On the state of pure shear

Similar documents
Lecture notes: Applied linear algebra Part 1. Version 2

Chapter 3 Transformations

Chapter Two Elements of Linear Algebra

Math 102, Winter Final Exam Review. Chapter 1. Matrices and Gaussian Elimination

MAT Linear Algebra Collection of sample exams

Chapter 6: Orthogonality

Linear Algebra using Dirac Notation: Pt. 2

implies that if we fix a basis v of V and let M and M be the associated invertible symmetric matrices computing, and, then M = (L L)M and the

MATH 583A REVIEW SESSION #1

MATH 20F: LINEAR ALGEBRA LECTURE B00 (T. KEMP)

Notes on singular value decomposition for Math 54. Recall that if A is a symmetric n n matrix, then A has real eigenvalues A = P DP 1 A = P DP T.

NORMS ON SPACE OF MATRICES

Linear Algebra Review. Vectors

Chapter 4 Euclid Space

4.2. ORTHOGONALITY 161

MATH 304 Linear Algebra Lecture 20: The Gram-Schmidt process (continued). Eigenvalues and eigenvectors.

1 Planar rotations. Math Abstract Linear Algebra Fall 2011, section E1 Orthogonal matrices and rotations

Principal Component Analysis

22.3. Repeated Eigenvalues and Symmetric Matrices. Introduction. Prerequisites. Learning Outcomes

4.1 Distance and Length

1. What is the determinant of the following matrix? a 1 a 2 4a 3 2a 2 b 1 b 2 4b 3 2b c 1. = 4, then det

Vector Geometry. Chapter 5

Linear Algebra 2 Spectral Notes

Linear Algebra Massoud Malek

Linear Algebra. Session 12

Some notes on Coxeter groups

ECE 275A Homework #3 Solutions

DS-GA 1002 Lecture notes 0 Fall Linear Algebra. These notes provide a review of basic concepts in linear algebra.

6 Inner Product Spaces

MATH 315 Linear Algebra Homework #1 Assigned: August 20, 2018

Math 350 Fall 2011 Notes about inner product spaces. In this notes we state and prove some important properties of inner product spaces.

Review of Linear Algebra

Chapter 6. Orthogonality

SOLUTION KEY TO THE LINEAR ALGEBRA FINAL EXAM 1 2 ( 2) ( 1) c a = 1 0

Exam questions with full solutions

MTH Linear Algebra. Study Guide. Dr. Tony Yee Department of Mathematics and Information Technology The Hong Kong Institute of Education

A Review of Linear Algebra

linearly indepedent eigenvectors as the multiplicity of the root, but in general there may be no more than one. For further discussion, assume matrice

Recall the convention that, for us, all vectors are column vectors.

7. Symmetric Matrices and Quadratic Forms

(a) If A is a 3 by 4 matrix, what does this tell us about its nullspace? Solution: dim N(A) 1, since rank(a) 3. Ax =

CS 143 Linear Algebra Review

Math 520 Exam 2 Topic Outline Sections 1 3 (Xiao/Dumas/Liaw) Spring 2008

Math 18, Linear Algebra, Lecture C00, Spring 2017 Review and Practice Problems for Final Exam

Review problems for MA 54, Fall 2004.

LINEAR ALGEBRA KNOWLEDGE SURVEY

Trace Class Operators and Lidskii s Theorem

Least Squares Optimization

(v, w) = arccos( < v, w >

2. Linear algebra. matrices and vectors. linear equations. range and nullspace of matrices. function of vectors, gradient and Hessian

October 25, 2013 INNER PRODUCT SPACES

5 Linear Transformations

Duke University, Department of Electrical and Computer Engineering Optimization for Scientists and Engineers c Alex Bronstein, 2014

(v, w) = arccos( < v, w >

Linear Algebra 1. M.T.Nair Department of Mathematics, IIT Madras. and in that case x is called an eigenvector of T corresponding to the eigenvalue λ.

Diagonalizing Matrices

Algebra II. Paulius Drungilas and Jonas Jankauskas

Conceptual Questions for Review

Algebra Workshops 10 and 11

Lecture 7: Positive Semidefinite Matrices

Theorem A.1. If A is any nonzero m x n matrix, then A is equivalent to a partitioned matrix of the form. k k n-k. m-k k m-k n-k

EE731 Lecture Notes: Matrix Computations for Signal Processing

LINEAR ALGEBRA BOOT CAMP WEEK 4: THE SPECTRAL THEOREM

4 ORTHOGONALITY ORTHOGONALITY OF THE FOUR SUBSPACES 4.1

The value of a problem is not so much coming up with the answer as in the ideas and attempted ideas it forces on the would be solver I.N.

Repeated Eigenvalues and Symmetric Matrices

IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET

Chapter 7: Symmetric Matrices and Quadratic Forms

We simply compute: for v = x i e i, bilinearity of B implies that Q B (v) = B(v, v) is given by xi x j B(e i, e j ) =

Elementary linear algebra

Linear Algebra. Preliminary Lecture Notes

SOLUTIONS TO EXERCISES FOR MATHEMATICS 133 Part 1. I. Topics from linear algebra

Math 1060 Linear Algebra Homework Exercises 1 1. Find the complete solutions (if any!) to each of the following systems of simultaneous equations:

LINEAR ALGEBRA SUMMARY SHEET.

(v, w) = arccos( < v, w >

Optimization Theory. A Concise Introduction. Jiongmin Yong

2. Every linear system with the same number of equations as unknowns has a unique solution.

15 Singular Value Decomposition

Extra Problems for Math 2050 Linear Algebra I

Math 3C Lecture 25. John Douglas Moore

Lecture 2: Linear Algebra Review

Chapter 8. Rigid transformations

A PRIMER ON SESQUILINEAR FORMS

The Jordan Canonical Form

Quantum Computing Lecture 2. Review of Linear Algebra

NOTES on LINEAR ALGEBRA 1

Applied Linear Algebra in Geoscience Using MATLAB

BASIC ALGORITHMS IN LINEAR ALGEBRA. Matrices and Applications of Gaussian Elimination. A 2 x. A T m x. A 1 x A T 1. A m x

1. Foundations of Numerics from Advanced Mathematics. Linear Algebra

Introduction to Linear Algebra, Second Edition, Serge Lange

Lecture 3: Review of Linear Algebra

Lecture 3: Review of Linear Algebra

We wish the reader success in future encounters with the concepts of linear algebra.

The Singular Value Decomposition and Least Squares Problems

Math 443 Differential Geometry Spring Handout 3: Bilinear and Quadratic Forms This handout should be read just before Chapter 4 of the textbook.

Exercise Sheet 1.

Foundations of Matrix Analysis

Linear Algebra. Preliminary Lecture Notes

9.1 Eigenvectors and Eigenvalues of a Linear Map

j=1 x j p, if 1 p <, x i ξ : x i < ξ} 0 as p.

Transcription:

Theoret. Appl. Mech., Vol.37, No.3, pp. 229 250, Belgrade 2010 On the state of pure shear Jovo P. Jarić Dragoslav S. Kuzmanović Zoran -D. Golubović Abstract The algebraic proof of the fundamental theorem concerning pure shear, by making use only of the notion of orthogonal projector, is presented. It has been shown that the state of pure shear is the same for all singular symmetric traceless tensors in E 3, up to the rotation. Keywords: continuum mechanics, pure shear, orthogonal projector. 1 Introduction It is known that in classical continuum mechanics the Cauchy stress tensor T is symmetric. By definition, a state of stress is said to be one of pure shear if there is an orthogonal basis p i (i = 1, 2, 3) for which p i Tp i = 0, no sum over indices i = 1, 2, 3. (1) Faculty of Mathematics, University of Belgrade, Serbia Faculty of Transport and Traffic Engineering, University of Belgrade, Serbia Faculty of Mechanical Engineering, University of Belgrade, Serbia 229

230 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović Note that, if p i satisfies (1), so does p i. Therefore, these vectors p i (i = 1, 2, 3) are unique up to their orientation. In what follows, we shall use the term unique in this sense. Theorem 1 A necessary and sufficient condition for T to be a state of pure shear is tr T = 0. (2) It is almost obvious that (1) is necessary condition for (2). Indeed, from (1) and 3 p i p i = I, (3) i=1 where I is identity tensor, we have 0 = 3 p i Tp i = i=1 3 tr T(p i p i ) = tr T. (4) i=1 As for the second part of the theorem it suffices for the proof to exhibit just one orthonormal basis for which (2) (1). Belik and Fosdick [1], in order to exhibit all such bases, prove this fundamental theorem from both the geometric and algebraic points of view in three dimensional Euclidean space, E 3. Recently, Boulanger and Hayes [2] presented what they called an even more elementary proof and gave an insightful geometrical approach in terms of elliptical sections of the stress ellipsoid. They also stated that it may be shown that n Tn = 0 for all n lying in a plane, if and only if one of the eigenvalues is zero (say σ 2 = 0), and all the n lie in either one or other of the planes of central circular section of ellipsoid E... No proof was given. Ting [3] provided a characterization of directions n such that σ nn = 0 in terms of the total shear in the plane normal to n, τ = Tn. Norris [4] discussed the pure shear basis vectors independent of the values of principal stresses. Here, making use only of the notion of orthogonal projector, we present the proof of the theorem in E 3. It distinguishes the present

On the State of Pure Shear 231 discussion from the recent notes ([1]-[4]). The proof includes also the case mentioned by Boulanger and Hayes [2]. In our approach, we do not refer to any ellipsoid, nor do we determine the principal axes of an elliptical section. In this sense our approach is direct and general. This is shown in Section 3, where we analyze the n-dimensional Euclidean space E n. Of course, 3-dimensional case is a special one. But in presenting the paper in this order we wanted to emphasize two things some specific feature of the 3-dimensional case as well as the role of the orthogonal projector in solving the general n-dimensional case. The organization of this paper is as follows. In Section 1, we establish the notation. In Section 2, we discuss only the algebraic approach for the 3-dimensional case, since the geometrical approach is given in [1]. Moreover, we show that the state of pure shear is the same for all singular symmetric traceless tensors in E 3, up to a rotation. In Section 3 detailed analysis of the n-dimensional case is given. The procedure consists of several steps. Each step is based on corresponding Lemma. Although these lemmas are identical in form, we stated them separately in order to clarified each step. In Section 4, we extend our results to nonsymmetric tensors in E n. Finally, in Section 5, the summary and a brief discussion are given. 2 Notation We use the following notations: - π: p x = 0 for the plane defined by unit outward normal vector p, where x E n, - P = I p p Sym, P 2 = P, for the orthogonal projector along p onto π, - v = Pv for the projection of a vector, - S = PSP for the projection of a second order tensor S.

232 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović S is singular for any P I. Particularly, Pp = 0 and S p = 0. Therefore, p is eigenvector of P and S, corresponding to zero eigenvalue. Also, Pξ = ξp = ξ, ξ S ξ = ξ Sξ, (5) for any vector ξ π. For symmetric S: S = PSP = S Sp p p Sp + (p Sp)p p (6) tr S = tr S p Sp. (7) As a preliminary to the general definition of a projector, we remind the reader of the definition of the decomposition of E n into direct sum of subspaces U and V, symbolized by E n = U V. (8) Then P is orthogonal projector, of E n along V onto U, if P Sym and U and V are orthogonal. 3 Algebraic Approach in E 3 First, we confine our investigation to a tensor T Sym in E 3. For further reference we write its spectral form T = σ 1 n 1 n 1 + σ 2 n 2 n 2 + σ 3 n 3 n 3. (9) Then, in view of (2) We assume that σ 1 + σ 2 + σ 3 = 0. (10) σ 1 > 0, σ 2 0, σ 3 < 0. (11) We seek p(= p 1 ), such that the component of T in the direction of p is zero, i.e. p Tp = 0. (12)

On the State of Pure Shear 233 Accordingly, p lies along a generator of the elliptical cone c : x (Tx) = σ 1 x 2 1 + σ 2 x 2 2 + σ 3 x 2 3 = 0 (13) through its tip. A solution to (13) certainly exists, i.e. x i = ±1, i = 1, 2, 3. For any particular p, which satisfies (12), p 2 and p 3 must lie in π. Therefore, π c defines directions of p 2 and p 3, if they are orthogonal. To show that, we make use of (5) 1 and write where 0 = p α Tp α = p α PTPp α = p α T p α, α = 2, 3, (14) T = PTP Sym (15) is the projection of T along p onto π. Moreover, in view of (6), (7) and (12) we have and But T = PTP = T Tp p p Tp, (16) tr T = tr T, (17) T = λ 1 ν 1 ν 1 + λ 2 ν 2 ν 2. (18) tr T = 0 tr T = 0, (19) so that λ 1 = λ 2 (= λ) and accordingly we write (18) as T = λ(ν 1 ν 1 ν 2 ν 2 ). (20) In view of (14) and (20), the corresponding p α must lie on the cone c : ξ T ξ = λ(ξ1 2 ξ2) 2 = 0, (21) where ξ = ξ α ν α. We shall discuss all possible solutions of (21), which satisfy (1). I) λ 0. In this case ξ 2 = ±ξ 1,

234 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović i.e. But, p = ξ ξ and thus ξ = ξ 1 (ν 1 ± ν 2 ). p 2 = 1 2 (ν 1 + ν 2 ), p 3 = 1 2 (ν 1 ν 2 ). (22) Thus obtained p i (i = 1, 2, 3) are orthonormal and represent the unique solution to our problem. It is easy to calculate λ. For instance, from (20) we have and from this T 2 = λ 2 (ν 1 ν 1 + ν 2 ν 2 ), (23) Next, in view of (15) and (12), we obtain 2λ 2 = tr T 2. (24) 2λ 2 = tr (PTP) 2 = tr (PT) 2 = tr T 2 2p T 2 p (25) (see (3.6) in [2]). II) λ = 0. Then T = 0, and from (16) we have T = Tp p + p Tp, from which we conclude that either (see for instance [5]), or In view of this and (19) 1 we have det T = 0, (26) σ 2 = 0. σ 1 = σ 3 (= σ),

On the State of Pure Shear 235 Thus, from (9) we have T = σ (n 1 n 1 n 3 n 3 ). (27) Since (21) is identity for any ξ π, we are looking for p c, which defines such plane π. But in view of (13) c : x Tx = σ(x 2 1 x 2 3) = 0, (28) so that τ 1 : x 1 + x 3 = 0 t 1 x = 0, τ 2 : x 1 x 3 = 0 t 2 x = 0, (29) are the solutions of (28), where t 1 = 1 2 (n 1 + n 3 ), t 2 = 1 2 (n 1 n 3 ). (30) It is clear that c = τ 1 τ 2, where τ 1 and τ 2 represent two perpendicular planes, which intersect along direction defined by n 2. In order to complete our discussion we consider the following possible cases. a) Let p 2, p 3 τ 1 be any two orthonormal vectors. Then p 1 = t 1 τ 2 is the only unit vector perpendicular to the vectors p 2 and p 3. More precisely, any such set of orthonormal vectors satisfying (1) is given by p 1 = t 1, p 2 = n 2 cos α + t 2 sin α, p 3 = n 2 sin α + t 2 cos α, 0 α π. (31) b) In the same way, we conclude that any two orthonormal vectors p 2, p 3 τ 2, and p 1 = t 1 τ 1, given by p 1 = t 2, p 2 = n 2 cos α + t 1 sin α, p 3 = n 2 sin α + t 1 cos α, 0 α π, (32)

236 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović form a set of orthonormal vectors satisfying (1). The sets of orthonormal vectors given by (31) and (32) include all possible solutions to (1). Particularly, if cos α = 1, then the set of vectors n 2, t 2, t 1 (33) satisfies (1). Finally, we go one step further and state Lemma 1 Let T, S be any two symmetric singular traceless tensors. Then the cones that define their states of pure shear, differ by the rotation of their eigenvectors. Proof. According to the supposition of Lemma 1 Tn 2 = 0 and Sf 2 = 0. Then (27) holds and S = µ (f 1 f 1 f 3 f 3 ), (34) where f i (i = 1, 2, 3) are orthonormal. Now, there is unique orthogonal tensor R such that Rf i = n i. Hence, RSR T = µ (Rf 1 Rf 1 Rf 3 Rf 3 ) = = µ (n 1 n 1 n 3 n 3 ) = = µ σ T where µ/σ 0. In view of the above relation, the cone transforms to the cone where c T : x Tx = 0, c S : y Sy = 0 y = R T x. Geometrically these cones differ for rotation represented by R.

On the State of Pure Shear 237 Corollary 1 Given two singular, symmetric and traceless tensors T and S, define an orthogonal tensor R = n i f i, where n i and f i, i = 1, 2, 3, are eigenvectors of T and S, respectively. Let p i, i = 1, 2, 3, be an orthonormal set of vectors satisfying (1). Then the set of orthonormal vectors q i = R T p i satisfies q i Sq i = 0. This simply follows from the last three expressions. We shall illustrate it by the following Example Let, 1 0 0 3 6 0 T = 0 1 0, S = 6 0 6 0 0 0 0 6 3 with respect to the basis n 1, n 2, n 3. Obviously, It easy to show that is tr T = det T = 0 and tr S = det S = 0. s 1 = 9, s 2 = 9, s 3 = 0 are the eigenvalues of S. Corresponding eigenvectors are Then f 1 = 1 3 (1, 2, 2), f 2 = 1 3 ( 2, 2, 1), f 3 = 1 (2, 1, 2). 3 The orthogonal tensor which is represented by S = 9(f 1 f 1 f 2 f 2 ). R = n i f i, 1 2 2 1 2 2 1, 3 2 1 2

238 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović on the basis (n 1, n 2, n 3 ), transforms n 1, n 2, n 3 into f 1, f 2, f 3 so that Rf i = n i. It follows that RSR T = 9T. Then, for all x, for which transforms into so that x Tx = 0 y = Rx, y Sy = 0. If p i p j = δ ij and p i Tp i = 0, i = 1, 2, 3, no sum with respect to i, then, for all q i = Rp i, i = 1, 2, 3, q i q j = δ ij and q i Sq i = 0, no sum with respect to i. Further, 1 (n 1 ± n 2 ) = R 1 (f 1 ± f 2 ). 2 2 Also, (31) and (32) are mapped by R into corresponding solutions of S. 4 n-dimensional case In investigating n-dimensional case, we shall make use of the following notation rx αr, rσ αr, rn αr, α r = 1,..., k r their meaning will be clear from the context. Let a tensor T Sym is given in Euclidean n-dimensional space E n. Then Theorem 1 holds, having in mind that now i = 1, 2,..., n, in (1) and (3). In order to include all possible cases, we write its spectral form as T = k σ α n α n α, k n, (35) α=1

On the State of Pure Shear 239 where Then from (2) and (35), we have n i n j = δ ij, i, j = 1, 2,..., n. (36) k σ α = 0. α=1 If k < n, then there is a set of n k orthonormal vectors n σ such that Tn σ = 0, σ = k + 1,..., n. (37) This set of vectors n σ spans n k dimensional vector space V, so that any unit vector v V satisfies (1). Hence, there is an infinity of sets of n k orthonormal vectors which satisfy (1). Remaining k orthonormal vectors are in k-dimensional spaces U, spanned by k orthonormal vectors n α, α = 1,..., k. Thus, E n = U V, where U and V are mutually orthogonal spaces. In order to complete the set of n orthonormal unit vectors satisfying (1), we proceed in several steps. A 1. Let x = x i n i. Then x must lay on the cone C : x Tx = k σ α x 2 α = 0. (38) Obviously (38) does not impose any restrictions upon x σ, σ = k + 1,..., n. Therefore, it is sufficient to consider only x U, i.e. when x = x α n α, α = 1,..., k or equivalently when x n σ = 0. Let x = x α n α U be any solution of (38), and p 1 its unit vector. Then, the set of orthonormal vectors p 1 and n σ, σ = k+1,..., n, spans the (n k + 1) dimensional linear vector space V (1) 1. Accordingly, any x V (1) 1 satisfies (38). Therefore, there is infinite of sets of orthonormal vectors in V (1) 1 satisfying (1). α=1

240 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović A 2. Now, let E n = V (1) 1 U 1. Then V (1) 1 V, U 1 U, and dim U 1 = k 1. Therefore, the orthogonal projection of E n along V (1) 1 onto U 1 is defined by the orthogonal projector P 1 = I p 1 p 1 Obviously, rank P 1 = k 1. Lemma 2 x U 1 iff P 1 x = x. n σ=k+1 n σ n σ. (39) Proof. If x U 1, then x p 1 = 0 and x n σ = 0. Hence P 1 x = x. Conversely, from x = P 1 x we have x p 1 = 0 and x n σ = 0, i.e. x U 1. Thus, the remaining k 1 orthonormal vectors satisfying (39) must lay in the intersection of U 1 and the cone (38). Making use of Lemma 2, their intersection can be put in the following form: where x Tx = P 1 x TP 1 x = x P 1 TP 1 x = x T 1 x = 0, (40) T 1 = P 1 TP 1, T 1 Sym (41) is the orthogonal projection of T by P 1. According to the modified forms of (6) and (7) we conclude that tr T 1 = tr T, and tr T tr T 1 = 0. (42) But rank T 1 k 1. In general, its spectral form reads T 1 = k 1 α 1 =1 1σ α1 1n α1 1 n α1 (43) The set of n vectors 1 n α1, p 1, n σ, α 1 = 1,..., k 1; σ = k + 1,..., n, are orthonormal and thus linearly independent. They may be taken as the basis of E n. Then, we may write x = k 1 α 1 =1 n k 1x α1 + p 1 p 1 + x σ n σ, σ=1

On the State of Pure Shear 241 for any x E n. But, we need only those x which satisfy x = Px = k 1 α 1 =1 1x α1 U 1. Hence, in view of properties of T 1, we have that C 1 : x Tx = x T 1 x = k 1 α 1 =1 1σ α1 1x 2 α 1 = 0. (44) Accordingly, any unit vector p 2 U 1 along the generator of the above cone (44) is the solution of (1). Hence, we have n k + 2 orthonormal vectors satisfying (1). They are p 1, p 2, n σ, σ = k + 1,..., n. Moreover, in addition to V (1) 1, we have space V (2) 1 of n k + 1 dimensions, spanned by p 2, n σ, σ = k + 1,..., n, such that any vector in this space satisfies (1). The space V 2 of n k + 2 dimension spanned by vectors p 1, p 2, n σ, σ = k + 1,..., n, does not have this property. For instance, let x = p 1 p 1 + p 2 p 2. Then, in general, x Tx = 2p 1 p 2 p 1 Tp 2 0, i.e. x is not on the cone (44). Therefore, any set of orthonormal vectors in V (1) 1, together with p 2 form a set of n k + 2 orthonormal vectors satisfying (1). Likewise, any set of orthonormal vectors in V (2) 1, together with p 1 form a set of n k + 2 orthonormal vectors satisfying (1). A 3. Let E n = V 2 U 2. Then P 2 = I 2 p a p a a=1 n σ=k+1 n σ n σ, (45) where P 2 Sym, rank P 2 = k 2, represents an orthogonal projection of E n along V 2 onto U 2. Obviously, the remaining k 2 orthonormal vectors satisfying (1) must lay in the intersection of U 2 and the cone (38). But, vectors x U 2 are subjected to the following restrictions: x p a = 0, and x n σ = 0, a = 1, 2; σ = k + 1,..., n. Therefore, we restate Lemma 2 in this case as: Lemma 3 x U 2 iff P 2 x = x. The proof of this lemma is the same as for Lemma 2.

242 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović Making use of the Lemma 3, we write the intersection of U 2 and (38) as x Tx = P 2 x TP 2 x = x P 2 TP 2 x = x T 2 x = 0, where T 2 = P 2 TP 2, T 2 Sym, rank T 2 k 2 tr T 2 = tr T, tr T = 0 tr T 2 = 0. The spectral form of T 2, in general, now reads (46) T 2 = k 2 α 2 =1 2σ α2 2n α2 2 n α2 (47) The set of n orthonormal vectors 2 n α2 ; p a ; n σ ; α 2 = 1,..., k 2; a = 1, 2; σ = k + 1,..., n; spans E n. Thus, any x E n has the following representation x = k 2 α 2 =1 2x α2 2n α2 + 2 n k p a p a + x σ n σ. Then, in view of Lemma 3, we write for the intersection of U 2 and (38) a=1 C 2 : x Tx = x T 2 x = k 2 α 2 =1 σ=1 2σ α2 2x 2 α 2 = 0. (48) Then, any unit vector p 3 U 2 of x = k 2 α 2 =1 2x α2 2n α2 along the generator of the cone (48) is the solution of (1). Hence we have n k + 3 orthonormal vectors satisfying (1). They are p 1, p 2, p 3, n σ, σ = k + 1,..., n. Moreover, in addition to V (1) 1 and V (2) 1 of n k + 1 dimensions, we have the space V (3) 1, also of n k + 1 dimension, spanned by p 3, n σ, σ = k +1,..., n, such that any vector in this space satisfies (1). Again, no space of n k + 2 dimension spanned by two of vectors p 1, p 2, p 3 and n σ, σ = k + 1,..., n, has this property. Therefore, any set of orthonormal vectors in V (1) 1 together with p 2 and p 3 form a set of n k + 3 orthonormal vectors satisfying (1).

On the State of Pure Shear 243 Likewise, any set of orthonormal vectors in V (2) 1 together with p 1 and p 3 form a set of n k + 3 orthonormal vectors satisfying (1). Also, any set of orthonormal vectors in V (3) 1 together with p 1 and p 2 form a set of n k + 3 orthonormal vectors satisfying (1). More concisely, any set of orthonormal vectors in V (k) 1, together with the set {p e } of two vectors, e, k = 1, 2, 3, e k, form a set of n k + 3 orthonormal vectors satisfying (1). A 4. We may proceed further in the same way until P r = I r p a p a a=1 n σ=k+1 n σ n σ, (49) where rank P r = k r > 0; p a, n σ ; a = 1,..., r; σ = k+1,..., n. From the way we obtain p a, vectors p a ; n σ ; a = 1,..., r; σ = k + 1,..., n, are orthonormal and satisfy (1). We shall denote the (n k + r) - dimensional space they span, by V r. Then, we may write E n = V r U r, where dim U r = k r > 0, and thus U r U 1 U. As above, we conclude that any x U r must satisfy the following conditions: x p a = 0 and x n σ = 0, a = 1,..., r; σ = k +1,..., n. Next, as above, we write Lemma 4 x U r iff P r x = x. Then the intersection of U r and (38) reads as x Tx = P r x TP r x = x P r TP r x = x T r x = 0, where T r = P r TP r, T r Sym, rank T r k r tr T r = tr T, tr T = 0 tr T r = 0. The spectral form of T r, in general, now reads (50) T r = k r α r =1 rσ αr rn αr r n αr. (51) The set of n orthonormal vectors r n αr ; p a ; n σ ; α r = 1,..., k r; a = 1,..., r; σ = k + 1,..., n; spans E n.

244 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović Thus any x E n has the following representation x = k r α r=1 rx αr rn αr + r n k p a p a + x σ n σ. (52) a=1 σ=1 Then, in view of Lemma r+1, we write for the intersection of U r and (38) as C r : x Tx = x T r x = k r α r =1 rσ αr rx 2 α r = 0. (53) Then any unit vector p r+1 U r along the generator of the cone (48) is the solution of (1). Hence we have n k + r + 1 orthonormal vectors satisfying (1). They are p b ; n σ ; b = 1,..., r + 1; σ = k + 1,..., n. But now we have V (b) 1, b = 1,..., r + 1, linear vector spaces of n k + 1 dimensions, spanned by each vector p b, b = 1,..., r + 1, and set of vectors n σ, σ = k + 1,..., n, such that any vector in this spaces satisfies (1). Again, no space of n k + 2 or higher dimension spanned by vectors p b, b = 1,..., r + 1 and set of vectors n σ, σ = k + 1,..., n has this property. Therefore, any set of orthonormal vectors in V (b) 1, b = 1,..., r + 1 and set {p c } of r vectors, b, c = 1,..., r + 1, b c, represents the set of n k + r + 1 orthonormal vectors satisfying (1). It is clear that (51), (52) and (53) represent recurrent formulas. Indeed, for r = 0, 1,..., k 2 we obtain all possible cases. Particularly, for r = 0, with following identification: C 0 = C, 0 x α0 = x α, p 0 = 0 we obtain (38). A 5. The final step is obtained for r = k 2. Then, from (51), (52) and

On the State of Pure Shear 245 (53) we have x = T k 2 = 2 α k 2 =1 2 α k 2 =1 k 2σ αk 2 k 2n αk 2 k 2 n αk 2 k 2 k 2x αk 2 k 2n αk 2 + C k 2 : x Tx = x T k 2 x = But since tr T k 2 = 0, then and hence 2 α k 2 =1 n k p a p a + x σ n σ a=1 σ=1 k 2σ αk 2 k 2x 2 α k 2 = 0. k 2σ 1 + k 2 σ 2 = 0 or k 2σ 1 = k 2 σ 2 = k 2 σ, (54) T k 2 = k 2 σ ( k 2 n 1 k 2 n 1 k 2 n 2 k 2 n 2 ), (55) C k 2 : x Tx = x T k 2 x = k 2 σ ( k 2x 2 1 k 2 x 2 2) = 0. (56) From (55) we obtain that k 2x 2 = ± k 2 x 1. (57) Then the last two vectors, which completes the set of n orthonormal set vectors satisfying (1), are obtained as the unit vectors of set of vectors k 2 n k x ± = k 2 x 2 ( k 2 n 1 ± k 2 n 2 ) + p a p a + x σ n σ. (58) a=1 Clearly, U k 2 U 1 U. In U k 2 we have that x ± = k 2 x 2 ( k 2 n 1 ± k 2 n 2 ), σ=1 so that their unit vectors are given by very simple expressions p k 1 = p k = 2 2 ( k 2n 1 + k 2 n 2 ), 2 2 ( k 2n 1 k 2 n 2 ) (59)

246 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović Obviously, p k 1 p k = 0. Then we conclude that there are k linear spaces V (α) 1 of n k + 1 dimensions spanned by the set of {p β, n σ }; α, β = 1,..., k, α β; σ = k + 1,..., n. Thus, any other set of orthogonal vectors is formed of any set of n k + 1 vectors in V (α) 1, and the set of k 1 vectors {p β }, α β. In particular, when n = 3 and k = 2, we have the Case II. The case k = n is included as the special one. Then x σ = 0. As a consequence, there is no space of two and higher dimension in which any vector will satisfies (1). The orthonormal set of vectors satisfying (1) is just the set of vectors {p α }, α = 1,..., k. Particularly, when n = 3 p 1, p 2, p 3, are orthonormal vectors, the Case I. 5 Non-symmetric tensor It has long been known that non-symmetric stress tensors T may occur in mechanics. Then, its unique decomposition in symmetric and skewsymmetric tensors, denoted by T and T A, respectively, is given by T = T + T A. (60) But this decomposition holds for any second order tensor T in E n. Moreover, from (60), we have where p is any unit vector. Accordingly, we state the following p Tp = p Tp, (61) Theorem 2 A necessary and sufficient condition for T to be a state of pure shear is tr T = 0. (62) Obviously, in that case only symmetric part of any tensor of second order matters. Therefore, the proof of the Theorem 1 holds generally for any tensor T of second order in E n.

On the State of Pure Shear 247 6 Discussion Recently Hayes and Laffey in their paper [6], in Remark 2 stated: another formulation of the Basic Result (in our paper equation (1)) in matrix theory language (valid in all dimensions) is as follows: Let T be an n n matrix with tr T = 0. Then there exists a real orthogonal matrix Q such that Q T T Q has all its diagonal entries zero. To find this orthogonal matrix Q they proceed as follows. Since tr T = 0, T is not a scalar multiple of the identity matrix, so they can choose a vector w such that w and T w are linearly independent. Let z = Sw rw and note that w z = 0. Let w 1 = w/ w and w 2 = z/ z, and extend these to an orthonormal basis w 1, w 2,..., w n of real n-space and let W be the corresponding orthogonal matrix (w 1, w 2,..., w n ). Then ( ) 0 W T T12 T W = T12 T (63) T 22 where T 22 is a symmetric (n 1) (n 1) matrix with tr S 22 = 0. Using induction on n, they can find an orthogonal (n 1) (n 1) matrix Y with Y2 T T 22 Y 2 having zero entries on its diagonal. Let ( ) 1 0 Y = and Q = W Y. (64) 0 Y 2 Then Q is orthogonal and ( ) 0 Q T T12 Y T Q = 2 Y2 T T12 T Y2 T T 22 Y 2 (65) has zero diagonal, as desired. The proof of this statement, in our opinion, is at least incomplete. Besides missprint where instead r = z Sw/w w should bee written that r = w Sw/w w, the expression for z is missleading. For instance, zero element in (63) means that w 1 T w 1 = 0. Hence, this is the only condition which has to be satisfied by w 1. There is no any need for z at this stage to be define by T and w.

248 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović In the next step, of induction, we have to choose w 2 such that w 2 T w 2 = 0 and w 1 w 2 = 0 and so on. In fact, the problem of finding Q reduces to the process of finding q i which has to satisfy the condition that q i T q i = 0. One of the procedure for this problem is given in our Chapter 3. 7 Conclusion We prove Theorem 1 in general form for any tensor T of second order in E n, making use of the notation of orthogonal projector. In E 3 we derive some general conclusion concerning singular traceless tensors of second order. The generalization of this problem to the decomposition of a large incompressible deformation in E 3 has been done by He and Zheng [7]. We did not discuss some special cases, such as T has some eigenvalues of the multiplicity of higher order then one. In these cases, the problem simplifies a lot, but the procedure is same. Also, we did not discus the applications of these representation for such a state of pure shear in continuum mechanics. This has been investigated in several papers, among them we refer the reader to Boulanger and Hayes [8], and Norris [4]. Acknowledgements The authors are grateful to prof. Siniša Mesarović and dr Borislav Gajić for useful comments and suggestions during the preparation of the paper. This paper is a part of scientific project supported by MNTR of Republic Serbia. References [1] P. Belik and R. Fosdick, The state of pure shear, Journal of Elasticity, 52, 91-98, 1998.

On the State of Pure Shear 249 [2] Ph. Boulanger and M. Hayes, On Pure Shear, Journal of Elasticity, 77, 83-89, 2004. [3] T. C. T. Ting, Further study on pure shear, Journal of Elasticity 83 95-104, 2006. [4] A. Norris, Pure shear axes and elastic strain energy, The Quarterly Journal of Mechanics and Applied Mathematics, Vol. 59, No.4, pp. 551-561, 2006. [5] P. Chadwick, Continuum Mechanics, London, George Allen & Unwin Ltd., 1976., pp. 17 (Problem 4). [6] M. Hayes and T.J. Laffey, Pure Shear - a Footnote, Journal of Elasticity, 92, 109-113, 2008. [7] Q.C. He, Q.S. Zheng, Decomposition of Large Incompressible Deformations, J. Elasticity, 85, 2006. [8] Ph. Boulanger, M. Hayes, Consequences of a result on pure shear, Int. J. Nonlin. Mech. Vol 42, pp. 376-380 (2007) Submitted on June 2010, revised on September 2010.

250 Jovo P. Jarić, Dragoslav S. Kuzmanović, Zoran -D. Golubović O stanju čistog smicanja U radu se dokazuje fundamentalna teorema, koja se odnosi na čisto smicanje, koristeći samo pojam ortogonalnog operatora. Pokazano je da je stanje čistog smicanja isto, do na rotaciju, za sve singularne simetrične tenzore u E 3, čiji je trag jednak nuli. doi:10.2298/tam1003229j Math.Subj.Class.: 74A05, 74A10.