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Functionaland Structured TensorAnalysisfor Engineers
A casual (intuition-based) introduction to vector andtensoranalysis with
reviews of popular notations used in contemporary materials modeling
R. M. Brannon
University of New Mexico, Albuquerque
Copyright is reserved.
Individual copies may be made for personal use.
No part of this document may be reproduced for profit.
Contact author at rmbrann@sandia.gov
UNM BOOK DRAFT
September 4, 2003 5:21 pm
NOTE: When using Adobe’s “acrobat reader” to view this
document, the page numbers in acrobat will not coincide
with the page numbers shown at the bottom of each page
of this document.
Note to draft readers: The most useful textbooks are
the ones with fantastic indexes. The book’s index is
rather new and still under construction.
It would really help if you all could send me a note
whenever you discover that an important entry is miss-
ing from this index. I’ll be sure to add it.
This work is a community effort. Let’s try to make this
document helpful to others.
FUNCTIONAL AND STRUCTURED TENSOR
ANALYSIS FOR ENGINEERS
A casual (intuition-based) introduction to vector
and tensoranalysis with reviews of popular
notations used in contemporary materials
modeling
Rebecca M. Brannon
†
†
University of New Mexico Adjunct professor
rmbrann@sandia.gov
Abstract
Elementary vector andtensoranalysis concepts are reviewed in a manner that
proves useful for higher-order tensoranalysis of anisotropic media. In addition
to reviewing basic matrix and vector analysis, the concept of a tensor is cov-
ered by reviewing and contrasting numerous different definition one might see
in the literature for the term “tensor.” Basic vector andtensor operations are
provided, as well as some lesser-known operations that are useful in materials
modeling. Considerable space is devoted to “philosophical” discussions about
relative merits of the many (often conflicting) tensor notation systems in popu-
lar use.
ii
iii
Acknowledgments
An indeterminately large (but, of course, countable) set of people who have offered
advice, encouragement, and fantastic suggestions throughout the years that I’ve spent
writing this document. I say years because the seeds for this document were sown back in
1986, when I was a co-op student at Los Alamos National Laboratories, and I made the
mistake of asking my supervisor, Norm Johnson, “what’s a tensor?” His reply? “read the
appendix of R.B. “Bob” Bird’s book, Dynamics of Polymeric Liquids. I did — and got
hooked. Bird’s appendix (which has nothing to do with polymers) is an outstanding and
succinct summary of vector andtensor analysis. Reading it motivated me, as an under-
graduate, to take my first graduate level continuum mechanics class from Dr. H.L. “Buck”
Schreyer at the University of New Mexico. Buck Schreyer used multiple underlines
beneath symbols as a teaching aid to help his students keep track of the different kinds of
strange new objects (tensors) appearing in his lectures, and I have adopted his notation in
this document. Later taking Buck’s beginning and advanced finite element classes further
improved my command of matrix analysisand partial differential equations. Buck’s teach-
ing pace was fast, so we all struggled to keep up. Buck was careful to explain that he
would often cover esoteric subjects principally to enable us to effectively read the litera-
ture, though sometimes merely to give us a different perspective on what we had already
learned. Buck armed us with a slew of neat tricks or fascinating insights that were rarely
seen in any publications. I often found myself “secretly” using Buck’s tips in my own
work, and then struggling to figure out how to explain how I was able to come up with
these “miracle instant answers” — the effort to reproduce my results using conventional
(better known) techniques helped me learn better how to communicate difficult concepts
to a broader audience. While taking Buck’s continuum mechanics course, I simulta-
neously learned variational mechanics from Fred Ju (also at UNM), which was fortunate
timing because Dr. Ju’s refreshing and careful teaching style forced me to make enlighten-
ing connections between his class and Schreyer’s class. Taking thermodynamics from A.
Razanni (UNM) helped me improve my understanding of partial derivatives and their
applications (furthermore, my interactions with Buck Schreyer helped me figure out how
gas thermodynamics equations generalized to the solid mechanics arena). Following my
undergraduate experiences at UNM, I was fortunate to learn advanced applications of con-
tinuum mechanics from my Ph.D advisor, Prof. Walt Drugan (U. Wisconsin), who intro-
duced me to even more (often completely new) viewpoints to add to my tensor analysis
toolbelt. While at Wisconsin, I took an elasticity course from Prof. Chen, who was enam-
oured of doing all proofs entirely in curvilinear notation, so I was forced to improve my
abilities in this area (curvilinear analysis is not covered in this book, but it may be found in
a separate publication, Ref. [6]. A slightly different spin on curvilinear analysis came
when I took Arthur Lodge’s “Elastic Liquids” class. My third continuum mechanics
course, this time taught by Millard Johnson (U. Wisc), introduced me to the usefulness of
“Rossetta stone” type derivations of classic theorems, done using multiple notations to
make them clear to every reader. It was here where I conceded that no single notation is
superior, and I had better become darn good at them all. At Wisconsin, I took a class on
Greens functions and boundary value problems from the noted mathematician R. Dickey,
who really drove home the importance of projection operations in physical applications,
and instilled in me the irresistible habit of examining operators for their properties and
iv
Copyright is reserved. Individual copies may be made for personal use. No part of this document may be reproduced for profit.
classifying them as outlined in our class textbook [12]; it was Dickey who finally got me
into the habit of looking for analogies between seemingly unrelated operators and sets so
that my strong knowledge. Dickey himself got sideswiped by this habit when I solved one
of his exam questions by doing it using a technique that I had learned in Buck Schreyer’s
continuum mechanics class and which I realized would also work on the exam question by
merely re-interpreting the vector dot product as the inner product that applies for continu-
ous functions. As I walked into my Ph.D. defense, I warned Dickey (who was on my com-
mittee) that my thesis was really just a giant application of the projection theorem, and he
replied “most are, but you are distinguished by recognizing the fact!” Even though neither
this book nor very many of my other publications (aside from Ref. [6], of course) employ
curvilinear notation, my exposure to it has been invaluable to lend insight to the relation-
ship between so-called “convected coordinates” and “unconvected reference spaces” often
used in materials modeling. Having gotten my first exposure to tensoranalysis from read-
ing Bird’s polymer book, I naturally felt compelled to take his macromolecular fluid
dynamics course at U. Wisc, which solidified several concepts further. Bird’s course was
immediately followed by an applied analysis course, taught by ____, where more correct
“mathematician’s” viewpoints on tensoranalysis were drilled into me (the textbook for
this course [17] is outstanding, and don’t be swayed by the fact that “chemical engineer-
ing” is part of its title — the book applies to any field of physics). These and numerous
other academic mentors I’ve had throughout my career have given me a wonderfully bal-
anced set of analysis tools, and I wish I could thank them enough.
For the longest time, this “Acknowledgement” section said only “Acknowledgements
to be added. Stay tuned ” Assigning such low priority to the acknowledgements section
was a gross tactical error on my part. When my colleagues offered assistance and sugges-
tions in the earliest days of error-ridden rough drafts of this book, I thought to myself “I
should thank them in my acknowledgements section.” A few years later, I sit here trying to
recall the droves of early reviewers. I remember contributions from Glenn Randers-Pher-
son because his advice for one of my other publications proved to be incredibly helpful,
and he did the same for this more elementary document as well. A few folks (Mark Chris-
ten, Allen Robinson, Stewart Silling, Paul Taylor, Tim Trucano) in my former department
at Sandia National Labs also came forward with suggestions or helpful discussions that
were incorporated into this book. While in my new department at Sandia National Labora-
tories, I continued to gain new insight, especially from Dan Segalman and Bill Scherz-
inger.
Part of what has driven me to continue to improve this document has been the numer-
ous encouraging remarks (approximately one per week) that I have received from
researchers and students all over the world who have stumbled upon the pdf draft version
of this document that I originally wrote as a student’s guide when I taught Continuum
Mechanics at UNM. I don’t recall the names of people who sent me encouraging words in
the early days, but some recent folks are Ricardo Colorado, Vince Owens, Dave Dooli-
nand Mr. Jan Cox. Jan was especially inspiring because he was so enthusiastic about this
work that he spent an entire afternoon disscussing it with me after a business trip I made to
his home city, Oakland CA. Even some professors [such as Lynn Bennethum (U. Colo-
rado), Ron Smelser (U. Idaho), Tom Scarpas (TU Delft), Sanjay Arwad (JHU), Kaspar
William (U. Colorado), Walt Gerstle (U. New Mexico)] have told me that they have
v
directed their own students to the web version of this document as supplemental reading.
In Sept. 2002, Bob Cain sent me an email asking about printing issues of the web
draft; his email signature had the Einstein quote that you now see heading Chapter 1 of
this document. After getting his permission to also use that quote in my own document, I
was inspired to begin every chapter with an ice-breaker quote from my personal collec-
tion.
I still need to recognize the many folks who have sent
helpful emails over the last year. Stay tuned.
vi
Copyright is reserved. Individual copies may be made for personal use. No part of this document may be reproduced for profit.
Contents
Acknowledgments iii
Preface xv
Introduction 1
STRUCTURES and SUPERSTRUCTURES 2
What is a scalar? What is a vector? 5
What is a tensor? 6
Examples of tensors in materials mechanics 9
The stress tensor 9
The deformation gradient tensor 11
Vector andTensor notation — philosophy 12
Terminology from functionalanalysis 14
Matrix Analysis (and some matrix calculus) 21
Definition of a matrix 21
Component matrices associated with vectors and tensors (notation explanation) 22
The matrix product 22
SPECIAL CASE: a matrix times an array 22
SPECIAL CASE: inner product of two arrays 23
SPECIAL CASE: outer product of two arrays 23
EXAMPLE: 23
The Kronecker delta 25
The identity matrix 25
Derivatives of vector and matrix expressions 26
Derivative of an array with respect to itself 27
Derivative of a matrix with respect to itself 28
The transpose of a matrix 29
Derivative of the transpose: 29
The inner product of two column matrices 29
Derivatives of the inner product: 30
The outer product of two column matrices 31
The trace of a square matrix 31
Derivative of the trace 31
The matrix inner product 32
Derivative of the matrix inner product 32
Magnitudes and positivity property of the inner product 33
Derivative of the magnitude 34
Norms 34
Weighted or “energy” norms 35
Derivative of the energy norm 35
The 3D permutation symbol 36
The ε-δ (E-delta) identity 36
The ε-δ (E-delta) identity with multiple summed indices 38
Determinant of a square matrix 39
More about cofactors 42
Cofactor-inverse relationship 43
vii
Derivative of the cofactor 44
Derivative of a determinant (IMPORTANT) 44
Rates of determinants 45
Derivatives of determinants with respect to vectors 46
Principal sub-matrices and principal minors 46
Matrix invariants 46
Alternative invariant sets 47
Positive definite 47
The cofactor-determinant connection 48
Inverse 49
Eigenvalues and eigenvectors 49
Similarity transformations 51
Finding eigenvectors by using the adjugate 52
Eigenprojectors 53
Finding eigenprojectors without finding eigenvectors. 54
Vector/tensor notation 55
“Ordinary” engineering vectors 55
Engineering “laboratory” base vectors 55
Other choices for the base vectors 55
Basis expansion of a vector 56
Summation convention — details 57
Don’t forget what repeated indices really mean 58
Further special-situation summation rules 59
Indicial notation in derivatives 60
BEWARE: avoid implicit sums as independent variables 60
Reading index STRUCTURE, not index SYMBOLS 61
Aesthetic (courteous) indexing 62
Suspending the summation convention 62
Combining indicial equations 63
Index-changing properties of the Kronecker delta 64
Summing the Kronecker delta itself 69
Our (unconventional) “under-tilde” notation 69
Tensor invariant operations 69
Simple vector operations and properties 71
Dot product between two vectors 71
Dot product between orthonormal base vectors 72
A “quotient” rule (deciding if a vector is zero) 72
Deciding if one vector equals another vector 73
Finding the i-th component of a vector 73
Even and odd vector functions 74
Homogeneous functions 74
Vector orientation and sense 75
Simple scalar components 75
Cross product 76
Cross product between orthonormal base vectors 76
Triple scalar product 78
viii
Copyright is reserved. Individual copies may be made for personal use. No part of this document may be reproduced for profit.
Triple scalar product between orthonormal RIGHT-HANDED base vectors 79
Projections 80
Orthogonal (perpendicular) linear projections 80
Rank-1 orthogonal projections 82
Rank-2 orthogonal projections 83
Basis interpretation of orthogonal projections 83
Rank-2 oblique linear projection 84
Rank-1 oblique linear projection 85
Degenerate (trivial) Rank-0 linear projection 85
Degenerate (trivial) Rank-3 projection in 3D space 86
Complementary projectors 86
Normalized versions of the projectors 86
Expressing a vector as a linear combination of three arbitrary (not necessarily
orthonormal) vectors 88
Generalized projections 90
Linear projections 90
Nonlinear projections 90
The vector “signum” function 90
Gravitational (distorted light ray) projections 91
Self-adjoint projections 91
Gram-Schmidt orthogonalization 92
Special case: orthogonalization of two vectors 93
The projection theorem 93
Tensors 95
Analogy between tensors and other (more familiar) concepts 96
Linear operators (transformations) 99
Dyads and dyadic multiplication 103
Simpler “no-symbol” dyadic notation 104
The matrix associated with a dyad 104
The sum of dyads 105
A sum of two or three dyads is NOT (generally) reducible 106
Scalar multiplication of a dyad 106
The sum of four or more dyads is reducible! (not a superset) 107
The dyad definition of a second-order tensor 107
Expansion of a second-order tensor in terms of basis dyads 108
Triads and higher-order tensors 110
Our V
m
n
tensor “class” notation 111
Comment 114
Tensor operations 115
Dotting a tensor from the right by a vector 115
The transpose of a tensor 115
Dotting a tensor from the left by a vector 116
Dotting a tensor by vectors from both sides 117
Extracting a particular tensor component 117
Dotting a tensor into a tensor (tensor composition) 117
Tensor analysis primitives 119
[...]... product Fourth-order tensor inner product Fourth-order Sherman-Morrison formula Higher-order tensor inner product Self-defining notation The magnitude of a tensor or a vector Useful inner product identities Distinction between an Nth-order tensorand an Nth-rank tensor Fourth-order oblique tensor projections Leafing and palming operations... Symmetric and skew-symmetric tensors 155 Positive definite tensors 156 Faster way to check for positive definiteness 156 Positive semi-definite 157 Negative definite and negative semi-definite tensors 157 Isotropic and deviatoric tensors 158 Tensor operations 159 Second-order tensor inner product 159 ix A NON-recommended scalar-valued... Coordinate/basis transformations Change of basis (and coordinate transformations) EXAMPLE Definition of a vector and a tensor Basis coupling tensorTensor (and Tensor function) invariance What’s the difference between a matrix and a tensor? Example of a “scalar rule” that satisfies tensor invariance Example of a “scalar rule” that violates tensor invariance... may be reproduced for profit T AFT DR ann ca Br Rebec July 11, 2003 1:03 pm Preface on xvi Copyright is reserved Individual copies may be made for personal use No part of this document may be reproduced for profit DRAF September 4, 2003 5:24 pm Introduction Rebec FUNCTIONALAND STRUCTURED TENSORANALYSIS FOR ENGINEERS: a casual (intuition-based) introduction to vector andtensoranalysis with reviews... Vector, tensor, and matrix analysis are subsets of a more general area of study called functionalanalysis One purpose of this book is to specialize several overly-general results from functionalanalysis into forms that are the more convenient for “real world” engineering applications where generalized abstract formulas or notations are not only not necessary, but also damned distracting Functional analysis. .. complementary projection tensors 143 Self-adjoint (orthogonal) projectors 143 Non-self-adjoint (oblique) projectors 144 Generalized complementary projectors 145 More Tensor primitives 147 Tensor properties 147 Orthogonal (unitary) tensors 148 Tensor associated with the cross product 151 Cross-products in left-handed and general bases...Three kinds of vector andtensor notation 119 REPRESENTATION THEOREM for linear forms 122 Representation theorem for vector-to-scalar linear functions 123 Advanced Representation Theorem (to be read once you learn about higher-order tensors and the Vmn class notation) 124 Finding the tensor associated with a linear function 125 Method... Quantities such as A or T with two ˜under-tildes are second˜ ˜ order tensors In general, the number of under-tildes beneath a symbol indicates to you the order of that tensor (for this reason, scalars are sometimes called zeroth-order tensors and vectors are called first-order tensors) Occasionally, we will want to make statements that apply equally well to tensors of any order In that case, we might... of the deformation gradient tensor Of course, this is only a qualitative description of the deformation gradient tensor A more classical (and quantified) definition of the deformation gradient tensor starts with the assertion that each point x in the currently deformed ˜ body must have come from some unique initial location X in the initial undeformed refer˜ ence configuration, you can therefore claim... meaning of the tensor too (i.e., how it shows how squares deform to parallelepipeds) All that is needed to determine the components of this (or any) tensor is knowledge of how that transformation changes any three linearly independent vectors Vector andTensor notation — philosophy This section may be skipped You may go directly to page 21 without loss Tensor notation unfortunately remains non-standardized, . community effort. Let’s try to make this document helpful to others. FUNCTIONAL AND STRUCTURED TENSOR ANALYSIS FOR ENGINEERS A casual (intuition-based) introduction to vector and tensor analysis. made for personal use. No part of this document may be reproduced for profit. FUNCTIONAL AND STRUCTURED TENSOR ANALYSIS FOR ENGINEERS: a casual (intuition-based) introduction to vector and tensor. Functional and Structured Tensor Analysis for Engineers A casual (intuition-based) introduction to vector and tensor analysis with reviews of popular notations