where index notation is the shorthand for dealing with tensors and vectors; a variable with a single subscript is a vector a = a i

Size: px
Start display at page:

Download "where index notation is the shorthand for dealing with tensors and vectors; a variable with a single subscript is a vector a = a i"

Transcription

1 1 Brief Review of Elasticity (Copyright 2009, David T Sandwell) This is a very brief review of the elasticity theory needed to understand the principles of stress, strain, and flexure in Geodynamics [Turcotte and Schubert, 2002] This review assumes that you have already taken a class in continuum mechanics One difference from T&S is that we follow the sign convention used by seismologists and engineers where extensional strain and stress is positive Stress Stress is a force acting on an area is measured in Newtons per meter squared (N m 2 ) which corresponds to a Pascal unit (Pa) The following diagram shows a cube of solid material Each face of the cube has three components of stress so there are 9 possible components of the stress tensor We will consider only the symmetric part of the stress tensor so only 6 of these components are independent The antisymmetric part of the tensor represents a torque In Cartesian coordinates the stress tensor is given by σ xx σ ij = σ zz where index notation is the shorthand for dealing with tensors and vectors; a variable with a single subscript is a vector a = a i, a variable with two subscripts is a tensor σ = σ ij, and a repeated index indicates summation over the spatial coordinates For example the pressure is given by P = σ ii / 3 In addition, a comma preceding a subscript means differentiation with respect to that variable a = a i, j or for example a x,y = a x y

2 2 Strain Strain is change in length over the original length so it is a dimensionless variable and we will assume strains are small (<< 10-3 ) Let the displacement vector field inside of a solid body be given by u = u i = [ u x u y u z ] The gradient of this vector is a tensor u = u i, j This tensor is commonly decomposed into a symmetric tensor (strain) and an antisymmetric tensor (rotation) u i, j = 1 u i + u j 2 x j x i + 1 u i u j 2 x j x i We will not consider the rotation tensor further but the strain tensor is given by ε ij 2 u i, j + u j,i ) Stress vs strain If one assumes the material has an isotropic and linear response then the relationship between stress and strain is given by σ ij = λδ ij ε kk + 2µε ij where δ ij is equal to 0 except when i=j and then it is equal to 1 The Lame constants λ and µ define the elastic properties The shear modulus µ (or G in the engineering literature) relates the shear stress to shear strain on a component by component basis = 2µε xy = µ u x y + u y x Invariants and principal stress This general relation between stress and strain tensors is rather involved and it is difficult to invert this relationship to develop a relationship between strain and stress One means of simplifying this relationship is to find a co-ordinate system rotation that will cause the stress and strain tensors to be diagonal Let R be a rotation matrix such that R t R = I is the identity matrix There are three properties (invariants) of the stress tensor that do not change under co-ordinate rotation The invariants are found by first developing the characteristic equation from the determinant of the following equation

3 3 σ xx γ γ γ = 0 which becomes γ 3 Iγ 2 + IIγ III = 0 where the stress invariants are I = σ ii II 2 σ iiσ jj σ ij σ ij ) = σ xx + + σ xx σ 2 xy σ 2 2 yz III = σ ij the trace I, the sum of minors II, and the determinant of the stress tensor III The first invariant is related to the mean normal stress or pressure P = σ ii / 3 The second invariant is related to shear stress and thus is commonly used as the Von Mises failure criteria We will not consider the third invariant further Real symmetric matrices have real eigenvalues, orthogonal eigenvectors, and can be diagonalized This implies that there always exists some principal coordinate system where the the shear stresses are zero on planes orthogonal to the coordinate axes and where the normal stresses act along the principal axes directions (the eigenvectors) form the rotation matrix R The eigenvalues form the principal stress tensor σ p = σ σ 3 = R t σr where σ 2 σ 3 The principal stress system is important in geophysics and geology Due to the presence of the free surface, the stress field close to the Earth's surface is expected to have one principal stress vertical and hence two horizontal principal stresses Also in the earth we sometimes subtract the pressure from the stress tensor In this case it is called deviatoric stress In the principal stress system the pressure and maximum shear stress are given by

4 4 P = 1 ( 3 σ + σ + 2 3) τ 2 σ 3) Principal stress and strain The stress versus strain relation is far simpler in the principal co-ordinate system σ 2 σ 3 = λ + 2µ λ λ λ λ + 2µ λ λ λ λ + 2µ ε 2 ε 3 where, ε 2, and ε 3 are the principal strains Next we can use this relationship to develop three important parameters, Poisson s ratio ν, Young s modulus E, and bulk modulus K First consider the case of uniaxial stress where σ 2 = σ 3 = 0 This represents application of an end load to an elastic beam fastened to a wall The second equation for σ 2 is 0 = λ + ( λ + 2µ )ε 2 + λε 3 Because of symmetry we know ε 2 = ε 3 so we arrive at a relationship between ε 2 and ε 2 = λ 2( λ + µ ) ε = ν 1 where ν is Poisson s ratio Next we can use this relationship between strains in the first equation to provide a relationship between and = ( λ + 2µ ) + λ 2 λ + µ ( )( λ + µ ) λ 2 = λ + 2µ λ + µ ( ) λ + µ µ 3λ + 2µ = = E

5 5 where E is Young s modulus ( ) / 3 is related to a change in volume ΔV = ( + ε 2 + ε 3 ) Using the stress- Next we consider the case of uniform pressure ΔP = + σ 2 + σ 3 strain relation we find In this case, the change in pressure ΔP = λ µ ΔV ΔP = KΔV where K is the bulk modulus One can invert this stress vs strain relationship to obtain a strain vs stress relationship We ll also assume that the principal co-ordinates are aligned with the x-, y-, and z- axes ε xx ε yy ε zz = 1 E 1 ν ν ν 1 ν ν ν 1 σ xx Now we have arrived at equations 3-4, 3-5, and 3-6 in T&S Before moving onto the flexure problem we consider the case of a thin elastic plate Thin plate means that there are no variations in the vertical displacement field as a function of depth in the plate so we can make the approximation = 0 Under this approximation we have the following ε xx E σ vσ xx yy ) ε yy E σ v xx ) ε zz = ν E ( σ + σ xx yy )

State of Stress at Point

State of Stress at Point State of Stress at Point Einstein Notation The basic idea of Einstein notation is that a covector and a vector can form a scalar: This is typically written as an explicit sum: According to this convention,

More information

Mechanical Properties - Stresses & Strains

Mechanical Properties - Stresses & Strains Mechanical Properties - Stresses & Strains Types of Deformation : Elasic Plastic Anelastic Elastic deformation is defined as instantaneous recoverable deformation Hooke's law : For tensile loading, σ =

More information

Elasticity Theory Basics

Elasticity Theory Basics G22.3033-002: Topics in Computer Graphics: Lecture #7 Geometric Modeling New York University Elasticity Theory Basics Lecture #7: 20 October 2003 Lecturer: Denis Zorin Scribe: Adrian Secord, Yotam Gingold

More information

1 of 79 Erik Eberhardt UBC Geological Engineering EOSC 433

1 of 79 Erik Eberhardt UBC Geological Engineering EOSC 433 Stress & Strain: A review xx yz zz zx zy xy xz yx yy xx yy zz 1 of 79 Erik Eberhardt UBC Geological Engineering EOSC 433 Disclaimer before beginning your problem assignment: Pick up and compare any set

More information

Unit 3 (Review of) Language of Stress/Strain Analysis

Unit 3 (Review of) Language of Stress/Strain Analysis Unit 3 (Review of) Language of Stress/Strain Analysis Readings: B, M, P A.2, A.3, A.6 Rivello 2.1, 2.2 T & G Ch. 1 (especially 1.7) Paul A. Lagace, Ph.D. Professor of Aeronautics & Astronautics and Engineering

More information

Adding vectors We can do arithmetic with vectors. We ll start with vector addition and related operations. Suppose you have two vectors

Adding vectors We can do arithmetic with vectors. We ll start with vector addition and related operations. Suppose you have two vectors 1 Chapter 13. VECTORS IN THREE DIMENSIONAL SPACE Let s begin with some names and notation for things: R is the set (collection) of real numbers. We write x R to mean that x is a real number. A real number

More information

A Primer on Index Notation

A Primer on Index Notation A Primer on John Crimaldi August 28, 2006 1. Index versus Index notation (a.k.a. Cartesian notation) is a powerful tool for manipulating multidimensional equations. However, there are times when the more

More information

[1] Diagonal factorization

[1] Diagonal factorization 8.03 LA.6: Diagonalization and Orthogonal Matrices [ Diagonal factorization [2 Solving systems of first order differential equations [3 Symmetric and Orthonormal Matrices [ Diagonal factorization Recall:

More information

Scalars, Vectors and Tensors

Scalars, Vectors and Tensors Scalars, Vectors and Tensors A scalar is a physical quantity that it represented by a dimensional number at a particular point in space and time. Examples are hydrostatic pressure and temperature. A vector

More information

12.510 Introduction to Seismology Spring 2008

12.510 Introduction to Seismology Spring 2008 MIT OpenCourseWare http://ocw.mit.edu 12.510 Introduction to Seismology Spring 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 04/30/2008 Today s

More information

Unit 6 Plane Stress and Plane Strain

Unit 6 Plane Stress and Plane Strain Unit 6 Plane Stress and Plane Strain Readings: T & G 8, 9, 10, 11, 12, 14, 15, 16 Paul A. Lagace, Ph.D. Professor of Aeronautics & Astronautics and Engineering Systems There are many structural configurations

More information

1 2 3 1 1 2 x = + x 2 + x 4 1 0 1

1 2 3 1 1 2 x = + x 2 + x 4 1 0 1 (d) If the vector b is the sum of the four columns of A, write down the complete solution to Ax = b. 1 2 3 1 1 2 x = + x 2 + x 4 1 0 0 1 0 1 2. (11 points) This problem finds the curve y = C + D 2 t which

More information

When the fluid velocity is zero, called the hydrostatic condition, the pressure variation is due only to the weight of the fluid.

When the fluid velocity is zero, called the hydrostatic condition, the pressure variation is due only to the weight of the fluid. Fluid Statics When the fluid velocity is zero, called the hydrostatic condition, the pressure variation is due only to the weight of the fluid. Consider a small wedge of fluid at rest of size Δx, Δz, Δs

More information

Figure 1.1 Vector A and Vector F

Figure 1.1 Vector A and Vector F CHAPTER I VECTOR QUANTITIES Quantities are anything which can be measured, and stated with number. Quantities in physics are divided into two types; scalar and vector quantities. Scalar quantities have

More information

5.04 Principles of Inorganic Chemistry II

5.04 Principles of Inorganic Chemistry II MIT OpenourseWare http://ocw.mit.edu 5.4 Principles of Inorganic hemistry II Fall 8 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 5.4, Principles of

More information

9.4. The Scalar Product. Introduction. Prerequisites. Learning Style. Learning Outcomes

9.4. The Scalar Product. Introduction. Prerequisites. Learning Style. Learning Outcomes The Scalar Product 9.4 Introduction There are two kinds of multiplication involving vectors. The first is known as the scalar product or dot product. This is so-called because when the scalar product of

More information

Finite Element Formulation for Plates - Handout 3 -

Finite Element Formulation for Plates - Handout 3 - Finite Element Formulation for Plates - Handout 3 - Dr Fehmi Cirak (fc286@) Completed Version Definitions A plate is a three dimensional solid body with one of the plate dimensions much smaller than the

More information

3 Concepts of Stress Analysis

3 Concepts of Stress Analysis 3 Concepts of Stress Analysis 3.1 Introduction Here the concepts of stress analysis will be stated in a finite element context. That means that the primary unknown will be the (generalized) displacements.

More information

Plates and Shells: Theory and Computation - 4D9 - Dr Fehmi Cirak (fc286@) Office: Inglis building mezzanine level (INO 31)

Plates and Shells: Theory and Computation - 4D9 - Dr Fehmi Cirak (fc286@) Office: Inglis building mezzanine level (INO 31) Plates and Shells: Theory and Computation - 4D9 - Dr Fehmi Cirak (fc286@) Office: Inglis building mezzanine level (INO 31) Outline -1-! This part of the module consists of seven lectures and will focus

More information

9 MATRICES AND TRANSFORMATIONS

9 MATRICES AND TRANSFORMATIONS 9 MATRICES AND TRANSFORMATIONS Chapter 9 Matrices and Transformations Objectives After studying this chapter you should be able to handle matrix (and vector) algebra with confidence, and understand the

More information

DATA ANALYSIS II. Matrix Algorithms

DATA ANALYSIS II. Matrix Algorithms DATA ANALYSIS II Matrix Algorithms Similarity Matrix Given a dataset D = {x i }, i=1,..,n consisting of n points in R d, let A denote the n n symmetric similarity matrix between the points, given as where

More information

Analysis of Stresses and Strains

Analysis of Stresses and Strains Chapter 7 Analysis of Stresses and Strains 7.1 Introduction axial load = P / A torsional load in circular shaft = T / I p bending moment and shear force in beam = M y / I = V Q / I b in this chapter, we

More information

EDEXCEL NATIONAL CERTIFICATE/DIPLOMA MECHANICAL PRINCIPLES AND APPLICATIONS NQF LEVEL 3 OUTCOME 1 - LOADING SYSTEMS

EDEXCEL NATIONAL CERTIFICATE/DIPLOMA MECHANICAL PRINCIPLES AND APPLICATIONS NQF LEVEL 3 OUTCOME 1 - LOADING SYSTEMS EDEXCEL NATIONAL CERTIFICATE/DIPLOMA MECHANICAL PRINCIPLES AND APPLICATIONS NQF LEVEL 3 OUTCOME 1 - LOADING SYSTEMS TUTORIAL 1 NON-CONCURRENT COPLANAR FORCE SYSTEMS 1. Be able to determine the effects

More information

The Matrix Elements of a 3 3 Orthogonal Matrix Revisited

The Matrix Elements of a 3 3 Orthogonal Matrix Revisited Physics 116A Winter 2011 The Matrix Elements of a 3 3 Orthogonal Matrix Revisited 1. Introduction In a class handout entitled, Three-Dimensional Proper and Improper Rotation Matrices, I provided a derivation

More information

The elements used in commercial codes can be classified in two basic categories:

The elements used in commercial codes can be classified in two basic categories: CHAPTER 3 Truss Element 3.1 Introduction The single most important concept in understanding FEA, is the basic understanding of various finite elements that we employ in an analysis. Elements are used for

More information

Lap Fillet Weld Calculations and FEA Techniques

Lap Fillet Weld Calculations and FEA Techniques Lap Fillet Weld Calculations and FEA Techniques By: MS.ME Ahmad A. Abbas Sr. Analysis Engineer Ahmad.Abbas@AdvancedCAE.com www.advancedcae.com Sunday, July 11, 2010 Advanced CAE All contents Copyright

More information

Differential Relations for Fluid Flow. Acceleration field of a fluid. The differential equation of mass conservation

Differential Relations for Fluid Flow. Acceleration field of a fluid. The differential equation of mass conservation Differential Relations for Fluid Flow In this approach, we apply our four basic conservation laws to an infinitesimally small control volume. The differential approach provides point by point details of

More information

Plane Stress Transformations

Plane Stress Transformations 6 Plane Stress Transformations ASEN 311 - Structures ASEN 311 Lecture 6 Slide 1 Plane Stress State ASEN 311 - Structures Recall that in a bod in plane stress, the general 3D stress state with 9 components

More information

Høgskolen i Narvik Sivilingeniørutdanningen

Høgskolen i Narvik Sivilingeniørutdanningen Høgskolen i Narvik Sivilingeniørutdanningen Eksamen i Faget STE66 ELASTISITETSTEORI Klasse: 4.ID Dato: 7.0.009 Tid: Kl. 09.00 1.00 Tillatte hjelpemidler under eksamen: Kalkulator Kopi av Boken Mechanics

More information

Notes on Orthogonal and Symmetric Matrices MENU, Winter 2013

Notes on Orthogonal and Symmetric Matrices MENU, Winter 2013 Notes on Orthogonal and Symmetric Matrices MENU, Winter 201 These notes summarize the main properties and uses of orthogonal and symmetric matrices. We covered quite a bit of material regarding these topics,

More information

Stress Analysis, Strain Analysis, and Shearing of Soils

Stress Analysis, Strain Analysis, and Shearing of Soils C H A P T E R 4 Stress Analysis, Strain Analysis, and Shearing of Soils Ut tensio sic vis (strains and stresses are related linearly). Robert Hooke So I think we really have to, first, make some new kind

More information

Objectives. Experimentally determine the yield strength, tensile strength, and modules of elasticity and ductility of given materials.

Objectives. Experimentally determine the yield strength, tensile strength, and modules of elasticity and ductility of given materials. Lab 3 Tension Test Objectives Concepts Background Experimental Procedure Report Requirements Discussion Objectives Experimentally determine the yield strength, tensile strength, and modules of elasticity

More information

MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set.

MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set. MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set. Vector space A vector space is a set V equipped with two operations, addition V V (x,y) x + y V and scalar

More information

Introduction to Matrix Algebra

Introduction to Matrix Algebra Psychology 7291: Multivariate Statistics (Carey) 8/27/98 Matrix Algebra - 1 Introduction to Matrix Algebra Definitions: A matrix is a collection of numbers ordered by rows and columns. It is customary

More information

α = u v. In other words, Orthogonal Projection

α = u v. In other words, Orthogonal Projection Orthogonal Projection Given any nonzero vector v, it is possible to decompose an arbitrary vector u into a component that points in the direction of v and one that points in a direction orthogonal to v

More information

Similar matrices and Jordan form

Similar matrices and Jordan form Similar matrices and Jordan form We ve nearly covered the entire heart of linear algebra once we ve finished singular value decompositions we ll have seen all the most central topics. A T A is positive

More information

Feature Commercial codes In-house codes

Feature Commercial codes In-house codes A simple finite element solver for thermo-mechanical problems Keywords: Scilab, Open source software, thermo-elasticity Introduction In this paper we would like to show how it is possible to develop a

More information

1 The basic equations of fluid dynamics

1 The basic equations of fluid dynamics 1 The basic equations of fluid dynamics The main task in fluid dynamics is to find the velocity field describing the flow in a given domain. To do this, one uses the basic equations of fluid flow, which

More information

Eigenvalues, Eigenvectors, Matrix Factoring, and Principal Components

Eigenvalues, Eigenvectors, Matrix Factoring, and Principal Components Eigenvalues, Eigenvectors, Matrix Factoring, and Principal Components The eigenvalues and eigenvectors of a square matrix play a key role in some important operations in statistics. In particular, they

More information

Chapter 6. Orthogonality

Chapter 6. Orthogonality 6.3 Orthogonal Matrices 1 Chapter 6. Orthogonality 6.3 Orthogonal Matrices Definition 6.4. An n n matrix A is orthogonal if A T A = I. Note. We will see that the columns of an orthogonal matrix must be

More information

Analysis of Stress CHAPTER 1 1.1 INTRODUCTION

Analysis of Stress CHAPTER 1 1.1 INTRODUCTION CHAPTER 1 Analysis of Stress 1.1 INTRODUCTION The basic structure of matter is characterized by nonuniformity and discontinuity attributable to its various subdivisions: molecules, atoms, and subatomic

More information

Elastic Wave Propagation

Elastic Wave Propagation Introduction to Elastic Wave Propagation A Bedford & D S Drumheller This document contains the complete text of the book published in 1994 by John Wiley & Sons Ltd, Chichester, England It has been edited

More information

CBE 6333, R. Levicky 1. Tensor Notation.

CBE 6333, R. Levicky 1. Tensor Notation. CBE 6333, R. Levicky 1 Tensor Notation. Engineers and scientists find it useful to have a general terminology to indicate how many directions are associated with a physical quantity such as temperature

More information

LS.6 Solution Matrices

LS.6 Solution Matrices LS.6 Solution Matrices In the literature, solutions to linear systems often are expressed using square matrices rather than vectors. You need to get used to the terminology. As before, we state the definitions

More information

Shear Center in Thin-Walled Beams Lab

Shear Center in Thin-Walled Beams Lab Shear Center in Thin-Walled Beams Lab Shear flow is developed in beams with thin-walled cross sections shear flow (q sx ): shear force per unit length along cross section q sx =τ sx t behaves much like

More information

Question 2: How do you solve a matrix equation using the matrix inverse?

Question 2: How do you solve a matrix equation using the matrix inverse? Question : How do you solve a matrix equation using the matrix inverse? In the previous question, we wrote systems of equations as a matrix equation AX B. In this format, the matrix A contains the coefficients

More information

15.062 Data Mining: Algorithms and Applications Matrix Math Review

15.062 Data Mining: Algorithms and Applications Matrix Math Review .6 Data Mining: Algorithms and Applications Matrix Math Review The purpose of this document is to give a brief review of selected linear algebra concepts that will be useful for the course and to develop

More information

Linear Algebra Review. Vectors

Linear Algebra Review. Vectors Linear Algebra Review By Tim K. Marks UCSD Borrows heavily from: Jana Kosecka kosecka@cs.gmu.edu http://cs.gmu.edu/~kosecka/cs682.html Virginia de Sa Cogsci 8F Linear Algebra review UCSD Vectors The length

More information

Plate waves in phononic crystals slabs

Plate waves in phononic crystals slabs Acoustics 8 Paris Plate waves in phononic crystals slabs J.-J. Chen and B. Bonello CNRS and Paris VI University, INSP - 14 rue de Lourmel, 7515 Paris, France chen99nju@gmail.com 41 Acoustics 8 Paris We

More information

ES240 Solid Mechanics Fall 2007. Stress field and momentum balance. Imagine the three-dimensional body again. At time t, the material particle ( x, y,

ES240 Solid Mechanics Fall 2007. Stress field and momentum balance. Imagine the three-dimensional body again. At time t, the material particle ( x, y, S40 Solid Mechanics Fall 007 Stress field and momentum balance. Imagine the three-dimensional bod again. At time t, the material particle,, ) is under a state of stress ij,,, force per unit volume b b,,,.

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS Systems of Equations and Matrices Representation of a linear system The general system of m equations in n unknowns can be written a x + a 2 x 2 + + a n x n b a

More information

Review Jeopardy. Blue vs. Orange. Review Jeopardy

Review Jeopardy. Blue vs. Orange. Review Jeopardy Review Jeopardy Blue vs. Orange Review Jeopardy Jeopardy Round Lectures 0-3 Jeopardy Round $200 How could I measure how far apart (i.e. how different) two observations, y 1 and y 2, are from each other?

More information

The Basics of FEA Procedure

The Basics of FEA Procedure CHAPTER 2 The Basics of FEA Procedure 2.1 Introduction This chapter discusses the spring element, especially for the purpose of introducing various concepts involved in use of the FEA technique. A spring

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS 1. SYSTEMS OF EQUATIONS AND MATRICES 1.1. Representation of a linear system. The general system of m equations in n unknowns can be written a 11 x 1 + a 12 x 2 +

More information

Introduction to Solid Modeling Using SolidWorks 2012 SolidWorks Simulation Tutorial Page 1

Introduction to Solid Modeling Using SolidWorks 2012 SolidWorks Simulation Tutorial Page 1 Introduction to Solid Modeling Using SolidWorks 2012 SolidWorks Simulation Tutorial Page 1 In this tutorial, we will use the SolidWorks Simulation finite element analysis (FEA) program to analyze the response

More information

is in plane V. However, it may be more convenient to introduce a plane coordinate system in V.

is in plane V. However, it may be more convenient to introduce a plane coordinate system in V. .4 COORDINATES EXAMPLE Let V be the plane in R with equation x +2x 2 +x 0, a two-dimensional subspace of R. We can describe a vector in this plane by its spatial (D)coordinates; for example, vector x 5

More information

Vector and Tensor Algebra (including Column and Matrix Notation)

Vector and Tensor Algebra (including Column and Matrix Notation) Vector and Tensor Algebra (including Column and Matrix Notation) 2 Vectors and tensors In mechanics and other fields of physics, quantities are represented by vectors and tensors. Essential manipulations

More information

13 MATH FACTS 101. 2 a = 1. 7. The elements of a vector have a graphical interpretation, which is particularly easy to see in two or three dimensions.

13 MATH FACTS 101. 2 a = 1. 7. The elements of a vector have a graphical interpretation, which is particularly easy to see in two or three dimensions. 3 MATH FACTS 0 3 MATH FACTS 3. Vectors 3.. Definition We use the overhead arrow to denote a column vector, i.e., a linear segment with a direction. For example, in three-space, we write a vector in terms

More information

Lecture L26-3D Rigid Body Dynamics: The Inertia Tensor

Lecture L26-3D Rigid Body Dynamics: The Inertia Tensor J. Peraire, S. Widnall 16.07 Dynaics Fall 008 Lecture L6-3D Rigid Body Dynaics: The Inertia Tensor Version.1 In this lecture, we will derive an expression for the angular oentu of a 3D rigid body. We shall

More information

Inner Product Spaces and Orthogonality

Inner Product Spaces and Orthogonality Inner Product Spaces and Orthogonality week 3-4 Fall 2006 Dot product of R n The inner product or dot product of R n is a function, defined by u, v a b + a 2 b 2 + + a n b n for u a, a 2,, a n T, v b,

More information

Linear algebra and the geometry of quadratic equations. Similarity transformations and orthogonal matrices

Linear algebra and the geometry of quadratic equations. Similarity transformations and orthogonal matrices MATH 30 Differential Equations Spring 006 Linear algebra and the geometry of quadratic equations Similarity transformations and orthogonal matrices First, some things to recall from linear algebra Two

More information

8.2 Elastic Strain Energy

8.2 Elastic Strain Energy Section 8. 8. Elastic Strain Energy The strain energy stored in an elastic material upon deformation is calculated below for a number of different geometries and loading conditions. These expressions for

More information

STATISTICS AND DATA ANALYSIS IN GEOLOGY, 3rd ed. Clarificationof zonationprocedure described onpp. 238-239

STATISTICS AND DATA ANALYSIS IN GEOLOGY, 3rd ed. Clarificationof zonationprocedure described onpp. 238-239 STATISTICS AND DATA ANALYSIS IN GEOLOGY, 3rd ed. by John C. Davis Clarificationof zonationprocedure described onpp. 38-39 Because the notation used in this section (Eqs. 4.8 through 4.84) is inconsistent

More information

by the matrix A results in a vector which is a reflection of the given

by the matrix A results in a vector which is a reflection of the given Eigenvalues & Eigenvectors Example Suppose Then So, geometrically, multiplying a vector in by the matrix A results in a vector which is a reflection of the given vector about the y-axis We observe that

More information

Advanced Structural Analysis. Prof. Devdas Menon. Department of Civil Engineering. Indian Institute of Technology, Madras. Module - 5.3.

Advanced Structural Analysis. Prof. Devdas Menon. Department of Civil Engineering. Indian Institute of Technology, Madras. Module - 5.3. Advanced Structural Analysis Prof. Devdas Menon Department of Civil Engineering Indian Institute of Technology, Madras Module - 5.3 Lecture - 29 Matrix Analysis of Beams and Grids Good morning. This is

More information

Linear Algebra: Vectors

Linear Algebra: Vectors A Linear Algebra: Vectors A Appendix A: LINEAR ALGEBRA: VECTORS TABLE OF CONTENTS Page A Motivation A 3 A2 Vectors A 3 A2 Notational Conventions A 4 A22 Visualization A 5 A23 Special Vectors A 5 A3 Vector

More information

Vector Calculus: a quick review

Vector Calculus: a quick review Appendi A Vector Calculus: a quick review Selected Reading H.M. Sche,. Div, Grad, Curl and all that: An informal Tet on Vector Calculus, W.W. Norton and Co., (1973). (Good phsical introduction to the subject)

More information

Rotation Matrices and Homogeneous Transformations

Rotation Matrices and Homogeneous Transformations Rotation Matrices and Homogeneous Transformations A coordinate frame in an n-dimensional space is defined by n mutually orthogonal unit vectors. In particular, for a two-dimensional (2D) space, i.e., n

More information

Vector and Matrix Norms

Vector and Matrix Norms Chapter 1 Vector and Matrix Norms 11 Vector Spaces Let F be a field (such as the real numbers, R, or complex numbers, C) with elements called scalars A Vector Space, V, over the field F is a non-empty

More information

Similarity and Diagonalization. Similar Matrices

Similarity and Diagonalization. Similar Matrices MATH022 Linear Algebra Brief lecture notes 48 Similarity and Diagonalization Similar Matrices Let A and B be n n matrices. We say that A is similar to B if there is an invertible n n matrix P such that

More information

MCE380: Measurements and Instrumentation Lab. Chapter 9: Force, Torque and Strain Measurements

MCE380: Measurements and Instrumentation Lab. Chapter 9: Force, Torque and Strain Measurements MCE380: Measurements and Instrumentation Lab Chapter 9: Force, Torque and Strain Measurements Topics: Elastic Elements for Force Measurement Dynamometers and Brakes Resistance Strain Gages Holman, Ch.

More information

MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets.

MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets. MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets. Norm The notion of norm generalizes the notion of length of a vector in R n. Definition. Let V be a vector space. A function α

More information

4.3 Results... 27 4.3.1 Drained Conditions... 27 4.3.2 Undrained Conditions... 28 4.4 References... 30 4.5 Data Files... 30 5 Undrained Analysis of

4.3 Results... 27 4.3.1 Drained Conditions... 27 4.3.2 Undrained Conditions... 28 4.4 References... 30 4.5 Data Files... 30 5 Undrained Analysis of Table of Contents 1 One Dimensional Compression of a Finite Layer... 3 1.1 Problem Description... 3 1.1.1 Uniform Mesh... 3 1.1.2 Graded Mesh... 5 1.2 Analytical Solution... 6 1.3 Results... 6 1.3.1 Uniform

More information

Chapter 11 Equilibrium

Chapter 11 Equilibrium 11.1 The First Condition of Equilibrium The first condition of equilibrium deals with the forces that cause possible translations of a body. The simplest way to define the translational equilibrium of

More information

2.75 6.525 Problem Set 1 Solutions to ME problems Fall 2013

2.75 6.525 Problem Set 1 Solutions to ME problems Fall 2013 2.75 6.525 Problem Set 1 Solutions to ME problems Fall 2013 2. Pinned Joint problem Jacob Bayless a) Draw a free-body diagram for the pin. How is it loaded? Does the loading depend on whether the pin is

More information

MATH 551 - APPLIED MATRIX THEORY

MATH 551 - APPLIED MATRIX THEORY MATH 55 - APPLIED MATRIX THEORY FINAL TEST: SAMPLE with SOLUTIONS (25 points NAME: PROBLEM (3 points A web of 5 pages is described by a directed graph whose matrix is given by A Do the following ( points

More information

Stress-Strain Material Laws

Stress-Strain Material Laws 5 Stress-Strain Material Laws 5 Lecture 5: STRSS-STRAIN MATRIAL LAWS TABL OF CONTNTS Page 5. Introduction..................... 5 3 5.2 Constitutive quations................. 5 3 5.2. Material Behavior

More information

Technology of EHIS (stamping) applied to the automotive parts production

Technology of EHIS (stamping) applied to the automotive parts production Laboratory of Applied Mathematics and Mechanics Technology of EHIS (stamping) applied to the automotive parts production Churilova Maria, Saint-Petersburg State Polytechnical University Department of Applied

More information

3. Let A and B be two n n orthogonal matrices. Then prove that AB and BA are both orthogonal matrices. Prove a similar result for unitary matrices.

3. Let A and B be two n n orthogonal matrices. Then prove that AB and BA are both orthogonal matrices. Prove a similar result for unitary matrices. Exercise 1 1. Let A be an n n orthogonal matrix. Then prove that (a) the rows of A form an orthonormal basis of R n. (b) the columns of A form an orthonormal basis of R n. (c) for any two vectors x,y R

More information

Inner products on R n, and more

Inner products on R n, and more Inner products on R n, and more Peyam Ryan Tabrizian Friday, April 12th, 2013 1 Introduction You might be wondering: Are there inner products on R n that are not the usual dot product x y = x 1 y 1 + +

More information

CONTROLLABILITY. Chapter 2. 2.1 Reachable Set and Controllability. Suppose we have a linear system described by the state equation

CONTROLLABILITY. Chapter 2. 2.1 Reachable Set and Controllability. Suppose we have a linear system described by the state equation Chapter 2 CONTROLLABILITY 2 Reachable Set and Controllability Suppose we have a linear system described by the state equation ẋ Ax + Bu (2) x() x Consider the following problem For a given vector x in

More information

The Singular Value Decomposition in Symmetric (Löwdin) Orthogonalization and Data Compression

The Singular Value Decomposition in Symmetric (Löwdin) Orthogonalization and Data Compression The Singular Value Decomposition in Symmetric (Löwdin) Orthogonalization and Data Compression The SVD is the most generally applicable of the orthogonal-diagonal-orthogonal type matrix decompositions Every

More information

1 Introduction to Matrices

1 Introduction to Matrices 1 Introduction to Matrices In this section, important definitions and results from matrix algebra that are useful in regression analysis are introduced. While all statements below regarding the columns

More information

Brief Review of Tensors

Brief Review of Tensors Appendix A Brief Review of Tensors A1 Introductory Remarks In the study of particle mechanics and the mechanics of solid rigid bodies vector notation provides a convenient means for describing many physical

More information

521493S Computer Graphics. Exercise 2 & course schedule change

521493S Computer Graphics. Exercise 2 & course schedule change 521493S Computer Graphics Exercise 2 & course schedule change Course Schedule Change Lecture from Wednesday 31th of March is moved to Tuesday 30th of March at 16-18 in TS128 Question 2.1 Given two nonparallel,

More information

6. Vectors. 1 2009-2016 Scott Surgent (surgent@asu.edu)

6. Vectors. 1 2009-2016 Scott Surgent (surgent@asu.edu) 6. Vectors For purposes of applications in calculus and physics, a vector has both a direction and a magnitude (length), and is usually represented as an arrow. The start of the arrow is the vector s foot,

More information

The Matrix Stiffness Method for 2D Trusses

The Matrix Stiffness Method for 2D Trusses The Matrix Stiffness Method for D Trusses Method CEE 4L. Matrix Structural Analysis Department of Civil and Environmental Engineering Duke University Henri P. Gavin Fall, 04. Number all of the nodes and

More information

October 3rd, 2012. Linear Algebra & Properties of the Covariance Matrix

October 3rd, 2012. Linear Algebra & Properties of the Covariance Matrix Linear Algebra & Properties of the Covariance Matrix October 3rd, 2012 Estimation of r and C Let rn 1, rn, t..., rn T be the historical return rates on the n th asset. rn 1 rṇ 2 r n =. r T n n = 1, 2,...,

More information

Unified Lecture # 4 Vectors

Unified Lecture # 4 Vectors Fall 2005 Unified Lecture # 4 Vectors These notes were written by J. Peraire as a review of vectors for Dynamics 16.07. They have been adapted for Unified Engineering by R. Radovitzky. References [1] Feynmann,

More information

Chapter 7: Polarization

Chapter 7: Polarization Chapter 7: Polarization Joaquín Bernal Méndez Group 4 1 Index Introduction Polarization Vector The Electric Displacement Vector Constitutive Laws: Linear Dielectrics Energy in Dielectric Systems Forces

More information

Finite Element Formulation for Beams - Handout 2 -

Finite Element Formulation for Beams - Handout 2 - Finite Element Formulation for Beams - Handout 2 - Dr Fehmi Cirak (fc286@) Completed Version Review of Euler-Bernoulli Beam Physical beam model midline Beam domain in three-dimensions Midline, also called

More information

Math 265 (Butler) Practice Midterm II B (Solutions)

Math 265 (Butler) Practice Midterm II B (Solutions) Math 265 (Butler) Practice Midterm II B (Solutions) 1. Find (x 0, y 0 ) so that the plane tangent to the surface z f(x, y) x 2 + 3xy y 2 at ( x 0, y 0, f(x 0, y 0 ) ) is parallel to the plane 16x 2y 2z

More information

Lecture 12: Fundamental Concepts in Structural Plasticity

Lecture 12: Fundamental Concepts in Structural Plasticity Lecture 12: Fundamental Concepts in Structural Plasticity Plastic properties of the material were already introduced briefly earlier in the present notes. The critical slenderness ratio of column is controlled

More information

STRESS AND DEFORMATION ANALYSIS OF LINEAR ELASTIC BARS IN TENSION

STRESS AND DEFORMATION ANALYSIS OF LINEAR ELASTIC BARS IN TENSION Chapter 11 STRESS AND DEFORMATION ANALYSIS OF LINEAR ELASTIC BARS IN TENSION Figure 11.1: In Chapter10, the equilibrium, kinematic and constitutive equations for a general three-dimensional solid deformable

More information

SF2940: Probability theory Lecture 8: Multivariate Normal Distribution

SF2940: Probability theory Lecture 8: Multivariate Normal Distribution SF2940: Probability theory Lecture 8: Multivariate Normal Distribution Timo Koski 24.09.2015 Timo Koski Matematisk statistik 24.09.2015 1 / 1 Learning outcomes Random vectors, mean vector, covariance matrix,

More information

SF2940: Probability theory Lecture 8: Multivariate Normal Distribution

SF2940: Probability theory Lecture 8: Multivariate Normal Distribution SF2940: Probability theory Lecture 8: Multivariate Normal Distribution Timo Koski 24.09.2014 Timo Koski () Mathematisk statistik 24.09.2014 1 / 75 Learning outcomes Random vectors, mean vector, covariance

More information

CBE 6333, R. Levicky 1 Differential Balance Equations

CBE 6333, R. Levicky 1 Differential Balance Equations CBE 6333, R. Levicky 1 Differential Balance Equations We have previously derived integral balances for mass, momentum, and energy for a control volume. The control volume was assumed to be some large object,

More information

R&DE (Engineers), DRDO. Theories of Failure. rd_mech@yahoo.co.in. Ramadas Chennamsetti

R&DE (Engineers), DRDO. Theories of Failure. rd_mech@yahoo.co.in. Ramadas Chennamsetti heories of Failure ummary Maximum rincial stress theory Maximum rincial strain theory Maximum strain energy theory Distortion energy theory Maximum shear stress theory Octahedral stress theory Introduction

More information

Notes on Determinant

Notes on Determinant ENGG2012B Advanced Engineering Mathematics Notes on Determinant Lecturer: Kenneth Shum Lecture 9-18/02/2013 The determinant of a system of linear equations determines whether the solution is unique, without

More information