]

(1

li2]

sech2 6.

(4.29) It falls within a class of functions that was indicated by Patoine and Warn (1982) and Wu (1987). With the phase velocity c = w/k = 0, (4.28) and (4.29) provide a steady solution depending only on z.A relationship between its constants obeys (4.27). No steady solution is allowed within the homogeneous KdV model, provided that background perturbations are zero. As is readily seen, this constraint leads to k = A, = 0 if a1 = a2 = 0. In the general case, let the forcing f ( t ,z) be expressed through a3y,/az3, where y, = y, ( r , z) stands for a local roughness stretching in the direction of the external oncoming stream aligned with the x-axis. On the assumption that both the forcing and the corresponding solution decay sufficiently fast as z -+ TCO, the mass conservation law,

holds for a function, A, = y, - 6 , determined by (4.8). Hence we have

L

00

[, 00

s ( t , z)dz =

y W ( t , z),

provided that 6(0, z) = 0. There are important relationships between the general problem on conservation laws intrinsic to the homogeneous KdV equation and other fundamental properties considered, for example, in Drazin and Johnson (1989) and Ablowitz and Clarkson (1991). The mass of a soliton propagating against zero background perturbations, fixed by means of

[ +( +7 ; ;

a1 = 6k2(c+4k2) 1

+ +

1

) ] I 2 ],

is M , = 12k[l (1 a ~ / 9 k ~ ) ' /where ~ ] , a2 can take on arbitrary values. In the absence of forcing ( a , = a2 = 0 , c = -4k2 < 0), this becomes M , = 24k, in keeping with (4.22). A similarity law plays a decisive role in mathematical modeling of the crossflow-disturbance generation in 3D boundary layers (Bogdanova-Ryzhova and Ryzhov, 1995b). This law depends on a group of affine transformations, t --f P3t, z +. Pz, A +. PP2A, admitted by the homogeneous KdV equation. As in the previous analysis of the forced BDA system, the external source is specified through y, = ag(r/ro)h(z/b),with a time-dependent multiplier g = 0

Oleg S. Ryzhov and Elena K Bogdanova-Ryzhova

386

<

if t 0. Three arbitrary constants, to, b, and a, define the characteristic time, the reference length, and the amplitude of the forcing. We assume g to be a monotonically increasing function on the interval 0 < t < to, becoming g = 1 for t 3 to. Let us apply the affine transformation with j3 = b to both (4.8a) and (4.8b). The resulting model is cast in the form

(4.3 1) The two similarity parameters S = Qb = ob2 and To = to/b3 appear here in place of the original three parameters, to, b, and a; they specify the similarity law of the disturbance-excitation process for all t and z . However, at sufficiently large times (t >> TO),the motion must become effectively independent of the second parameter To, because g = 1, by virtue of our assumption. Thus the only similarity parameter S turns out to control distinctive features of the oscillation pattern at later stages after switching on the forcing source. This parameter has a simple physical meaning, being proportional to the moment of the area (mass) of a disturbing obstacle positioned on an otherwise flat plate. Because of the specific form of a function f in (4.8), the similarity law is stated in terms intrinsic to the crossflow-disturbance generation. We see that in the same 3D boundary layer, nonlinear eigenmodes radiated in the streamwise and spanwise directions depend on the roughness mass and the moment of the mass, respectively. Insofar as disturbing agencies can be disparate in nature, a variety of similarity laws feature the disturbance emission in different environments (shallow water, atmospheric and oceanic phenomena), with the forced KdV equation at the bottom. In what follows we leave aside an in-depth discussion of similarities arising from outer sources indicated by Akylas (1984), Cole (1983, Grimshaw and Smyth (1986), and Wu (1987) for such environmental conditions.

D. STABILITY ANALYSIS The shape of a stationary surface that corresponds to (4.28), (4.29) with a2 = 0 is given by at

yW = -[lnch(kx) k2

+ kx + In 21.

(4.32)

This approaches a flat plate aligned with the oncoming crossflow, as x -+ -00, and tends to another flat plate y w = (2al /k)x at infinity x -+ 00. In consequence, we may treat the resulting motion as a special type of ramp flow. It is worthy of note that surface geometry defined by (4.32) seems to be artificial as applied to

Forced Generation of Solitary-Like Waves

387

spanwise disturbances in a 3D boundary layer. On the contrary, the same geometry is quite natural for a problem on a thin jet developing in the vicinity of a flat plate and impinging against a ramp (Smith and Duck, 1977). One more natural formulation stems from considering a viscous flow past a flat plate mounted vertically in the gravity field and heated (Messiter and LiiiBn, 1976). On the strength of a requirement 6 = -A + 0, as x + -00, a constant entering the expression for A, becomes zero, therefore (4.29) yields al = 48k4. Let us slightly perturb the base solution and write down

A, = A,,y(x)

+ ~ ( tx),,

A,,

= -12k2 sech2(kx),

(4.33)

assuming q in (4.33) to be small compared to the leading term. Then the correction function comes from a linear equation,

1

?! - ?[fi + 12sech2(x)~ = 0, at

ax an2

upon taking advantage of an affine transformation t -+ t/k3, x + x/k. The independent variables can be separated by putting

D = e"'{(x), where { satisfies the following ordinary differential equation:

+ 12sech2(x){

1

= w{,

(4.34)

subject to regular conditions at infinity, i.e.,

3+ o

dx'l

exponentially fast for n = 0 , 1 , 2 , as 1x1-+ oo.

(4.35)

In (4.34), (4.35) we have exactly the same eigenvalue problem in w as one studied by Camassa and Wu (1991a) in connection with the wave systems generated and sustained at near-resonance in a shallow channel of uniform water depth. The difficulty of the problem derives from the fact that the governing operator is of the third order and non-self-adjoint. The stability of the base solution, and the corresponding ramp-type flow, depend on the sign of the real part of w . We note that if (4.34), (4.35) have an eigenvalue w and an eigenfunction {(x), they must admit of the other three eigenvalues, -w and f w * , along with their eigenfunctions {(-x) and {*(&x), respectively. As usual, the asterisk implies the complex conjugation. Therefore, the ramp flow under examination is absolutely unstable whenever an eigenvalue with a nonvanishing real part exists. Thus we are led to address, first of all, the question

388

Oleg S. Ryzhov and Elena V. Bogdanova-Ryzhova

of whether w = 0 can represent a simplest real eigenvalue. In this case (4.34) reduces to the second-order equation d2<

-

dx2

+ 12 sech2(x){ = 0,

<

which is well known in quantum mechanics and has the only solution = 0, subject to homogeneous boundary conditions (4.35) at infinity (see, for example, Landau and Lifshitz, 1958). So w = 0 is not an eigenvalue; however, the complex eigenvalue w = w, iwi does exist, and the computation by Camassa and Wu (1991a) provides an estimate w, = 6.84 x lop4 for its real part. As a result, the base ramp-type flow turns out to be slightly unstable within the framework of inviscidhnviscid interaction theory exploited here. Turning back to the original (nontransformed) independent variables, we observe that the linear solution amplifies like exp(6.84 x 1OP4k3t); hence the amplitude growth rate is highly sensitive to an increase in k . On the other hand, the ramp slope dy,/dx also varies very rapidly with k and becomes as large as 96k4 at infinity. One more distinctive feature of the boundary-layer flow under consideration is in its strong dependence on initial data (Camassa and Wu, 1991a). Given A, (0, x) = 0, the nearly periodic bifurcating regime immediately starts developing in time. In contrast, with the steady-state initial condition A, (0,x) = A,,y (x), the nonlinear solution shows no radiation of solitary waves, as well as disturbances of other types, up to some large value t = t S , when the computation stops. If A, (0, x) 0.4A,, (x), approximately the same incipient transition time Tir x ts determines the formation of the first solitary-like wave advancing upstream. It is remarkable that the period of the runaway soliton emission almost doubles from T x To in the case A,(O, x) = A,,y(x) to T x 1.84To for A,(O, x) = 0.4A,,s(x). Thus the nearly periodic generation process due to a forcing ramp drastically changes in response to nonuniform background perturbations introduced at t = 0 in the vicinity of the point x = 0. It is pertinent to note that the wavenumber k = ko = const throughout the computation by Camassa and Wu (1991a), but a value S = 12 of the similarity parameter proves to be independent of k for an obstacle fixed by (4.32). Absolute instability suffered by the initial state of rest is the most important property to be inferred for our purposes from the above discussion. It is just this instability that leads to the nearly periodic regime bifurcating from a steady shear flow. The same phenomenon has been carefully analyzed in Section I11 as applied to the disturbance-generation process evolving in the Blasius boundary layer within the framework of the forced BDA model. The absolute instability of a steady boundary layer past a ramp is likely to have been discovered by Zhuk

+

<

Forced Generation of Solitary-Like Waves

389

and Ryzhov (1987), using the triple-deck scheme with a supersonic external flow. In their computation, the nearly periodic regime comes locally in place of steady separation, close to a corner point of this particular geometry, without giving rise to large-sized disturbances both upstream and downstream. A steady separation bubble with reverse flow inside can persist for a long time before turning to more complicated pulsating motion. This observation correlates well with a small value of w = 6.84 x lOP4k3 in the study of Camassa and Wu (1991a). Results of another paper by Camassa and Wu (1991b) based on a similar linear analysis point to the existence of the nearly periodic regime taking place in the forced KdV system in response to the disturbing source (4.28), where a1 = 0 but a2 # 0. On the other hand, Smith and Khorrami (1991) suggest a completely different scenario of the separation-bubble breakdown that involves the formation of a strong singularity predicted earlier by Smith (1988) for any interactive boundary-layer environments. The two points of view can be reconciled if the singularity for large-sized disturbances (including solitary-like waves) is allowed within the near-wall viscous sublayer scaled by ( 4 3 , (4.6) and controlled by the classical boundary-layer equations in t , y e d , z. In this case the excess pressure Ped = p ( t , z ) is expressed in terms of the predetermined displacement thickness 6ed = yw - A,(t, z ) coming from a solution of the forced KdV model.

E. SLOWDISTURBANCE-GENERATION PROCESS Guided by conclusions from the linear and nonlinear analyses of Camassa and Wu (1991a,b), as well as results set forth in Section I11 for the forced BDA system, we proceed to a systematic discussion of the changes occurring in the KdV disturbance-generation process as the similarity parameter S in (4.3 1) varies (Bogdanova-Ryzhova and Ryzhov, 1995b). It is worth remembering that S = 12 for an obstacle of the form (4.32), regardless of the value of the wavenumber k. In what follows, the shape of a local roughness is kept identical to that used in the BDA computation, namely g = t/t0, to = 1, whereas h = ocos2nx/2b, -b < x < b and h = 0 for both x 6 -b and x 3 b, b = 3.5. The process in question may be expected to be strongly dependent on whether a hump or a dent is chosen as the disturbing source. With this reservation in mind, we begin with a consideration of humps, assuming S > 0. No attempt will be made to derive the corresponding stationary solution and to put it to a stability test, since the computation always shows the unsteady response in the form of strong nonlinear oscillations. The instantaneous displacement-thickness distributions are illustrated in Figure 32 for two values, S = 1.0 and S = 5.0, which may be regarded as suffi-

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

390

S=l.o

S-5.0 1-850

1=550

1=550

1450

1=W

a:+ A 1=150

0.02 0.01

3 0

;5-0.01

-0.1

loo

0 X

200

0

loo

200

X

FIG.32. Instantaneous wave patterns for sufficiently small (S = 1.0) andmedium-sized (5' = 5.0) humps. a) The Upstream separating front x f I , is still indistinguishable. b) An upstream soliton breaks away from the obstacle, and two downstream solitary waves are built up at t = 850 (cf. Tj, 700).

ciently small and moderate, respectively. These curves should be compared with the plots of the corresponding disturbance fields computed in the context of the forced BDA system and presented in Figure 11 for Q = 0.9 and Q = 1.5. Up to t = 850, the wave patterns in Figure 32a obtained with S = 1.0 consist of a quasi-steady peak above the hump and an oscillatory tongue extending far downstream, no nonlinear eigenmode emerges at that stage. The next stage becomes conspicuous when the first soliton breaks away from the hump, much later than the nonlinear solution sets in on either side of the local roughness. Figure 32b, where S = 5.0, gives an indication of the onset of this event. An upstream soliton is seen here to be shaping at t = T,, 700. Thus the stronger the external source is, the less time nonlinear effects need to be accumulated to give rise to slow solitons. However, to further elucidate the slow disturbance-excitation process, the value of the similarity parameter should be substantially increased. The wave patterns at the threshold of bifurcation are drawn in Figure 33 for S = 12.60. In many respects they bear close resemblance to analogous wave patterns characteristic of the subcritical regime I in the forced BDA system

Forced Generation of Solitaly-Like Waves

39 1

5=12.60

-x =

I

0.50. Lo -0.5

-100

0

100

200

300

400

X

F l G . 3 3 . Instantaneous disturbance patterns in the subcritical regime (S = 12.60). Even at the threshold of bifurcation, only a few solitons are seen to advance upstream. The number of downstreamsweeping solitary waves is approximately doubled.

(cf. Figure 13). The disturbance field behind the local hump is seen to begin with a long, modulated oscillatory tongue of small amplitude, known from Figure 32. This rapidly spreading motion terminates in gradually evolving solitarylike waves. The disturbance system as a whole is separated from the obstacle by a depression with smooth variations of 6 ( t , x ) , which spreads extremely slowly. The depression area serves as a negative background, allowing solitary waves to be formed from the tail-end cycles of small-sized oscillations running downstream. However, within the framework of the forced BDA system, mild pulsations of a transitional type fill up a short intervening region that comes to light between the small oscillatory tongue and solitary-like waves. An analogous region is hardly discernible when passing to the KdV model. In the latter case, small-sized oscillations smoothly turn into solitary waves, without introducing sharp distinctions between disturbances of these two types. For this reason it is difficult to assess the number of downstream-travelling solitary waves. In contrast, no oscillatory motion preceding the upstream-advancing solitarylike waves originates in front of them. The amplitude of the leading soliton is approximately twice as large as the disturbance size immediately above the hump.

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

392

This observation correlates well with the corresponding statement related to the forced BDA system. Apparently, the number of solitary waves evolving from the tail-end cycles of low-amplitude oscillations downstream of the obstacle exceeds the number of upstream emitted solitons. At the same time, the aforementioned uncertainty in discriminating between solitary-like waves and smaller-sized oscillations must be properly accounted for. Both the incipient transition time and the period of the soliton emission upstream of the hump in this subcritical regime at the threshold of bifurcation can be estimated as T,, x T x 100. It is pertinent to note that wave patterns computed by Camassa and Wu (1991a) for the ramp-type obstacle (4.32) are most likely to belong to a similar regime of slow disturbance generation. As is known from the analysis of the forced BDA system, the way in which S varies in the hump region is crucial for the overall process of the disturbance generation. Figure 34 shows that & ( t ) = S ( t , 0) sharply drops, shortly after triggering the external source, and then gradually changes around 60 x 0.45 if S = 12.60

I

0

50

I

100

150

200

I

I

I

t

t

250

300

350

400

450

t FIG. 34. The displacement thickness

Sg at the hump crest as a function of time t in the subcrit-

ical regime (S = 12.60) and the supercritical regime (S = 12.61). Vigorous pulsations stem from bifurcation within an interval 12.60 < S < 12.61.

Forced Generation of Solitary-Like Waves

393

(coincidentally, nearly the same mean value is characteristic of the subcritical regime I at the threshold of the first bifurcation in the BDA system). The slack run of 60(t),with smooth variations confined to a very narrow band, is at the heart of the fairly large period T M 100 of the soliton emission upstream. The evolution of a single solitary-like wave at the tail end of the oscillatory motion takes seemingly less time. In turn, owing to the large T , nonlinear disturbances discharged to crossflow in a 3D boundary layer in opposite directions are of moderate amplitude and therefore move slowly both downstream and upstream. Small-amplitude pulsations over the hump as well as the generation of slow solitary waves are distinctive features of the subcritical regime in the forced KdV system. With some slight deviations, the regime in question parallels the subcritical regime I in the BDA model.

F. BIFURCATION AND GRADUAL EVOLUTION The smooth evolution of wave systems suddenly comes to an end in an attempt to further increase the value of the similarity parameter beyond S = 12.61. The disturbance pattern changes drastically, with S growing within a narrow interval, 12.60 < S < 12.61, where bifurcation happens (Bogdanova-Ryzhova and Ryzhov, 1995b). To disclose the existence of a threshold value S = S*,let us consider again the mass M-b = M - b ( f ) carried by the wave system in the region -co < x < -3.5 upstream of the hump. Note that the total mass of oscillations remains constant on the strength of (4.30). The plots of M-b in Figure 35 defined by (4.29) suggest that a solution for S = 12.60 typical of the subcritical regime with S < S* suffers stability loss if the governing parameter increases by only 0.01 and becomes equal to S = 12.61. As known from the above analysis of the corresponding phenomenon occurring in the forced BDA system, a new solution arising from bifurcation is endowed with completely different properties, this solution marks the beginning of the supercritical regime specified by S > S*. According to the results computed, the incipient transition time T,, x 100 of the nonlinear eigenmode excitation remains unchanged, whereas bifurcation comes into operation somewhat later, at t x 130. This happens because an earlier phase of disturbance generation still belongs to the subcritical regime; however, as soon as the first KdV soliton is built up upstream of the hump, the process turns to the next, more intensive stage related to the supercritical regime. (We note that an estimation for the passage from one regime to the other turns out not to be instructive if it is given in terms of the mass radiated upstream, since the mass M , of a single KdV soliton depends, by virtue of (4.22), on its wavenumber (and amplitude).) Although the

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

394

2.45

h

0

50

100

150

200

F I G . 35. The mass M-h transported by the wave system upstream of the hump as a function of time r for a wide range (1.4 S 193.0) of the similarity parameter.

< <

number of steps in the run of a curve in Figure 35 drawn with S = 12.61 still determines the number of upstream emitted solitary waves, the height of each step varies according to the intensity of a particular wave discharged to crossflow of the boundary layer. With this reservation in mind, the reference time T required for the production of a nonlinear disturbance may be deemed as being T x 25

Forced Generation of Solitury-Like Waves

395

(note that T x 100 if S = 12.60). This implies that slow solitons of the subcritical regime give way to fast solitons when the supercritical regime is called into being by bifurcation. Like that of the BDA solitons, the amplitude of the KdV solitary waves grows proportionally with the absolute value of their phase velocity (the mass M , increases as the square root of -c). The instantaneous displacement-thickness distributions shown in Figure 36 for S = 12.61 provide a further insight into changes provoked by bifurcation in the disturbance fields. The number of upstream-advancing solitary waves emitted by the same time t = 400 increases from 4 to 17 when passing through the threshold value S = S* inside the narrow interval 12.60 < S < 12.61. Accordingly, the amplitude of these strong disturbances becomes approximately 3.5 times larger. We omit a detailed discussion of the vigorous unsteady motion arising from bifurcation; however, it is worthy of note that the solitary waves within their combs are not strictly arranged in decreasing order of amplitudes with the highest peak ahead S~12.61

t=150

-x

2c 1-

b100

a 0

-1 -

FIG. 36. Instantaneous disturbance patterns in the supercritical regime ( S = 12.61). Upon bifurcation, fast solitary-like waves of much larger size appear in place of slow solitary waves both downstream and upstream.

396

Oleg S. Ryzhov and Elenu V Bogdunova-Ryzhova

of others. One more feature to be mentioned is that a clearly defined nonuniform elevation is missing from the disturbance patterns upstream of the hump, where the wavetrains propagate against the oncoming stream without forming an intrinsic footing. As in the forced BDA system, the most crucial dissimilarities between the two regimes, superseding one another in response to bifurcation, manifest themselves in the behavior of disturbances immediately over the hump, i.e., within a short interval, -3.5 < x < 3.5. To elucidate the mechanism at the heart of the fast solitary-wave production in the supercritical regime, let us turn back to the plot of 6 0 ( t ) . As Figure 34 demonstrates, the slack run of this curve with S = 12.60 gives way, after the end of the incipient switch-on process, to vigorous pulsations of a nearly constant period T x 16.0 if S = 12.61. According to the above estimation, it is just the time required for the radiation of a solitary wave upstream of the obstacle. However, the resemblance of the BDA and KdV generation processes does not go beyond this point. A comparison of the curves in Figure 14 with those in Figure 32 discloses marked distinctions in the type of pulsations under discussion. Whereas a sharp peak surmounting each BDA cycle springs up from a smooth curve associated with the preceding subcritical regime, the bifurcation in the forced KdV system gives rise to an initial overshoot in the displacementthickness variations, which is accompanied by a short transient phase terminating in slightly modulated strong pulsations around some mean value. This mean value is about 2.5 times as large as the corresponding mean value inherent in the subcritical regime at the threshold S = 12.60 of bifurcation. When reaching minimum values, the displacement thickness does not drop to a level characteristic of the subcritical regime. Vigorous pulsations at the hump crest progress evenly without being shaped into sharp positive peaks. No perceptible kink appears within a pulsation cycle. Because of the smoothed evolution of the generation process, the amplitude of strong disturbances, shown in Figure 36 to move upstream of the obstacle, is comparable with the size of vigorous pulsations. Unexpected difficulties emerge in an attempt to identify the nature of strong disturbances: except for the first few, they actually seem to be closer to cnoidal waves specified by (4.14) or (4.24), (4.26), with the parameter rn being close to 1 rather than to solitons (4.20) or (4.29), where a1 = a2 = 0. However, the leading disturbance is of the solitarywave type. Its amplitude exceeds the amplitude of an analogous solitary-like wave in Figure 33 by a factor of about 3. Since the phase velocity increases linearly with the amplitude of a KdV soliton, the propagation speed of solitary waves in the supercritical regime is also enhanced by the same factor, so that they are capable of advancing fast enough against the oncoming stream.

397

Forced Generation of Solitary-Like Waves

Further evidence in favor of the above statements comes from examination of the phase portrait of the supercritical regime in a plane (60, &). We observe in Figure 37 a trace representing the initial overshoot in the displacement-thickness variations, then two turns of a curve corresponding to the transient-type phase, and finally a band filled by oscillation coils. These are the maps of slightly modulated strong pulsations around a mean value derivable from Figure 34. By no means do the oscillation coils coalesce to produce a near-limit cycle in the plane (60, &>, although the band formed by them is not wide. By and large, this stage of the KdV generation process departs from the limit cycle far more than in an analogous case peculiar to the forced BDA system. In a broad range that is bounded from above by a value S = 193.0, the flow field undergoes a smooth evolution, without abrupt changes caused by subsequent bifurcations (Bogdanova-Ryzhova and Ryzhov, 1995b). As we know, the key element to gradual evolution of the disturbance excitation comes from alterations occurring in the form of pulsations immediately over a local roughness on a flat plate. The process is characterized by four plots presented in Figure 38 for differ-

I

-0.4'

0

Ss12.61

0.5

1

1

1.5

2

2.5

I

3

I

3.5

U) FIG.37. Phase portrait of vigorous pulsations at the hump crest in the plane (S,&) (S = 12.61). The band formed by oscillation coils does not collapse into a limit cycle.

Oleg S. Ryzhov and Elena K Bogdanova-Ryzhova

398

S=30.

S=60.

6

10

- 4

s

B

5

2 0' 0

50

100

0' 0

150

t

50

100

150

t

(b)

s=120.

s=90.

15

20 15

c

10

v

00"

10 5

0

5 50

0' 0

100

t

(c)

50

100

t

(dl

FIG. 38. The displacement thickness 80 at the hump crest as a function of time f for different values of S. The mean value of modulated pulsations grows steadily as the similarity parameter increases.

ent values of the similarity parameter. The initial overshoot in the displacementthickness variations becomes more clear cut and is accompanied by a longer transient phase terminating in modulated strong pulsations. From a comparison between Figure 34 and the plots in Figure 38, we observe that the mean value about which vigorous pulsations develop at the hump crest with S = 12.61 is progressively increasing as the similarity parameter takes on successively larger values. Accordingly, a period of modulated pulsations shortens from T FY 16.0 to 4.0 when S amounts to 120.0. In this case a kink appears on the leeward side of each large-amplitude peak, and smaller-size pulsations continue to evolve smoothly. Each oscillation cycle results in the excitation of an upstream solitary (or nearly cnoidal) wave, with the mass M,$depending on its intensity, and the discharge of a gently sloping disturbance of the mass -MF to the depression zone downstream. In compliance with the above observations on the displacement-thickness evolution at the hump crest, the corresponding phase portraits in Figure 39 show

Forced Generation of Solitary-Like Waves

399 s40.

S=30. 2

5

Fi -a 8

1

0

0

-1 -5

0

2

4

5

0

6

10

60U)

60(t)

(b)

.I

s=90.

15 10

-

5

F g o -5

s=120.

-20 -1 0

-10

0

(c)

(d)

F I G . 39. Phase portraits in the plane (So.lo),featuring the smooth evolution of vigorous pulsations at the hump crest in the range studied (12.61 < S < 193.0). The band-shaped domain progressively broadens as the similarity parameter increases.

an increased number of turns made by an image curve in mapping the initial overshoot and transient-type stage onto a (SO,&)-plane. In each of these plots, a fairly broad band filled by coils of different sizes is a map of vigorous pulsations around a mean value in a later period of the disturbance-radiation process. A band-shaped domain is broadened because of a rather strong modulation of pulsations for large values of S. It is worthy of note that a large-amplitude peak in the displacement-thickness distribution with a kink on the leeward side gives rise to a coil in the (SO,&)-plane, which somewhat resembles the asymmetric limitcycle-type portrait of the BDA generation process in the supercritical regime I with 3.93 < Q < 10 (see Figures 17 and 20a). The trajectories of the displacement-thickness maximum S,, defined by (3.40) result in the plots drawn in Figure 40. They have many properties in common with similar presentations of the forced BDA system. Except for the initial

400

'F, >

Oleg S. Ryzhov and Elena 'ci Bogdanova-Ryzhova S=60.

S=30.

b

( 0 4

i

2 0

-2

0

2

~

-2

@ + ~

.

0

2

Xmax

s=120.

s=90.

Xmax

(C)

Xmax

(a

FIG.40. Maps on the plane (xmax. Smax) of the vigorous pulsation process at the hump crest, illuminating the salient properties of the solitary wave radiation in the range studied (12.61 < S < 193.0). The broadening of the band-shaped domain occurs in response to vigorous pulsation modulation for large S .

overshoot responsible for the radiation of the strongest solitary wave upstream, 6max emerges on the windward side of the hump and moves downstream. On the leeward side of the local roughness it makes a sharp turn and then advances upstream, rapidly growing in magnitude before reaching the obstacle crest. Upon passing the crest, &ax loses its intensity but does not decay to a small value. Because of strong modulation featuring the displacement-thickness pulsations, trajectories in a plane (xmax,S,,) fall within a band that is moderate in width (cf. thin strips in Figure 21, peculiar to the forced BDA system). A solitary (or nearly cnoidal) wave leaves the leading edge of the hump at the end of each cycle. Since the pulsation cycles differ from each other, the amplitudes of upstream emitted disturbances are not equal and therefore they cannot propagate with the same velocity.

Forced Generation of Solitary-Like Waves

40 1

The next four figures (Figures 41-44) display results of the computation with a high value S = 190.0 of the similarity parameter. On the whole, they confirm the above conclusions about the character of the KdV radiation process sustained by humps. Figure 41 shows the soliton nature of the leading disturbance breaking away from a few other solitary-like waves followed by nearly cnoidal oscillations. The displacement-thickness amplitude at the hump crest becomes four times as large as the leading soliton. Disturbances within upstream-advancing combs are not arranged in decreasing order of their amplitudes; rather they show distributions not to be governed by an apparent rule. A depression region with smooth variations of s ( t , x) downstream of the local roughness appears as a background, allowing solitary-like waves to build up from the tail-end cycles of the highly modulated oscillatory tongue. Reckoned from the depression level, the amplitude of these solitary-like waves proves to be of the same order as the amplitude of disturbances ahead of the obstacle. Much like upstream-propagating waves, downstream-sweeping disturbances do not make up well-organized oscillation patterns.

t-65 t=55 t=45 t=35 t=25 t=l5 30P

7?20 -

2510-

0- ,

,L. t=5

1

1

X

FIG. 4 I . Instantaneous disturbance patterns in the supercritical regime for a high value (S = 190.0). Both the solitary-like and cnoidal-like waves appear in sequences that are not well organized.

Oleg S. Ryzhov and Elena 'Li Bogdanova-Ryzhova

402

s-190.

0

10

I

I

I

I

I

20

30

40

50

60

t

FIG.42. The displacement thickness So at the hump crest as a function of time t (S = 120.0). Vigorous pulsations about their mean value (So = S, z 23.5) become highly modulated.

An initial overshoot, responsible for exciting the leading soliton upstream of the obstacle, is seen in Figure 42 to be creating displacement-thickness variations. The next three peaks here are of approximately equal sizes, they bring about a bunch of three nearly identical solitary waves traveling together. A small kink emerges on the leeward side of almost each peak of highly modulated pulsations at the hump crest. The kinks lead to minor loops, featuring successive turns made by an image curve in mapping modulated pulsations onto a plane (60,80). As we may infer from Figure 43, these loops are not confined to a narrow strip similar to that arising not far from the origin in Figures 20b, c, d for the forced BDA system. On the whole, the phase portrait in Figure 43 has nothing in common with the limit cycle. By contrast, a large broad domain proves to be densely covered by traces of the image curve, providing a map of pulsations at the hump crest. A broad band densely filled by oscillation coils is also characteristic of the map of the disturbance-generation process onto a plane (xmax,SmaX)in Figure 44. Examination of the map shapes raises a question of conceptual significance as to whether random elements start developing in fluid motion controlled by the

Forced Generation of Solitary-Like Waves

403

s-190.

40

30 20

. g 5

10

0 -10

-20

-30

-40 0

5

10

15

20

25

30

s, 0) F I G . 43. Phase portrait of vigorous pulsations at the hump crest in the plane (So. 80) (S = 190.0). The broad domain is almost entirely filled by oscillation coils.

forced KdV model, as the similarity parameter S grows. We have addressed an analogous question at the end of Section 1II.H in connection with the second bifurcation in the BDA system, when the supercritical regime IV suddenly appears in place of the subcritical regime 111. A different scenario for erratic pulsations to come into play within the framework of the KdV model could seemingly be based on gradual alterations, bypassing abrupt changes.

V. Solitons and the Onset of Random Disturbances A. RANDOMIZATION TRIGGERED BY A HARMONIC SOURCE

So far the problem just stated has no rigorous resolution. On the other hand, some light may be shed on the essence of the matter by using results of the dynamical systems theory (Ryzhov, 1991,1994; Burov and Ryzhov, 1992; Bogdanova-

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

404

s=190.

30 -

25 20 -

z

f.0

15 -

10 -

1

O

$

-2

, -1

0

1

2

3

Xmax

FIG.44. Map on the plane (xmax.Smax) of the vigorous pulsation process at the hump crest (S = I90.0). The broad domain is seen to be densily covered by oscillation coils.

Ryzhova and Ryzhov, 1995a). To this end, let us assume the shape of an uneven wall to be time-dependent and fixed by y = y w ( t , x ) . For instance, the situation under discussion can be realized in experiments with a flexible wall slightly distorted by a harmonic wave sweeping downstream. Then the wavy plate serves as an external agency f = f ( k x - wt) =

a3yw(kx - w t ) ax3

for the crossflow motion in a 3D boundary layer adjacent to the solid surface. Another (and even simpler) example of an interacting 2D boundary layer arises from a viscous flow past a flat plate mounted vertically in the gravity field and heated (Messiter and Liiian, 1976; Smith and Duck, 1977; Ryzhov, 1982). With a forcing term taken in the forms of a traveling wave f = f (kx - w t ) , the KdV equation admits a similar traveling-wave-type solution, A , = F(kx - w t ) .

Forced Generation of Solitary-Like Waves

405

On applying the affine transformation mentioned in Section IV.C., F is derivable from a system of two first-order differential equations, (5.la)

where I, = sin and

e, c = x - t , stands for a harmonic excitation normalized by 6

H = Ho(F, k )

+ 6H1((, F ) (5.2)

<

denotes a Hamiltonian function. Unlike (4.10), is introduced in such a way as to rule out both the wavenumber k and the frequency w. In consequence, a modified entity w, = w / k 3 enters the right-hand sides of (5.lb) and (5.2). The model at hand can be treated as describing nonlinear oscillations of a pendulum with quadratic stiffness and no friction. Notice that there is no obvious reason for supplementing (5.2) with a term F F , since it has nothing to do with conventional mechanical friction. However, the second derivative, a 2 A , / a x 2 , necessary for F F to occur, is sometimes dependent on turbulent pulsations in crude models of real atmospheric environments (Christie, 1989). A phase-plane portrait of (5.1), (5.2) with 6 = 0 includes a center C: F, = w, - ( w i - 2C)'/2, Fc = 0 surrounded by a nested family of closed orbits. They represent periodic cnoidal waves in the form (4.14) or (4.24), with parameters bl and b2 fixed by (4.26), if allowance for the aforementioned redefinition of is made. An alpha-shaped separatrix loop enclosing the periodic orbits passes through a saddle S: F, = w, ( m i - 2C)'/*, FA = 0. The loop is an image of a soliton (4.20) or (4.28), where bl and b2 are given again by (4.26), taking into account the redefinition of In line with general properties, the soliton moves downstream against positive background perturbations F = Fs > 0, which correspond to a negative depression in the instantaneous displacement-thickness distribution. The separatrix loop forms the base of a cylindrical surface with generators parallel to the (-axis in the three-dimensional phase space (<, F , $). With 6 # 0, this surface splits into two manifolds, W,(6) and W,(6). The former is stable, whereas the latter is unstable. The relative location of these manifolds is known to control the dynamics of the system (see, for example, Guckenheimer and Holmes,

c

+

e.

Oleg S. Ryzhov and Elena I? Bogdunovu-Ryzhova

406

1983). We may exploit the results of the general theory to draw necessary conclusions about the case cast in (5. I), (5.2). Instead, a Mel’nikov function to easure the distance separating Ws(6) and W, (6) can be directly evaluated from an expression

Here the braces denote canonical Poisson brackets, perturbation calculations are supposed to rely on the initial soliton solution written in the form Fsol

= Fs -

3 ( 4 - 2C)I’*

ch2q

,

. Fsol

=

3(wi - 21Z)~I~shq ch’q

Let us substitute FsOland tso into l relations for Ho(F, k ) and H I (<, F) ensuing from (5.2). As a result, the general expression (5.3) reduces to (Burov and Ryzhov, 1992)

+ i)n,

Thus the Mel’nikov function has an infinite set of simple zeros, cpo = ( n n = . . . , -1,O, 1, . . . explicitely fixed by (5.4). It follows from this that W S ( 6 ) and W,(6) intersect indefinitely many times. This property is embodied in a Poincart map in Figure 45, where the homoclinic tangle contains a wide vari-

n

FIG.45. Paincare map with two homoclinic tangles erising from the splitting of the alpha-shaped separatrix and a subharmonic periodic orbit (from Bogdanova-Ryzhova and Ryzhov, 1 9 9 5 ) . Both homoclinic tangles involve trajectories with unpredictable behavior. Reprinted with permission of the Royal Society of London.

Forced Generation of Solitary-Like Waves

407

ety of different trajectories, including those with unpredictable behavior. On the whole, they determine the complex dynamics of the Hamiltonian system (5. l), (5.2) in spite of its apparent simplicity. A far more refined analysis is required when considering the splitting of closed orbits around the center C in the phase plane ( F , 8’) in response to a periodic forcing. For this reason, cnoidal waves are difficult to treat by using singular perturbation technique. The vanishing of the Mel’nikov function along a closed orbit, such that the corresponding free-oscillation frequency depending on w, is rationally commensurable with the forcing frequency, points to the existence of a subharmonic resonance. An upper estimate shows that splitting does occur; however, the splitting distance to separate stable and unstable manifolds turns out to be exponentially small (Neishtadt, 1984; Holmes et al.,1988). The presence of the homoclinic tangle gives rise to complex dynamics within a subharmonic resonance band involving trajectories with unpredictable behavior. A “beyond all orders” version of the Mel’nikov function has recently been demonstrated by Scheurle et al. (1991) and Kummer et al. (1991) to provide a legitimite mathematical tool for justifying the existence of the homoclinic tangle associated with the exponentially small splitting peculiar to a subharmonic resonance. The PoincarC map in Figure 45 gives a good idea of the homoclinic tangle emerging in place of a closed orbit in responce to a periodic forcing. The conclusion of conceptual importance from an analysis of all of the trajectories within the homoclinic tangles of both types mentioned is with regard to the development of dynamics referred to as Hamiltonian chaos. This arises from integral curves of the system (5.1) with unpredictable behavior but is, meanwhile, not a strange attractor (Guckenheimer and Holmes, 1983). The existence of orbits that are random in nature can be reformulated in terms of the original problem on crossflow disturbances in a 3D boundary layer or oscillations in a heated jet adjacent to a slightly vibrating plate. As soon as they enter an essentially nonlinear stage, large, well-organized structures would be expected to emerge in the form of solitary-like boundary-layer flow rather than being dependent on a particular type of environment under consideration. As was argued in Section II1.B in reference to experimental data from Borodulin and Kachanov (1988, 1990) and their in-depth discussion in Kachanov et al. (1993), this is the case as applied to the Blasius boundary layer, where the sharp narrow spike embedded in each oscillation cycle of a nonlinear TS wavetrain is endowed with soliton properties. The above findings from the extensive computation point to the same general concept for both BDA and KdV models controlling streamwise as well as crossflow disturbances in the truly nonlinear stage. Therefore, the breakdown of the high-amplitude wave pattern under the influence of an external harmonic source

408

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

should result in the excitation of a wide variety of more complex forms of fluid motion involving, in particular, random elements. Vigorous, erratic pulsations are also likely to be suddenly brought about by the second bifurcation in the forced BDA system and to gradually evolve in the KdV generation process. Thus the role played by high-amplitude periodic and solitary waves is twofold: they make up individual coherent structures and, at the same time, can provoke chaotic elements in the disturbance patterns (Ryzhov, 1991,1994; Burov and Ryzhov, 1992). The two properties of the nonlinear phenomenon are interconnected and inseparable. Supposedly these properties are just the ones needed to control the erratic arrays of large disturbances in Figures 23 and 41. B. FORMATION OF SOLITONS INSIDE ERRATICALLY DISTRIBUTED SIGNALS We may pose the opposite question, whether it is feasible for solitons to build up in the front part of an oscillatory tongue. Moreover, in Figure 41 severely modulated low-amplitude signals downstream of the obstacle appear in sequences that are not well organized. Furthermore, large coherent structures are known to form and persist for a long time, even in fully developed turbulent flows, where they are impinged on by strong chaotic disturbances (see, for example, Zilberman et al., 1976; Wygnanski et al., 1979). Nevertheless, our previous experience, based upon the forced BDA and KdV systems, would lead to a negative answer to the question raised, because solitary-like waves gradually evolve behind the hump only from the last cycles bringing up the rear of the oscillatory tongue. In an attempt to theoretically elucidate the essence of the matter, let us take advantage of a more sophisticated model: - + A w z - at

a3A, dX - A0 7 - f ( t ,x), ax

(5.5a)

which involves dispersion terms typical of both the BDA and KdV systems, each taken separately. The corresponding homogeneous equation involving the only similarity parameter A0 has been independently advanced by Ryzhov (1991, 1994) and Benjamin (1992) in their studies of completely dissimilar physical environments. Ryzhov (1991,1994) arrived at (5.5) with f = 0 in the context of 2D boundary-layer oscillations by taking into account the second-order effect of the streamline curvature on the velocity field. Although centrifugal forces in-

Forced Generation of Solitary-Like Waves

409

duced by the nonzero curvature are small, they may become comparable to the leading term expressed by the Hilbert integral in an expression, a2A d X - A0 2, ax for the excess pressure p , provided that the disturbance wavelength becomes short enough. This expansion is akin to (2.4); the distinction is that the second derivative of A is taken with respect to x rather than z . In spite of the fact that retaining only some of the second-order effects cannot be assigned to a strictly rational asymptotic approach, the resulting model points, nevertheless, to new, important features intrinsic to nonlinear waves driven by the normal pressure gradient. Within the framework of 2D boundary-layer flows, A0 is proportional to a ratio A l b ; therefore this quantity must be considered as a small parameter, but in practical situations it can typically reach a value of order 0.2. Benjamin (1992) derived (5.5) with f = 0 in an analysis of unidirectional propagation of long waves in a two-fluid system in which the lower fluid has greater density and is indefinitely deep. The effects of capillarity in the interface enter the model, notwithstanding the fact that they are, strictly speaking, of the second order. As a result, A0 proves to be a large parameter in this description. A forcing function (5.5b) was defined in terms of boundary-layer flows by Bogdanova-Ryzhova and Ryzhov (1995b). Unlike the parent homogeneous BDA and KdV equations, in their compound (5.5a) where f = 0 is practically unknown. It is not even proved to fall into a family of fully integrable evolution systems possessing infinite numbers of conservation laws (Drazin and Johnson, 1989; Ablowitz and Clarkson, 1991). However, three conservation laws in the form 00

eidx = 0 might be indicative of this important property, which is at the heart of soliton solutions. The densities ei in (5.6) are given by (Ryzhov, 1991, 1994; Benjamin, 1992)

el=A,

e 2 = -1 A 2, 2

(5.7a, b)

The first two of them, specified in (5.7a, b), are densities generic to both the BDA and KdV systems. As ( 5 . 7 ~ shows, ) the third one is a sum of the corresponding

410

Oleg S. Ryzhov and Elena L? Bogdanova-Ryzhova

BDA and KdV densities. Insofar as the concept of nonlinear eigenmodes, excited by an external agency in the form of high-amplitude periodic oscillations or solitons, was seen to be the cornerstone when the disturbance-generation process was analyzed, the existence of solitary-like waves intrinsic to the compound BDA-KdV equation is examined in some detail below. Values of the similarity parameter A0 are supposed to be small or moderate, as is the case in wind-tunnel tests with boundary-layer flows. To this end, let us seek a solution of the traveling-wave type, A = F ( < ) , = x -ct, where c designates the phase velocity, and assume F to be an even function obtainable from an integral-ordinary differential equation,

<

An integration constant Ao, standing for background perturbations at infinity, is set at zero in the subsequent discussion. Then the boundary conditions read (5.9) In (5.8), (5.9) we have a nonlinear eigenvalue problem in the phase velocity c posed and studied by Benjamin (1992). The functions corresponding to eigenvalues of c can be treated as nonlinear eigenmodes inherent in 2D boundary-layer motion. This problem admits of an explicit solution in the form of an algebraic soliton (Bogdanova-Ryzhova and Ryzhov, 1995b):

provided that c = l/(Aoyo) and yo equation, y3

5.519017 is a positive real root of a cubic

+ 15y2 - 625 = 0.

As the parent BDA and KdV solitary waves, the algebraic soliton of the compound BDA-KdV system is capable of moving upstream against zero background perturbations at a speed depending on A0 < 0. To the contrary, the mass 00 24 =L_(-A)dx = 5 n

of the soliton does not depend on a value of I A0 1 and exceeds in magnitude the mass of any one BDA soliton by 4/5n, regardless of the amplitude of the latter.

Forced Generation of Solitary-Like Waves

41 1

Upon linearization of (5.8) where Ao = 0, solutions exp(ik6) with k complex must converge to zero as + f00. The possible values of k satisfy a dispersion relation,

<

c = ksignk - Aok2,

(5.11)

which determines a maximum, c,

1 =4Ao '

(5.12)

achieved at Ikl = k, = 1/(2Ao). A comparison of the phase velocity c = l/(Aoyo) in (5.10) with the one given by (5.12) shows that the algebraic soliton sweeps downstream more slowly than infinitesimal harmonic waves and cannot break away from them. However, there are BDA-KdV solitary waves of another type with exponential decay at both infinities 6 -+ co.To see this, we consider (5.11) as a quadratic equation in k. The result, conveniently expressed by means of k = k , * i ( cT-) c,

112 ,

(5.13) shows that the propagation speed c of the solitary waves in question must be greater than the maximum speed c of infinitesimal harmonic oscillations defined in (5.12). These very fast solitary waves are just the ones we are looking for. They have oscillatory outskirts in the shape of short-scaled wiggles with the spacing n / k = 2nAo between separating zeroes, and their exponential decay at a ratio [(c - c,)/Ao]'/~ is achieved because of (5.13). The solitary waves under discussion are capable of breaking away from small-sized disturbances, even though they are born among cycles of the downstream spreading oscillatory tongue. The inhomogeneous model (5.5a), with a forcing term defined in (5.5b), provides an ideal means of illuminating the excitation of large-sized BDA-KdV solitons inside downstream-propagating signals (Bogdanova-Ryzhova and Ryzhov, 1995b). The general problem is extremely intricate because its solution depends on two similarity parameters, A0 and Q. For this reason we confine ourselves to an example showing the birth of solitary waves amid, and their subsequent breakaway from, disturbances behind a hump. As before, the hump shape is prescribed by h = c cos2 nx/2b, -b < x < b, where b = 3.5; the values of the similarity parameters A0 = 0.5, Q = 10 specify the case under examination. The instantaneous displacement-thickness patterns in Figure 46 clearly indicate two distinguishing features of the generation process. First, the form of a depression region downstream of the local roughness is no longer smooth; instead, high-amplitude

Oleg S. Ryzhov and Elena V Bogdanova-Ryzhova

412

t=1100 t=1000

w M

4

v

v

w

N

w

M

w

t=900 t=800

t=700 t=600 k500

Y

1400

t=300

b t=200 t=100

ioy ,?-0.5-1O 0

100

200

300

400

500

600

X

FIG.46. Instantaneous disturbance patterns for the compound BDA-KdV system (A0 = 0.5, Q = 10). The formation of very fast solitons amid and from depression-zone oscillations is clearly recognizable.

oscillations about some negative mean value develop here without being governed by an apparent law. As a result, the “foam” of erratically distributed signals occupies the entire region in place of gradually evolving waves. Second, solitons do emerge from these signals. A large disturbance is seen to be completely shaped into a solitary wave as early as t = 100. Then it breaks away from continuously generated signals and rapidly moves as a precursor of the oscillatory motion. The next solitary wave starts building up in the depression zone amid erratic pulsations some time between t = 600 and t = 700. At t = 1100, it proves to be separated from the depression zone but still surrounded by weak disturbances sweeping against zero background perturbations. At the same time t = 1100, the third solitary wave finds its way out of the depression-region oscillations. Small positive wings in the shape of solitary waves stem from the oscillatory behavior predicted by (5.13). Notice that small, short-scaled wiggles between the spikesolitons at the essentially nonlinear stage of the periodic disturbance development are also clearly discernible on the velocity oscilloscope traces in Figure 1 for x * b 460 mm.

Forced Generation of Solitary-Like Waves

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On the whole, the fast BDA-KdV solitons arising from the foam of erratically distributed signals bear some resemblance to large coherent structures that come into being, persist for a long time, and eventually die, being impinged upon by strong random pulsations, in fully developed turbulent shear layers (Zilberman et al., 1976; Wygnanski et al., 1979; Cantwell, 1981). The disturbance-excitation process, as considered in the context of the forced BDA, KdV, and compound BDA-KdV systems, is capable of capturing many essential features of boundarylayer flows at the threshold of laminar-turbulent transition, within the limits imposed by a 2D approach. Among these features are bifurcations, the birth of solitons from erratically distributed signals, and the onset of random elements in fluid motion. The concept of nonlinear eigenmodes is crucial for the theory which makes at present the first steps and calls for careful experimental verification.

Acknowledgments It is the authors’ pleasant duty to express their sincere thanks to Prof. Julian D. Cole for encouraging discussions and numerous comments made in the course of this study. In particular, the formulation of the similarity laws as applied to soliton-bearing systems arose from his profound remarks on mechanisms underlying the wave-excitation process. Special thanks go to Prof. Theodore Y. Wu for the suggestion to write a survey on the rapidly developing subject of forced nonlinear oscillations in boundary-layer flows. The general policy of the Royal Society of London and Cambridge University Press that gives permission to authors to reproduce, with due references, results of their original papers is gratefully acknowledged. This work has been carried out with the support of O.S.R. of AFOSR under grant F49620-93- 1-0022DEE

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Author Index

Numbem in italics refer to pages on which the complete references are cited.

A

Bathe, K. J., 62, 72, 73 Beaudoin, A. J., 79,80, 87, 111, 119-121, 127, 135, 136, 138, 141, 142, 144, 163, 164 Becker, R., 79,163 Belytschko, T., 5, 57, 58, 72 Benjamin, T. B., 321, 322, 338, 339, 346, 408. 409,410,413 Bennett, K., 80, 107, 120,164,169 Benney, D. J., 319,415 Bensoussan, A,, 185,295 Beran, M., 174, 235, 296 Bercovier, M., 119, 164 Berveiller, M., 173, 212, 262, 296 Betchov, R., 319,413 Bhattacharya, K., 215, 296 Bidanid, N., 45, 72 Biondo, A. C., 88,166 Birkhoff, G., 305,307,308,316 Bishop, J. F. W., 173, 185, 296 Bogdanova-Ryzhova, E. V., 325,326,346, 348,349, 351, 352, 357, 361, 366, 371, 385, 389, 393,397,404,406,409,410, 41 1,414 Bolourchi, S., 62, 72 Bonnet, G., 192,269,270,297 Bornert, M., 232,233,235,247,296 Borodulin, V. I., 319, 322, 327, 335, 340-346, 407,414 Bouchitte, G., 185, 296 Bout, A,, 62, 72 Boyce, M. C., 102, 164 Brandi, P., 314,315

Ablowitz, M. J., 323, 338, 348, 361, 381, 385, 409,413,414 Abramowitz, M., 351,381-383, 413 Acrivos, A,, 321, 338,414 Adams, B. L., 87,168 Aernoudt, E., 80, 169 Ahzi, S., 108-1 10,163,167,168,222,299 Akylas, T. R., 323, 386,413 Almroth, B. O., 62, 68, 72 Altmann, S. L., 163 Anand, L., 79, 80,166 Aravas, N., 174, 271,295 3,43, 72 Arbocz, .I., Argyris, J., 5 , 57, 58, 72 Asai, M., 319,4/6 Asaro, R. J., 78-80, 82, 89,90, 102, 108, 163, 165, 167, 168 Ashby, M. F., 88, 163, 165 Atluri, S. N., 142, 143, 163, 164 Avellaneda, M., 234, 295 Avery, D. H., 150, 166 Azrar, L., 3, 72

B Backofen, W. A., 126,163, I67 Bacroix, B., 151, 163 Bahei-El-Din, Y. A,, 260, 297 Baines, P. G., 324, 380, 413 Bammann, D. J., 104,163 Bao, G., 173,268, 273,295 Barlat, F., 121, 163 419

420

Author Index

Bratianu, C., 142, 143, 164 Britt, V., 4, 74 Brockenborough, J., 173,296 Brogan, F. A,, 5 , 15,53,54, 56, 62, 64-67, 72, 75 Bronkhorst, C. A,, 79, 80, 166 Brown, T. J . , 90, 166 Brush, D. O., 72 Bryant, J. D., 121, 164 Biichter, N., 62, 72 Budiansky, B., 2,43, 61, 72, 222, 234, 240, 244,249,276,296 Bufler, H., 62, 75 Bunge, H. J., 81, 87, 106, 164 Burggraf, 0. R., 321, 323,336-338, 346,350, 380,414,417 Burov, A. A,, 403,406,408,414 Buryachenko, V. A., 213, 239, 296

C Camassa, R., 323, 324, 387-389, 392,414 Canova, G. R., 90, 107, 108,163,164,166, 167,169,222,299 Cantwell, B. J., 413, 414 Carnoy, E., 43, 72 Carter, T. D., 318,417 Casciaro, R., 3, 73 Case, K. M., 361,414 Cesari, L., 314,315 Chan, K. S., 121, 124, 125,164 Chastel, Y.B., 80, 108, 112, 120, 127, 164, 168 Cheng, C., 174,271,295 Cherkaev, A., 215,233,299 Chin, G. Y., 94, I64 Choi, S. K., 79, 169 Christensen, R. M., 214,235,296 Christie, D. R., 324, 356, 405,414 Christman, T., 173, 274, 296 Chu, T., 262, 296 Clarke, F. H., 308,311,315 Clarkson, P. A,, 323, 338, 348, 361,381,385, 409,413 CICment, A,, 93, 164 Cochelin, B., 3, 72 Cole, J. D., 328, 337, 414 Cole, S. L., 323, 386, 414 Collin, T. J., 4, 74 Corke, T. C., 318,414 Coulomb, P., 164

Cowley, S. J., 3 18, 414 Craik, A. D. D., 32 1,414 Crisfield, M. A,, 3, 73 Crocker, A. G., 91, 167 Cuititio, A. M., 80, 164

D Dafalias, Y. F., 93, 164 Damil, N., 3, 63, 72, 73 Davis, R. E., 321, 338,414 Dawson, P. R., 79, 80,82, 85, 87, 90.91, 93-96,98, 102, 104, 108-1 12, 115, 118-121, 126-128, 135, 136, 138, 141, 142, 144, 148, 163,164,166-168 deBotton, G., 193, 200,202, 206, 208, 210, 254-256,261,269-27 1,286,296,300 de Buhan, P., 185,256,260,297 Dendievel, R., 192, 269, 270, 297 Denton, R. A,, 324, 380,414 Devaux, J., 245,297 Dluzewski, P. H., 82, 164 Doligalski, T. L., 366, 414 Douglas, A. S., 247,248, 299 Doviak, R. J., 324,414 Drazin, P. G., 323, 338, 345, 348, 385,409, 414 Drucker, D. C., 173, 186,200,244, 252, 259, 297,304,3 12,315 Duck, P. W., 332,350,377,387,404,4/4,417 Duva, J. M., 252,297 Dvorak, G. J., 260,276,297 Dvorkin, E. N., 73

E Eggert, G. M., 85.98, 104, 128,164 Einstein, A,, 252, 297 Ekeland, I., 280, 297 Ellison, J. A,, 407, 415 Engelman, M. S., 119, 164 Eshelby, J. D., 229, 232, 252, 297 Esling, C., 150, 151, 168 Esslinger, M., 6, 68, 7 1, 73 Etingof, P.I., 87, 168

F Farmer, D. M., 324,380,414 Fleck, N. A., 214, 297, 301 Fokas, A. S., 361, 414 Fox, D. D., 62, 75 Francfort, G., 230, 233, 236,297

Author Index Frank, F. C., 81, 82, 84, 85,95, 165 Frederick, S. F., 165 Fressengeas, C., 90, 11 1,164,166 Frey, F., 62, 73 Frost, H. J., 88, 165 Fukada, M., 150,168

G GLSjeu, M., 245, 247, 297 Garcea, G., 3,43, 74 Germain, P., 276, 278, 297, 298 Gilormini, P., 175, 180, 262, 268, 297 Golaganu, M., 245, 297 Goldstein, M. E., 318, 321, 415,417 Goldstein, S., 320,415 Golubitsky, M., 18, 63, 73, 75 Gotoh, M., 79, 165 Gottstein, G., 87, 106, 166 Greenspan, H. F., 319,415 Gresho, P. M., 119, 164 Grimshaw, R. H. J., 323,324,349,356,361, 386,415,416 Guckenheimer, J., 406,407, 415 Gurson, A. L., 245,297 Gurtin, M. E., 100,165

H Haftka, R. T., 3, 73 Hall, F. R., 80, 169 Hall, R., 6, 68, 71, 73 Hansbo, P., 94, 165 Hansen, J., 81, 165 Haritonidis, J., 408, 413,417 Harren, S. V., 79, 165 Hart, E. W., 128, I65 Hartley, P., 80, 169 Hasegawa, A., 121, I65 Hashin, Z., 174, 187,228,230, 248, 260, 262, 296-298 Hatch, A. J., 85, 121, 124, 165 Havlicek, F., 80, 165 He, M. Y., 251, 252,298 Heinz, A., 81, 82, 84, 165 Herbert, T., 318, 321,415 Hershey, A. V., 234,298 Herve, E., 232,233, 247, 248, 298 Hill, R., 173, 183, 185,225, 234,240,249, 262,296,298,304,311,313,3I5 Hino, S., 80, 165 Hol, J. M. A. M., 3, 72

42 1

Holmes, A. M. C., 72 Holmes, P., 407,415,417 Holmes, P. J., 406,407,415 Hom, C. L., 274, 275,298 Honeycombe, R. W. K., 89,165 Honneff, H., 108,165 Hori, M., 228, 300 Hosford, W. F., 91, 165 Householder, A. S., 31 1, 315 Hu, G., 213,298 Hughes, T. J. R., 5,57,58, 72,94, 165 Huh, H., 314,315 Hultgren, L. S., 318,417 Hunt, G. W., 11, 23, 75 Hutchinson, J. W., 90, 107, 120, 165, 173, 214,244,265,268-270, 273,295-298

I Ibe, G., 87, 165 Ibrahimbegovic, A., 62, 73 Iida, S., 319,416

J Jain, M., 121, 169 Jarvis, G. W., 121, 167 Jeanloz, R., 87,91, 151, 169 Jenkins, J. T., 87,90,93, 109, 120, 136, 138, 167-169 Johnson, C., 94, 114,165,166 Johnson,G. C., 87,91, 104, 119, 135, 138, 144, 151,163,169 Johnson, K. H., 45, 72 Johnson, R. S., 323,338,348,385,409,414 Jonas, J. J., 121, 169

K Kachanov, L. M., 289,298 Kachanov, Yu. S., 318-320, 322,327,335, 340-346,407,414,415 Kailasam, M., 227, 239, 256, 298, 300 Kalidindi, S. R., 79, 80, 166 Kallend, J. S., 87, 88, 106, 166 Kaplan, R. E., 408,413,417 Khorrami, A. F., 389,417 Klebanoff, P. S., 318, 321,326,415,417 Klein, H., 6, 68, 73 Knops, H. A. J., 42, 73 Kocks, U. F., 79-81, 87,88,90,91, 108, 109, 111, 120, 126, 136, 141, 142, 163, 164, 166,167,169

422

Author Index

Kohn, R. V., 189,215,233,269, 271,296, 298,299 Koiter, W. T., 2, 1 I , 18, 22, 23, 29, 30, 33, 61, 63, 64, 69, 73 Komoda, H., 319,417 Korzekwa, D. A,, 80, 87, 120, 136, 163 Koss, D. A., 121, 124, 125,164 Kouhia, R., 3, 73 Kozlov, V. V., 318, 319, 340,415 Kratochvil, J., 80, 165 Kreher, W., 213,298 Kroner, E., 234-236, 298 Kumar, A,, 82, 85, 87, 93-95, 127, 166 Kummer, M., 407,415

L Landahl, M. T., 3 19, 415 Landau, L. D., 318,388,415 Lanzo, A. D., 3.43, 73, 74 Larson, F. R., 150, 166 Laws, N., 222,287,299 Lebensohn, R. A,, 107, 151, I66 Leblond, J.-B., 245, 297, 299 Leckie, F. A,, 87, 167 Lee, B. J., 245, 251, 252, 299 Lee, E. H., 102, 166 Lee, S. J., 324, 380, 415 Lee, S. S., 318,415 Lee, Y.-S., 80, 166 Lemond, J., 79, 82, 167 Lenning, G. A., 165 Levchenko, V. Ya., 318,319,340,415 Levin, V. M., 225,299 Li, G., 247,248,271,274,275,298 Lifshitz, E. M., 318, 388,415 Lighthill, M. J., 415 Lifian, A., 377, 387, 404,416 Lions, J. L., 185,295 Lipanov, A. M., 213,239,296 Little, T. D., 215, 269, 271, 298 Liu, C. H., 260, 294, 297 Liu, K. H., 314,315 Lo, K. H., 214,235,296 Liicke, K., 81, 87,165 Luetjering, G., 150, 167 Lurie, K., 215, 233, 299

M MacEwen, S. R., 121, 169 Macheret, Y., 297

Mackens, W., 48, 74 MacLane, S., 305, 307, 308,315 Mallet, M., 94, 165 Mallet, R. H., 3, 73 Mammel, W. L., 94,164 Mandel, J., 276, 299 Maniatty, A. M., 80, 166 Marie, J., 58, 74 Marin, E. B., 90, 102, 115, 118, 120, 136, 138, 142,166, 167 Marsden, J. E., 407,415,417 Mathur, K. K., 79, 80, 87,90,96, 108, 109, 111,119-121, 126, 135, 136, 138,141, 142, 144,163,164, 167 Matzenmiller, A,, 62, 74 McCoy, J. J., 240, 249, 299 McHugh, P. E., 167 McLaughlin, R., 235,288,299 McMeeking, R. M., 173,268,273,295 Mear, M. E., 245, 251,252,299 Mecking, H., 79, 108, 151, 163, 165 Messiter, A. F., 320, 328-330, 377, 387,404, 416 Michel, J. C., 245, 262, 299 Miehe, C., 51, 76 Mika, D., 98, 167 Miller, M. P., 91, 167 Milton, G. W., 189, 215, 233-236, 240, 249, 298,299 Mindlin, R. D., 61, 74 Mitsudera, H., 324, 349, 356, 361,416 Mizukami, A,, 94, 165 Mlejnek, H. P., 5 , 57, 58, 72 Molinari, A., 90, 107, 164, 167, 169, 222,299 Mordwiec, A,, 82, 83, 95, 167 Mori, T., 232, 299 Moulinec, H., 173, 234, 256, 260, 26 1, 300, 301 Murat, F., 230,233,236,297 Murtha, S. J., 121, 167

N Nachbar, W., 73 Nakamura, T., 63, 74 Neale, K. W., 121, 169 Nebozhyn, M. V., 242,249,271,289,300 Needleman, A., 79, 80, 82, 90, 102, 163, 167, 168, 173,245,274,296,302 Neiland, V. Ya., 320, 416 Neishtadt, A. I., 407,416

423

Author Index Nemat-Nasser, S., 80, 168,228,300 Nemeth, M. P., 4, 74 Neumann, P., 81,82, 84, 165, 167 Nguyen, Q. S., 276,278,297,298 Nishimura, T., 121, 150, 165, 168 Nishioka, M., 319, 416 Nour Omid, B., 62, 74

0 Ogden, R. W., 11I, 167 Ohtani, S., 121,165 Olson, T., 192, 254, 300 Onat, E. T., 87, 167, I68 Ortega, J. M., 3,45,46, 74 Ortiz, M., 80, 164 Otte, H. M., 91, I67

P Pan, J., 90, I67 Panchanadeeswaran, S., 81,163 Papanicolaou, G., 185, 295 Park, K. C., 58, 74 Parks,D. M., 102, 109, 110,163,164,167 Patoine, A,, 385, 416 Paton, N. E., 167 Peirce, D., 79, 80, 82.90, 167, 168 Peridier, V. J., 366, 416 Perrin, G., 245,299 Peters, M., 150, 167 Phan-Thien, N., 235, 236,299 Phillipe, M. J., 150, 151, 168 Pian, T. H. H., 142, 169 Piehler, H. R., 150, 169 Pillinger, I., 80, 169 Ponte Castafieda, P., 174, 190-193, 195, 200-202,205,206,208,210,214-216, 218-220,224,225,227,231-233, 238-242,244,245,247-249,251,252, 254-257,261,262,265,269-271,274, 275,289,290,291,295,296,298-302 Popov, S. P., 324,361,417 Pospiech, J., 81, 165, 167 Potier-Ferry, M., 3, 63, 72, 73 Prantil, V. C., 87.93, 108, 109, 112, 168 Prandtl, L., 304, 315

Q Qiu, Y. P., 2 13, 239, 301

R Ramazanov, M. P., 319,340,415 Ramm, E., 62, 72, 74 Rankin, C. C., 4,5, 15, 41,42,47,53, 56,62, 64-67,70, 74-76 Raphanel, J. L., 79, 108, 109, 168, 169 Rashid, M. M., 80,93, 168 Rauscher, G. P., 167 Reed, H. L., 328,33 1,416 Reid, W. H., 345,414 Reissner, E., 61, 74 Reuss, A,, 186,301,304,315 Reynolds, G. A,, 318,417 Rheinboldt, W. C., 3, 9,45, 46, 52, 74 Rice, J. R., 90, 167, 276, 302 Richmond, O., 300 Rifai, M. S., 62, 75 Riks, E., 3-5,9, 15,41,42,45,47, 51-54, 56, 64-67, 74, 75 Roe, R. J., 87, 168 Rollett, A.D., 87, 166 Royden, H. L., 31 1,315 Ryzhov, 0. S., 32G-323, 325-328, 330-334, 336-339,341-346,348,349,351,352, 357,361,366,371,376-378,380,383, 385,389,393,397,403,404,406-41 1, 414-417 S Sachs, G., 108,168, 186,301 Saenz, A. W., 407,415 Salemo, G., 3, 73 Salvadori, A,, 314,315 Sam,D. D., 87,168 Sanchez-Palencia, E., 185, 301 Sani, R.L., 119,164 Sansour, C., 62, 75 Sargent, L. M., 318,321,326,415 Saric, W. S., 318, 328,331,416,417 Sarma,G.B., 80, 109-111, 120, 121, 127, 141, 142, 148,164, 168 Savenkov, I. V., 321,328,333,334,416 Schaeffer, D., 18,63, 73, 75 Scheurle, J., 407, 415, 417 Schlichting, H., 318,417 Schoenfeld, S. E., 168 Schubauer, G. B., 318,321,326,417 Serghat, M., 15 1, 168 Seydel, R., 3,9,45,47, 51, 75 Shih, C. F., 167 Shtrikman, S., 174, 187, 230, 298

Author Index

424

Sidoroff, F., 102,169 Simo, J. C., 62, 75,96, I68 Slutsky, S., 244,296 Smelser, R. E., 243, 301 Smith, C. R., 366,414 Smith, F. T., 318, 320-323, 327, 328, 330, 332,336338, 341-346,366,377,380, 387,389,404,407,415417 Smyshlyaev, V. P., 214,301 Smyth, N., 323,386, 415 Spitzig, W. A,, 244, 301 Stames, J. H., 4, 67, 74 Stegun, I. A,, 351,381-383,413 Stehlin, P., 54, 75 Stein, E., 80, 168 Stein, M., 6, 55, 75 Steinmann, P., 80, 168 Stern, P., 62, 72 Stewart, P. A,, 318,321,417 Stewartson, K., 320,328-330,417 Stolz, C., 232, 233, 247, 248, 295, 298 Story, J. M., 121, 167 Stuart, J. T., 318,417 Sturgess, C. E. N., 80,169 Suchy, H., 63, 75 Supple, W. J., 63, 75 Suquet, P., 173, 174, 180, 182, 184, 185, 192, 193, 197,200,203,206,207,209-21 1, 213,214,216,218,219,227,234, 238-240,245,247,248,254,256,257, 259,260-262,265,271-273.276279. 280,290,296-301 Suresh, S., 173, 274,296 Szepessy, A,, 94,165

T Tabourot, L., 79, 168 Takeshita, T., 87, 91, 151, 169 Talbot, D. R. S., 174, 187, 188, 192,205,215, 222,239,240,247,248,271,301,302 Taliercio, A,, 185, 260, 297 Tanabe, A,, 150,168 Tanaka, K., 232,299 Tandon, G. P., 212,262,302 Tani, J., 319,417 Taylor, G. I., 173, 186,302 Temam, R., 280,297 Teodosiu, C., 79, 102, 168,169 Terent’ev, E. D., 323, 328, 331, 332,376, 378, 380,383,416

Thompson, J. M. T., 1I , 23, 75 Thompson, P. F., 79,169 Thornburg, D. R., 150,169 Thurston, G. A., 54, 75 Tidstrom, K. D., 318,321,326,415 Timofeev, S. V., 333,334,416 Tokuda, M., 80,165 Tome, C. N., 107, 151,166, I69 Tong, P., 142, 169 T6th, L. S., 167 Tresca, H., 304, 312,315 Troger, H., 63, 75 Tvergaard, V., 173, 245, 274, 275, 302

U Uetani, K., 63, 74

V Van Bad, A., 80,169 Van der Burg, M. W. D., 245,302 Van der Giessen, E., 93, 121,169,245,302 Van Dyke, R. T., 121,164 Van Houtte, P., 80,93, 108, 109, 151,168, 169 Van Keulen, F., 62, 72, 76 Van Tiel, J., 302 Vandepitte, D., 4, 41, 75 Voce, E., 91,169 Voigt, W., 186,302 Vu Quoc, L., 96,168 W Wagner, F., 150, 151,168 Wagner, W., 5 I , 76 Wagoner, R. H., 80,169 Walker, J. D. A., 366,414,416 Walpole, L. J., 228, 288,302 Warn, T., 385,416 Waters, W. A,, Jr., 67, 74 Weber, G. G., 102,164 Weiss, R., 63, 75 Weng,G. J., 212,213,239,262,301,302 Wenk, H.-R., 80,81,87,89,91, 107, 120, 151,164, 166,169 Wienecke, H., 173,296 Williams, J. C., 167 Williams, P. G., 320, 417 Willis, J. R., 174, 184, 187, 188-192, 205, 214,215,222,228,229-233,235, 238-240,247-249,252,256,262,269, 270,27 I , 295,297,298,300-302

Author Index Wriggers, P., 51, 76 Wu, P. D., 121, 169 Wu, T. Y., 323, 324, 380, 385-389, 392, 414, 415,417 Wu, X., 318,414 Wundrow, D. W., 318,417 Wygnanski, I., 408,413,417

Y Yang, W.H., 309,311,313,314,315 Yao, Z., 80,169 Yates, G. T., 324, 380,415 Yeates, L. G., 328,417

425

Young, M. J., 79,169 Young, R. D., 4,41, 76

Z Zaidman, M., 239, 256, 261, 302 Zaoui, A., 108, 169, 173,212,232, 233, 247, 248,262,296,298 Zarkades, A., 150,166 Zhang, Y., 87,169 Zhou, Y., 121, 169 Zhuk, V. I., 320, 321, 323, 324, 328, 336338, 346,361,380,389.41 7 Zilberman, M., 408,413,417 Zonker, H. R., 121,167

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Subject Index

A

Artificial diffusion, 94 modification, 94 Associated optimality conditions, 208 Asymptotic analysis, 350, 352, 354, 380 Asymptotic expansion, 350,352 Asymptotic method, 43 Asymptotic theory, 341 Atmospheric phenomena, 348, 386 Atmospheric processes, 324 Atmospheric science, 356 Attraction, 25 Average strain, 286 Axial compression, 68 Axial stress, 260 Axis of transverse isotropy, 288 Axisymmetric cell, 271, 272 Axisymmetric deformation, 288 Axisymmetric deformation mode, 244

Absence of stability, 25 Absolute bound, 308 Adaptive parametrization, 9 Adjustment sublayer, 323,341,378-380 Admissible velocity functions, 3 14 Affine displacement, 182 Affine transformation, 348, 378, 385, 387, 405 Aggregate size, 134 Algebraic soliton, 346, 347, 410,411 Aligned disks, 248 ellipsoidal inclusions, 274 fibers, 204 spheroidal pores, 245 Alpha-shaped separatrix, 406 Amplitude of forcing, 386 Anglehxis representation, 84, 93 Anisotropic behavior, 80 Anisotropic composites, 205, 247 Anisotropic constituents, 193 Anisotropic linear composites, 292 Anisotropic material, 178 Anisotropic material with special symmetry, 288 Anisotropic matrix modulus tensor, 24 1 Anisotropic matrix phase, 237 Anisotropic phase, 293 Anisotropic plastic response, 123 Anisotropic single-crystal grains, 193 Anisotropic tangent moduli, 273 Anisotropy, 106, 107, 154, 293 Arbitrarily weak disturbing obstacle, 35 I Arbitrary phase contrast, 220 Arc-length continuation, 15

B Background perturbations, 345, 383,410 Background subharmonic modes, 3 18 Background-perturbation level, 382 Backlund transformations, 381 Balance laws, 141 Band-shaped domain, 400 Basal strength, 131 Basal systems, 91 Bauschinger effect, 280 BCC (body-centered cubic) metals, 8 1 BDA (Benjamin-Davis-Acrivos) equation, 321,328,340,409 forced, 350 BDA-KdV solitons, 413 BDA model, 321,323,326,344, 345,380,407 forced, 366, 388 BDA one-periodic solution, 343, 344 427

428

Subject Index

BDA solitary waves, 410 BDA soliton, 355, 357, 360, 383, 395 BDA soliton-emission process, 324 BDA system, 324,403,409 forced, 3,325,385, 389-393, 396, 397, 399,400,402,408,413 Benjamin solution, 339, 345 Beran third-order bounds, 240, 249 Bifurcation, 5, 13, 14, 357, 361, 372, 390, 392, 393, 395-397.413 branch, 17 point, 2,4,5,11,15,17,21,24,41,42,50, 52-54,63,65 prediction method, 70 problems, 61 Bimodal surface, 260,261 Birth of solitons from erratically distributed signals, 413 Blasius boundary, 362 layer, 321, 322, 326,332, 333, 335, 345, 366,388,407 Body-centered cubic (BCC) metals, 81 Boundary conditions and averages, 182 Boundary layer, 319,320,348,366,377 2D, 404 equations, 379 flows, 409 motion, 410 oscillations, 408 3D, 328,331,376-378,380,384-387, 404,407 stability, 379 cross-flow, 331 environments, 389 equations, 389 equations of Prandtl, 337 flow, 323,325,326,328,345,348,371, 388,409,410,413 nonlinear stability theory, 324 oscillations, 381 solitons, 319, 335 study, 356 theory, 320,325, 329 problem, 224 Bounded stress, 304 Bounds, 214,294 absolute, 308 classical Hashin-Shtrikman bounds, 191 classical bounds of Voigt and Reus type, 185

via piecewise constant moduli, 205 via piecewise constant polarizations, 189 Branch switch, 52-54 Branching diagrams, 17, 67 Brass component, 141 Bubnov-Galerkin approach, 95 Buckling, 2, 53 analysis, 1, 52 experiments, 6, 35 load, 51.64 mode, 39,63,65,66, 70 motion, 6,58,60 pattern, 55 process, 58, 68 Budiansky, 2 Bulk, 287 modulus, 226, 236 modulus d r ) ,208

C Carbon composite cylindrical shells, 67 Cauchy stress, 100, 105, 106, 114, 175 Cauchy-Schwarz inequality, 304, 305 Cavities, 37 1 Centrifugal forces, 33 1, 332 Characteristic time, 386 Chopped fibers, 274 Classical minimum energy principles, 174 Classical secant method, 262, 264, 266, 273, 29 I , 294 Classical variational principles and effective potentials, 183 Clustered bifurcations, 63, 69 Cnoidal oscillations, 40 1 Cnoidal waves, 381-383,405,407 Cold working, 121 Colinearity condition, 305 Collapse, 4,68 Complementary energy representation, 195 Compliance tensor, 210 Composite ellipsoids, 233 Composite materials, 172 Composite sphere, 233, 247, 254, 258 Composite-sphere (CS) types of microstructures, 244 Composites, 27 I with elastic ideally plastic phases, 186 with isotropic phases, 206 Compound BDA-KdV systems, 326,412,413

Subject Index Compression (ND) axis, 112,136,145,150 Computational optimization techniques, 313 Concave dual function, 198, 281,282 Concave function, 193,281 Concavity hypothesis, 193,195, 214,215 Conductivity, 227 Conjugate gradient method, 144 Conservation laws, 338,348,381,385,409 Constituent phases, 172,220 Constrained hybrid,109-112, 120,127,129, 130,133,136,145,147,150, 156 Continuation method, 3,5,48 Contrast between constituent properties, 216 Controlling similarity parameter, 357 Conventional stability theory, 345 Convergence characteristic, 46 Convex dual function, 280,283 Convex function, 200,280-282,308,310 Convex potential, 178 Convex surface, 26 Convex yield functions, 304 Cracked solids, 240 Cracks, 287 aligned, 240 randomly oriented, 240 Creep, 172,178,194,214,227 exponent, 270 Creeping solids, 245 Critical load, 2,69 Critical equilibrium state, 24 Critical point, 5,34 unstable, 59, 65 Critical state, 24,33,36-39, 50-52,65,70 Crossflow, 329,377 disturbance, 380,407 instability, 376 jetlike behavior, 376 motion, 404 Crossflowdisturbance generation, 385,386 Crystal anisotropy, 144 Crystal, 90 deformation rate, 90, 109 stress, 90, 105, 109 Crystal orientation, 78,80,81,93 distributions, 86 velocities, 96 Crystal symmetries, 84 Crystal viscoplastic stiffness, 90 Crystalline materials, 78,178,283 Crystallographic planes, 78

429

slip, 78,88, 102 texture, 78,81, 86,88,126 Cyclic loading, 280 Cylindrical elastic particles, 271 Cylindrical shells in compression, 6 Cylindrical voids, 239

D Damage, 173 Damping, 38,42,56,59 Dead-weight type loading, 54 Deep water phenomena, 348 Deformation, 67,87.93,96,97,99, 113, 152,

156,173 heterogeneity, 79 history, 126,129,136,144 mechanism, 88 Deformation theory of plasticity, 273,275,276 Degenerated attractors, 59 Delaminations, 72 Dent, 325,354,373-376 Depression, 359 area, 355 region, 411 zone, 363,412 Depression-region oscillations, 412 Destruction dependencing on the amount of energy freed, 55 Deviatoric plastic response, 107 Diamond, 3I 1 Diffusional creep, 88 Dilute concentrations, 232 Direct scatering, 381 Discrete orientation representations, 96 Disk density parameter, 248 Disks aligned, 248 randomly oriented, 249 Dislocations, 88 Displacement-thickness, 350,356,363,369,

374,392,398,402 ampIitude, 401 distribution, 354,368,372,376,405 evolution, 398 maximum, 364,365 pulsations, 400 variations, 397,398,402 Dissipation potential, 254,276,295

430

Subject Index

Disturbance amplitude, 325 excitation, 397 field, 391, 395 generation, 357, 393 by cavities, 37 1 magnitude, 344 pattern, 383 Disturbance-emission process, 353, 368 Disturbance-excitation process, 372, 374, 386, 390,413 Disturbance-generation process, 388,402, 410 Disturbance-radiation process, 325, 349, 399 Downstream advancing wave system, 352 Downstream- and upstream-propagating wave systems, 349 Dual convex potentials, 284 Dual norms, 308-3 10,312,313 of vectors, 304 Dual potentials, 185 Dual variational principle, 201 Duality, 303, 310 theorem, 313, 314 Ductile materials, 303 Duration of buckling motion, 56 Dynamical systems, 361 theory, 403

E Earing, 121 Effective compliance tensor, 246 deformation rate, 129 energy-density function, 295 flow stress, 243, 253, 258, 267 modulus tensor, 216, 225, 228, 238, 247, 287 potential, 174, 220, 235, 284 shear modulus, 254,263 strain, 291 strain energy, 184, 207 stress, 213 stress-strain relations, 208, 271, 275 tangent stiffness, 293 yield function, 256 Elastic and plastic strains, 280 Elastic composites, 187 Elastic particle-reinforced composites, 27 I Elastic stability problems, 3 Elastoviscoplastic formulation, 114, 121

Elementary bifurcation theory, 5 Ellipsoidal grains, 234 inclusions, 232 voids, 239 Emission process, 366 End-shortening control, 35 Environment atmospheric, 325 oceanic, 325 Equilibrium, 100 path, 24 point, 65 surface, 41, 43 Erratic pulsations, 403, 412 vigorous, 408 Erratically distributed signals, 408 Esslinger experiments, 69-7 1 Euler angle, 8 I , 98 Eulerian axes, 1 I 1 Eulerian mesh, I29 Even-order bounds, 236 Exact dilute (D) expression, 251 Exact effective potential, 21 6, 21 9 Exact variational representation, 199 Excess pressure, 334 Existence of stability, 25 Explicit methods, 58 Exponent of nonlinearity, 290 Extremal surface, 185, 261

F Face-centered cubic (FCC) symmetry, 81, 85, 270 Fiber-reinforced composites, 227, 233, 25 I , 256,260,27 1,289,294 Fictitious linear heterogeneous solid, 199 Finite contrast, 174 Finite time-dependent disturbances, 21 First bifurcation, 355-359 First KdV soliton, 393 Flash-spike, 327 Flat plate, 318, 328 Floquet approach, 3 I8 Fluid-saturated porous materials, 241 Foam, 326,412 Forced BDA equation, numerical solution, 350 Forced BDA model, 366,388 Forced BDA system, 3,325, 385, 389-393, 396,397, 399,400,402,408,413

Subject Index Forced KdV equation, 386 Forced KdV evolution system, 379 Forced KdV model, 389,403 Forced KdV system, 389 Forced oscillations, 346, 384 Forced solitary waves, 323 Forcing function, 409 Forcing source, 386 Forming processes, 80, 121 Four-deck structure, 377 Four-dimensional quatemion parameterization, 82 Fourier components, 322 decompositions, 344 modes, 342 series, 322, 340 transform, 349,350 Frkchet derivative, 212 Free oscillations, 323, 339, 381 Free-oscillation frequency, 407 Frictionless kinematical constraint, 27 Fundamental bifurcation equation, 17 Fundamental region, 84,93,94,96 Fundamental wave, 327

G General form of the potentials, 179 General isotropic microstructures, 254 General nonspherical pore shapes, 245 Generalized self-consistent scheme, 272, 274 Generalized Voce form, 91 Global equilibrium state, 43 Gradual evolution, 393 of disturbances, 361 Grain boundaries, 142 Grain compliances, 210 Grain interactions, 140 Grain orientations, 173 Grain shape, 141 Granular type of microstructures, 192, 233, 234, 267 Gravity field, 387,404 Growing-wave amplitudes, 3 18 Gurson model, 247

H Hamiltonian chaos, 407 Hamiltonian form, 361

43 1

Hamiltonian function, 405 Hamiltonian system, 407 Hardening, 136 behavior, 154 geometric, 136, 137 Harmonic oscillations, 340 Harmonic source, 403 Harmonic wave, 404 Hashin-Shtrikman (HS) bounds, 174, 192,214,228,231,233, 238-240,247,254,256,275,293,294 linear, 174, 247 lower, 258,261,263,264, 267,269,273 upper, 243,254, 258 upper and lower, 236,266 variational, 242, 244 estimates, 232, 234, 236, 241, 247-250, 254,265 procedure, 255 variational principles, 174, 187, 214, 218, 229,23 1,294 HCP (hexagonal close-packed) crystal, 81, 85, 144,156 Hem-Stolz-Zaoui upper bound, 254,269 Heterogeneous deformations, 80 High-amplitude negative spike, 335 High-amplitude oscillations, 412 High-amplitude periodic oscillations, 410 High-amplitude wave packet, 333 High-temperature creep of metals, I77 Higher-order bounds, 174, 214, 236 random composites, 235 Hilbert integral, 347, 361,409 Hill lemma, 183, 184, 217, 285 Hirota function, 381 Holder inequality, 197, 203, 304, 305, 307-309,3 13 generalized, 303, 308, 310, 312 Homochoric scaling, 98 Homogeneous BDA equation, 324,345 Homogeneous BDA model, 347 Homogeneous BDA system, 338 Homogeneous KdV equation, 381,383, 384, 385 Homogeneous nonlinear reference material, 216 Homogeneous quasi-convex reference material, 215 Homogeneous reference material, 187 Homogenization method, 172

432

Subject Index

Hump, 325,333,334,349,352-355,351,360, 366,368,370,373,390,408 crest, 356, 360, 363,364,365,369-371, 392,397404 Hybrid element polycrystal, 140, 141, 142, 144, 145, 148, 150, 151 Hydrodynamic stability theory, 322 Hydroforming, 121, 155 Hydrostatic strain, 242 Hyperbolic conservation laws, 94

I

Ideally plastic composites, 173, 175 Ideally plastic polycrystals, 173, 271 Imperfection, 65, 67 sensitivity, 2 Incipient motion at unstable points, 38 Incipient transition time, 353, 354, 357, 372, 388,392,393 Inclusion phase, 230 Inclusion shape, 288 Incompressibility constraint, 144 Incompressible matrix material, 287, 289 Incompressible power-law materials, 272 Incremental convection scheme, 95 Incremental elastoplastic model, 274 Incremental composite model, 175, 268,273, 279 of Hutchinson, 270 Incremental version of self-consistent method, 173 Inextensible deformation mode, 109 Infinitesimal harmonic oscillations, 41 1 Infinitesimal harmonic waves, 41 1 Infinitesimal waves, 383 Inhomogeneous BDA model, 346 Inhomogeneous BDA system, 338 Inhomogeneous KdV system, 384 Initial boundary layer, 378 Instantaneous displacement thickness, 330-332,441 distributions, 352, 358, 361, 389, 395 oscillations, 321 Instantaneous disturbance patterns, 355, 359, 362,368,373,391,395,401,412 Instantaneous wave patterns, 350, 353, 390 Intense pulsations, 375, 376

Interaction law, 330-332,335,377 Intercrystal boundaries, 142 Intermediate adjustment sublayer, 336, 337, 341,377,378 Internal atmospheric solitary waves, 324 Internal gravity waves, 324 Inverse scattering, 381 transforms, 323,361 Lax pairs, 338 Inviscid governing equations, 336 Inviscidinviscid interaction process, 378 Inviscidinviscid interaction theory, 388 Inviscid wave motion, 338 Isochoric plastic deformations, 142 Isothermal conditions, 100 Isotropic composite sphere assemblages, 254 Isotropic composites, 174, 215, 226, 254, 292 3D, 252 rigidly reinforced, 247 Isotropic constituents, 192, 201, 218, 220, 235, 237,253,282 Isotropic hardening, 276, 279 Isotropic linear comparison composites, 203 Isotropic microstructures, 187, 258, 267 Isotropic nonlinear matrix phase, 246

J Jacobian elliptic function, 382 Jet-like crossflow disturbances, 323 Jet-like near-wall crossflow disturbances, 323 J2 deformation theory of plasticity, 177

K K-regime, 3 18 K-route, 326 K-route to transition, 321, 322, 340, 341 KdV (Korteweg4e Vries) disturbance-generation process, 389 KdV equations, 322, 324, 328,409 KdV generation process, 408 KdV model, 323,326, 391,403,407 KdV radiation process, 401 KdV solitary waves, 323, 395,410 KdV soliton, 381, 383, 396 first, 393 KdV systems, 323,376,380,408,409 Kirchhoff-Love assumptions, 61 Koiter asymptotic theory, 3

Subject Index L Laminar boundary layer, 339 Laminar-turbulent transition, 326, 413 process, 346 Laminates, 200, 277 Lattice orientation, 86, 88, 136 rotations, 96 spin, 90, 93 Lax pair, 323,381 Level sets, 307 Limit analysis, 256 Limit cycle, 361 Limit points, 5, 1 I , 12, 15, 16, 20, 21, 24, 34-37,50,52,60 Limit-cycle-type loop, 375 Limit-cycle-type oscillations, 325 Limit-cycle-type process, 370 Limiting conditions, 332 Limiting dome height tests, 155 Linear comparison composite, 174, 192, 194-196, 199, 206208,215,269,294 polycrystal, 210 porous material, 241 solid, 199 Linear elastic composites, 172, 213, 225, 228, 247 Linear elastic inclusions, 272, 280 Linear Hashin-Shtrikman bounds, 174, 247 Linear heterogeneous comparison solid, 195, 220 Linear monochromatic motion, 327 Linear porous material, 238 Linear self-consistent estimate, 240 Linearized buckling analysis, 43,49 Load-carrying capacity, 22,40 Local potential, 199 Local problem, 181, 182,290 Local quantities, 172 Local roughness, 349, 362,385, 389, 390,397, 400,401,411 Local roughness shape, 347 Local secondary high-frequency (LSHF) instability, 3 19 Local streamwise, 329 Local stress and strain fields, 182 Localized deformation modes, 244, 252 Loss of stability, 22, 24, 34, 58 Lower bounds, 191,214,232,246

433

Lyapunov criterion, 22 Lyapunov-Schmidt-Koiter reduction of equilibrium equations, 18, 19

M Macroscopic deformation rate, 109, 110, 136, 154 Macroscopic scales, 106 Mass, 346, 358, 367, 372, 394 conservation law, 385 of disturbing obstacle, 348 pumping, 352 Mel’nikov function, 406 Metal-matrix composites, 172, 27 1-274, 276, 295 Metal-forming processes, 134, 295 Method of successive linearizations, 43 Microscopic scale, 106 Microstructure evolution, 295 Milton parameters, 249, 255 Minimax (duality) theorems in plasticity, 305 Minimax formulations of plasticity problems, 304 Minimum energy principles, 185, 235 Minkowski norms, 304,305,307,308,309 Mode jumping, 5,55,62,65,71, 72 experiment, 6 mechanisms, 72 problem of Stein, 64 procedure, 68 Modulated oscillatory motion, 355, 363 Modulated oscillatory tongue, 355, 360 Modulated strong pulsations, 398 Moment of a mass, 386 Monochromatic TS wavetrain, 335 Monotonic loading, 276, 279 Mori-Tanaka estimates, 232 Morphologically representative patterns, 232, 233 Multiparticle effective field method, 213,239 Multistructured boundary layers, 320

N N-breakdown, 318 N-route to transition, 318, 321 Narrow flashes, 3 19 N m w high-amplitude-spike zone, 377 Narrow negative spike, 335 Navier-Stokes equations, 330

434

Subject Index

Near wake behind the trailing edge of a flat plate, 320 Near-wall sublayer, 379 Near-wall viscous sublayer, 335,337, 338, 340,341,379,380,389 Negative flash-spike, 327 Neighborhood compliance assumption, 110, 111 Neo-Eulerian parametrizations, 82 Newtonian viscous material, 177 No-long-range order hypothesis, 228 No-overlap hypothesis, 232 No-slip conditions, 332, 335,337,377, 379 Nonconvex function, 3 11 Non-Euclidean model, 304 Nonhydrostatic loading of dry pores, 242 Nonlinear composites, 171, 191, 192, 220, 237 with anisotropic phases, 198, 205 with isotropic phases, 193, 208 with random microstructures, 294 Nonlinear conductivity, 227 Nonlinear cross-flow, 380 eigenmodes, 323, 381 Nonlinear elastic models, 294 Nonlinear dielectric composites, 190 Nonlinear disturbances, 335 Nonlinear eigenmode, 345 Nonlinear Hashin-Shtrikman bounds, 227 Nonlinear homogenization procedures, 235 Nonlinear hydrodynamic stability theory, 328 Nonlinear polycrystals, 210 Nonlinear solitary-like wavetrains, 323 Nonlinear soliton stage, 323 Nonlinear wave equations, 335 Nonlinear wave generation, 348 Nonlinear wave pattern, 354 Nonlinearly viscous constitutive models, 294 Nonmonotonic loadings, 276 Nonnegative dissipation, 303, 3 12 Nontrivial lower bounds, 191 Nonuniform background perturbations, 388 Nonuniform elevation, 396 Nonzero background perturbations, 322 Normality, 303, 304, 310 Normality relation, 307, 308 Normalized phase velocity, 345

0 Obstacle crest, 400 Oceanic events, 324 Oceanic phenomena, 348,386

Oceanic sciences, 356 One-periodic and soliton solutions, 38 1 One-sided bounds, 191, 214, 233 Onset of random elements in fluid motion, 413 Operator norms, 31 1 Optimal linear comparison solid, 199 Optimality conditions, 282, 283 Order two statistical information, 174 Orientation, 86 distribution, 94 conservation equations, 93 Oscillation, 352, 358, 393 coils, 361, 363, 397,402404 cycle, 319, 322, 326, 341-343, 360, 366, 398,407 parameters, 379 pattern, 348, 361, 386, 401 2D, 377 process, 361 motion, 412 downstream, 357 Oscillatory tongue, 390, 391,401,408,411 Oscilloscope trace, 319,343 Overall constitutive law, 292 Overall energy, 284 Overall flow stress, 269 Overall hardening, 280 Overall isotropy, 259 Overall stress-strain relation, 291

P Pairing, 306 Panel buckling, 63 Parabolic boundary-layer equations, 320 Parametric-resonance amplification, 3 18, 321 Parametric-resonance type, 3 18 Particle aligned, 275 dispersed randomly, 275 elastic, 275 shape, 274 spheroidal, 275 Particle-reinforced composites, 233, 256, 259 Particle-reinforced metal-matrix composites, 275 Particulate microstructures, 23 I , 233, 234, 236,247 Particulate type of microstructure, 192, 230, 247,258 Partitioning assumptions, 106, 107, 130, 132, 141

435

Subject Index Partitioning rules, 107, 109, 112, 151, 154, 156 Path-following method, 6,43, 45, 47,48, 49, 52, 59,60,69 Peaky-type pulsations, 365, 366 Perfect disorder, 234 Perfect plasticity, 252, 259 Perfect plate, 63, 65 clustered bifurcations, 64 Perfectly plastic limit, 270 Periodic forcing, 407 Periodic oscillations, 380 Periodic process, 363 Perturbation, 27, 29,36,38, 40, 43, 59 approach, 47 expansion, 227 forces, 37, 38 method, 43, 48 theory, 3, 61, 64 Perturbing roughnesses, 366 Phase-average strains, 222, 246 Phase plane, 67 portrait, 65 Phase velocity, 341,347, 360, 395, 396 Phenomena atmospheric, 348, 386 deep water, 348 oceanic, 348, 386 shallow water, 386 Piecewise constant linear comparison composite, 21 1 Piecewise constant polarization fields, 218, 286, 287 polarization Hashin-Shtrikman estimates, 232 shear modulus, 254 Pitchfork bifurcation, 20, 21 Planar deformation, 79 Plane strain compression, 96, 97, 112, 138, 141, 144, 145 Plane strain transverse shear, 242, 250 Plane stress, 305, 311, 313, 314 Plastic composites, 258 Plastic dissipation function, 185 Poincare map, 406,407 Point attractor, 36 Point-to-set map, 31 1 Poiseuille flow, 3 19 Polarization field, 188, 189, 218, 232 Pole expansions in a complex plane, 323, 338, 38 1

Polycrystal, 156, 182, 192, 201, 210, 234 plasticity, 77, 106, 126, 152, 156 theory, 78, 80, 86 Polycrystalline aggregates, 193, 215, 234 Polycrystalline metals, 78, 86, 91, 126, 140 Polycrystalline solids, 87, 99, 173, 269 Polyphase systems, 106, 110 Ponte Castaiieda procedures, 192, 215 hybrid, 192,215 Porous materials, 175, 213, 237 with incompressible phases, 239 Postbuckling behavior, 2 , 4 , 3 2 Postcollapse state, 68, 7 1 Potential energy functional, 33 Potential flow field, 320 Potential velocity field, 328 Power law, 177 composites, 174, 209, 267 constituents, 192, 202 creep, 269 exponent, 244 materials, 191, 194, 197, 202, 251, 253, 263,265,271 polycrystals, 204, 21 1, 269, 270 porous materials, 242-244 Prandtl approach, 320 equations, 330, 335, 341 Predetermined displacement thickness, 379, 389 Primal norm, 304,308,309.3 12,313 Primal-dual relation, 304 Prismatic and pyramidal slip systems, 144 Projection operators, 109 Projection tensors, 226, 287 Propagation, 335, 360 speed, 396,411 Pseudo-spectral method of Burggraf, 350 Pulsation crest, 375 Pulsation cycles, 366, 400 Pulsation process, 374 Pulse-mode disturbance, 345 Pumping, 352 Purely deviatoric loading, 242, 243 Pyramidal slip, 112, 121 system, 97, 131, 147

Q Quadratic-to-quartic-type nonlinearities, 3 18 Quantitative texture analysis, 87 Quasi-conservative structure, 7

436

Subject Index

Quasi-steady peak, 390 Quasi-two-dimensional region, 344

R Radiation, 400 Radiative damping, 324 Ramberg-Osgood model, 177 Ramp flow, 386 Ramp slope, 388 Ramp-type flow, 387,388 Ramp-type obstacle, 392 Random composites, 228, 231,233 Random disturbances, 403 Random microstructures, 173 Randomization, 403 Randomly isotropic configurations, 261 Randomly oriented spheroidal particles, 252 Rate dependence, 154 Rate-dependent single-crystal behavior, 79 Rayleigh damping, 8 Reissner-Mindlin assumptions, 61 Relaxed constraints, 108, 11 1, 120, 126 Representative volume element, 181 Repulsion, 25 Resonant-triad interaction, 318 Reuss, 258,267,270 bound, 192,215 lower bound, 252, 259 Rigid disks, 248,288 Rigid ideally plastic composites, 192, 204 Rigid ideally plastic constituents, 204, 268 Rigid ideally plastic materials, 185, 204 Rigid inclusions, 253,268 Rigid perfectly plastic porous materials, 245 Rigidly reinforced composites, 175, 246, 247 Rigorous bounds, 294 Rodrigues space, 84 Rolling, 80, 81.97, 105, 121, 126, 133, 142, 155 Rolling (RD) direction.112, 145, 150 Rotating disk, 380 Roughness, 358 mass, 386

S Sachs assumption, 141 Saddle point theorem, 196 Scaling, 377 Secant, 175, 271 compliance tensor, 180 estimate, 269, 271-273

method, 173, 21 1, 213, 262, 267, 273, 279, 290,292 classical, 262, 264, 266, 273, 291, 294 models, 175 moduli, 176, 193, 199, 294 procedure, 212 modified, 294 tensor, 212, 217 Second bifurcation, 366-370, 403,408 Second moment, 285,286 of strain, 212 of stress, 213 Second-order bounds, 227 Second-order estimates (SOE), 220, 226, 241, 243,245,249,25 1,252,256,269,294 Second order in a contrast, 224, 225 Second-order moment of a strain, 207 Second-order procedure, 174,262,266 Second-order theory, 216,250, 267 of Ponte Castafieda, 225 Self-consistent estimates, 174, 200, 233, 240, 242,249,250,268 generalized, 214 Self-consistent scheme (SC), 173, 262, 267, 27 1 generalized, 272, 274 Self-excited oscillation, 341 Self-excited wave, 341 Self-induced pressure, 33 1, 332 Seminorm, 308 Separation-bubble breakdown, 389 Separation from a smooth surface, 320 Separatrix loop, 405 Sequentially laminated composites, 200, 255 Shallow water channel, 323 phenomena, 386 wave, 377 Shape memory polycrystals, 215 Sharp upper bound, 305 Sharpness condition, 306, 308, 312 Shear, 68, 236 along fibers, 288 flows, 319,320 strength, 200 transverse to fibers, 288 Sheet formability, 121 Shell modeling, 61 Shock-capturing techniques, 94 Shock-wavehoundary-layer interaction, 320 Short-length wiggles, 322 Short-scaled large-sized flash-spike, 327

Subject Index Short-scaled wiggles, 41 1,412 Short-wavelength oscillations, 332 Short zone of transitional-type pulsations, 358 Similarity law, 325, 348,385, 386 Similarity parameter, 325, 349, 354, 357, 365, 372,386,388-390, 393,394,398,399, 401,403,408,411 Simple shear, 257, 259 Single crystal, 89, 102, 178 Singular perturbation technique, 407 Skew-symmetric bifurcation, 20, 21, 34-37, 60 Skew-symmetrical waves, 71 Skin-friction distributions, 322 Slip bands, 244 Slip directions, 91 Slip system, 79, 84, 88,90,91,99, 136, 144, 283 activity, 80 hardness, 97 normals, 91 potentials, 204 shear rates, 89 Slipline method, 3 I3 Slow disturbance generation, 392 Slow disturbance-generation process, 389 Slow solitary-wave radiation, 352 Slow soliton, 352, 357 Slow soliton emission, 354 Small-amplitude oscillatory tongue, 358 Small-amplitude pulsations, 357 Small-contrast expansions, 216, 219,225 257, 284 Snap buckling, 4 1 , 56 motion, 70 Solitary-like boundary-layer flow, 407 Solitary-like solution, 384 Solitary-like wave, 317, 324326, 355 emission, 371 evolution, 357 generation, 325 Solitary wave, 357, 358 emission, 356 radiation, 365, 376, 400 Solition stage, 323 Soliton, 319, 321-327, 353, 357, 380, 390, 391,401,403,408,410,412 emission, 323, 324, 365, 388 upstream, 392 process, 323 radiation, 372 upstream, 357 solution, 345, 409

437

Soliton-bearing models, 345 Soliton-bearing systems, 326 Soliton-generation theory, 324 Soliton-like structures, 333, 339 Sound pulse, 334 Sound pulse/local hump interaction, 333 Sound-pulse-pressure distribution, 333 Spanwise coordinate, 332 Spanwise cross-flow, 328 Spanwise direction, 332 Spanwise lengths, 329 Spanwise wavenumbers, 33 1 Spectral decomposition, 287,322, 341, 342 Spherical inclusion, 247, 269, 27 1, 273, 288 distributed with statistical isotropy, 254 Spherical rigid inclusions, 268 Spheroidal inclusion, 253,271,275 in an isotropic material, 286 Spike, 368 formation, 342 generation, 319 soliton, 412 formation, 343 parameters, 342 properties, 339 width, 345 zone, 335, 337, 379 Stability, 16, 22, 25, 26, 55 analysis, 2, 40, 41, 386 at critical states, 29 boundary, 24 point of view, 22 Stable equilibrium state, 36, 60 Stable postcollapse state, 35 Stable static trajectory, 67 Static equilibrium, 42 branches, 4 , 6 path, 47 Stationarity conditions, 206 Stationary estimate, 223 Stationary load, 41 Stationary points, 15-17 Stationary roughnesses, 384 Stationary surface, 386 Statistical homogeneity, 228 Statistical isotropy, 187, 247, 259 hypothesis, 232 Statistically isotropic microstructures, 235, 238,24 1,242,247,249,251,254,257 2D, 251 3D. 251

438

Subject Index

Statistically isotropic power-law composites. 262 Steady boundary layer, 388 Steady cross-flow disturbances, 384 Steady shear flow, 388 Strain energy, 290 functions, 175, 197, 281 gradient plasticity, 214 hardening, 106 heterogeneity, 144 polarization, 189 Stminxoncentration tensor, 225, 29 1 Streamwise flow, 328 Streamwise oscillations, 376 Streamwise velocity, 377 Streamwise wavenumbers, 33 1 Stress-energy functions, 28 1 Stressxnergy potential, 209 Subharmonic periodic orbit, 406 Subharmonic resonance, 407 Supersonic boundary-layer separation, 320 Supersonic external flow, 389 Surface geometty, 386 Swept wing, 380 Symmetric bifurcation pitchfork, 20 stable, 34, 35, 37, 60 unstable, 34,35,37,60 Symmetric normality relations, 3 11 T Talbot-Willis bounds, 174,214 procedure, 174, 192,214,215,238,262, 269 hybrid, 192, 215 variational principle, 187, 192, 214, 270 Tangent moduli, 175, 176,217 anisotropic, 273 of phases, 294 Taylor, 120, 156 assumption, 80.97, 107, 109, 11 I , 112, 136, 141, 144-147, 150, 157 bound, 270 estimate, 270 expansion, 15, 227 factor, 80, 137 formula, 220 hypothesis, 141 model, 268

Texture, 88, 124, 129, 134 analyses, 87 evolution, 96, 97, 105, 137, 140, 147 Theory of elastic stability, 2 of plasticity, 31 1 of solitons, 320 of solitons, 327, 339 Thermodynamic potentials, 276 Thermoelastic composites, 2 15, 228 Thin-walled cylindrical shell, 2 Thin-walled shells, 61 Third-order bounds, 235 Three-dimensional waves, 344 Three-point statistics, 235 Thunderstorms, 324 Titanium, 121, 133, 150 Tollmien-Schlichting (TS) linear eigenmodes, 318 Tongue, 354 Transformation field analysis, 276 Transient behavior of a structure, 38,42, 54 Transient procedure, 59, 71 Transient-type phase, 397 Transition, 318, 321, 339, 346, 366 Transitional boundary layer, 339 Transitional boundary-layer flows, 322 Transitional process, 358 Transverse (TD) direction, 1 12 Transverse isotropy, 227,231,275 Transverse shear, 227, 252,257, 260 Transversely isotropic microstructures, 260 Traveling wave, 345 Tresca norm, 3 12 Triple deck, 326,328, 329, 331,377, 379 approach, 345 scheme, 321, 329, 335, 389 stage, 328,380, 383 structure, 336 theory, 320, 321 TS (Tollmien-Schlichting) wave amplification, 319 TS wavetrain, 340 TS waves (2D), 332 Twinning, 88, 112, 149, 151 Two-dimensional boundary-layer flow, 3 18 Two-dimensional symmetric polycrystals, 269 Two-phase composites, 225, 235, 253, 256, 262 Two-point statistics, 294

Subject Index U Uniaxial compression textures, 150 Unidirectional composites, 261 with transverse isotropy, 256 Uniform strain (Taylor) assumption, 107 Uniform stress assumption, 108, 111, 112, 130, 146 Unstable boundary layers, 317 Unstable buckling, 5 Unstable critical state, 38, 40, 59, 65 Unstable secondary branch, 59 Upper bound, 191,214,232,243 Upstream-advancing solitary waves, 395 Upstream-propagating waves, 401 Upstream soliton, 353

V Variational bounds, 25 I , 252, 268 of Reus, 258,267, 270 of Voigt, 258,267, 270 Variational estimate, 235, 245, 269, 271, 272-275 Variational method,l87, 192, 21 1-213, 220, 253,255,262,263,267,269,27 1,274, 276,279 Variational principle, 174, 195, 197, 198, 236, 285 of Talbot and Willis, 187, 214, 270 Velocity-based viscoplastic formulation, 155 Velocity difference friction model, 128 Velocity oscilloscope, 319, 322,412 traces, 326, 335 Velocity/pressure formulation, 142 Vibrating ribbon, 3 18 Vigorous oscillation, 368, 370 Vigorous peaky-type disturbances, 361 Vigorous pulsation, 356,360, 362-364, 370, 371,392,396400,402,403 modulation, 400 process, 365,404 Viscoplastic approximation, 100, 105, 113, 127, 141 Viscoplastic finite-element formulation, 138 Viscoplastic response, 89 Viscous flow, 320,377 Viscous fluid, 328 Viscous/inviscid interaction, 320, 323, 328, 377 process, 320, 33 1

439

Viscous near-wall region, 335 Viscous shear flows, 318, 380 Viscous sublayer, 338, 366, 377 Viscous tangential stresses, 336, 378 Void growth and coalescence, 97 Void surface, 245 Voigt, 267, 270 bound, 214,268 estimate, 256 upper bound, 243 Volume fraction, 232,258, 259, 261, 267, 269, 272,273,279 Von Karman-Donne11 equations, 61,62 Von Mises, 312 criterion, 253 equivalent stress, 176 norm, 312 rigid ideally plastic material, 177 yield function, 31 I Vortex loops, 318,319,321

W Wall-shear-stress distribution, 333 Water-wave characteristics, 324 Water-wave parameters, 380 Wave-emission process, 35 1 Wave packet, 322, 327 Wave-system evolution, 352 Wave systems, 325,345,357 Wave/vortex interactions, 3 18 Wavenumber harmonics, 321 Weak disturbances, 349 Weak equilibrium equation, 3 14 Weakly inhomogeneous composites, 224,235 Weakly inhomogeneous nonlinear composites, 216 Weakly nonlinear theory, 3 18 Wind-tunnel measurements, 322 Wind-tunnel tests, 318, 319, 321, 326, 341-343.380

Y Yield function, 303,304, 3 1 1, 3 12

z Zinc, 150 Zirconium, 150

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