INHOMOGENEOUS, NON-LINEAR AND ANISOTROPIC SYSTEMS WITH RANDOM MAGNETISATION MAIN DIRECTIONS

Size: px
Start display at page:

Download "INHOMOGENEOUS, NON-LINEAR AND ANISOTROPIC SYSTEMS WITH RANDOM MAGNETISATION MAIN DIRECTIONS"

Transcription

1 dx dt DIFFERENTIAL EQUATIONS AND CONTROL PROCESSES N Electronic Journal reg. N P23275 at diff@osipenko.stu.neva.ru Applications to physics electrotechnics and electronics INHOMOGENEOUS NON-LINEAR AND ANISOTROPIC SYSTEMS WITH RANDOM MAGNETISATION MAIN DIRECTIONS Part two: Minimisation of functional issue and FEM equations for 3D field produced by permanent magnets BERE IOAN Assoc. Prof. Politehnica University Department of Electrotechnics Timisoara Romania ibere@et.utt.ro Abstract The paper presents the minimization of functional issue associated to the finite elements method (FEM) and establish on detail the equations to solve the problem of the three-dimensional (3D) magnetic field in inhomogeneous nonlinear and anisotropic domains with random main directions of magnetization. Numerical computation of the algebraic equations system obtained it could be established the state quantities of the magnetic field or other quantities which are interested in. Key words: permanent magnets FEM inhomogenity nonlinearity anisotropy.

2 4. The minimization of the energy functional On FEM the functional must be minimized to get the equations system which follow to solve the field problem. If the finite elements of 3D discretization mesh are small enough the relation (33) from 1] become m ( ) 2 ( ) 2 ( ) 2 F = A VH xx A VH yy A VH zz z ( )( ) ( )( ) ( )( ) ] A VH VH xy A VH VH yz A VH VH zx v z z m ( ) 2 ( ) 2 ( ) 2 A VH xx A VH yy A VH zz z ( )( ) ( )( ) ( )( ) A VH VH xy A VH VH yz A VH VH zx z z ( ) ( ) ( ) ] K x VH K y VH K z VH v z m N m (B n ) (V H ) (S N ) N where v is the volume of the finite element. (B n ) (V H ) (S N ) (34) The magnetic scalar potential (V H ) unknown function in a current point P (x y z) inside the finite element = 1 m could be written depending on the magnetic scalar potentials V Hi V Hj V Hk V Hl of the i j k l nodes (fig.4) which determine an irregular tetrahedron (finite element). The expression of (V H ) for random may be written 2] under the form (V H ) = 1 6v (c ii c ji x c ki y c li z) V Hi (c ij c jj x c kj y c lj z) V Hj (c ik c jk x c kk y c lk z) V Hk (c il c jl x c kl y c ll z) V Hl ] (35) where: v = ± det (C) /6; v > 0; c rs (r s = i j k l) are the algebraic complements (cofactors) in the matrix (C) of the nodes coordinates which Electronic Journal. 2

3 determine the tetrahedron : 1 x i y i z i (C) = 1 x j y j z j 1 x k y k z k 1 x l y l z l From (35) for the terms of relation (34) results: ( ) VH = 1 (c ji V Hi c jj V Hj c jk V Hk c jl V Hl ) 6v (37) ( ) VH = 1 (c ki V Hi c kj V Hj c kk V Hk c kl V Hl ) 6v (38) ( ) VH = 1 (c li V Hi c lj V Hj c lk V Hk c ll V Hl ) z 6v. (39). (36) z y l i P (x y z) The last two sums of expression (34) may be not detailed in a general treatment because the boundary Fig.4. Finite element conditions for the possible concrete cases are different. In practice we can also have cases when the Neumann conditions are equal to zero what correspond to canceling of the last two sums. With the object of continuing the general analysis of the minimization process of functional we will detail only the first two sums of relation (34) following to take into account for concrete cases the terms corresponding to the Neumann boundary conditions too. With these mentions taking into account the relations ( ) the functional (34) become F = m 1 A xx (c ji V Hi c jj V Hj c jk V Hk c jl V Hl ) 2 A 36v yy(c ki V Hi c kj V Hj c kk V Hk c kl V Hl ) 2 A zz (c liv Hi c lj V Hj c lk V Hk c ll V Hl ) 2 j k x A xy (c jiv Hi c jj V Hj c jk V Hk c jl V Hl ) (c ki V Hi c kj V Hj c kk V Hk c kl V Hl ) A yz (c ki V Hi c kj V Hj c kk V Hk c kl V Hl ) (c li V Hi c lj V Hj c lk V Hk c ll V Hl ) Electronic Journal. 3

4 A zx (c li V Hi c lj V Hj c lk V Hk c ll V Hl ) (c ji V Hi c jj V Hj c jk V Hk c jl V Hl ) ] m { 1 36v A xx (c ji V Hi c jj V Hj c jk V Hk c jl V Hl ) 2 A yy (c ki V Hi c kj V Hj c kk V Hk c kl V Hl ) 2 A zz (c liv Hi c lj V Hj c lk V Hk c ll V Hl ) 2 A xy (c jiv Hi c jj V Hj c jk V Hk c jl V Hl ) (c ki V Hi c kj V Hj c kk V Hk c kl V Hl ) A yz (c ki V Hi c kj V Hj c kk V Hk c kl V Hl ) (c li V Hi c lj V Hj c lk V Hk c ll V Hl ) A zx (c liv Hi c lj V Hj c lk V Hk c ll V Hl ) (c ji V Hi c jj V Hj c jk V Hk c jl V Hl )] 1 6 K x (c jiv Hi c jj V Hj c jk V Hk c jl V Hl )K y (c kiv Hi c kj V Hj c kk V Hk c kl V Hl ) K z (c li V Hi c lj V Hj c lk V Hk c ll V Hl )] }. (40) The expression (40) could be written more concentrated in the following way m m ( F = F F F p) (41) where: F is the general term of the first sum; F is the general term of the second sum; F p is the second general term of the second sum. To minimize the functional we have to cancel its derivatives by magnetic scalar potential of the n nodes from the discretization mesh. Using the concentrated form (41) results m F m F m F p = 0; i = 1 n. (42) The system (42) contains n algebraic equations where the unknowns are the magnetic scalar potentials V Hi (i = 1 n) the 3D discretization mesh of the Electronic Journal. 4

5 studied domain. In particular cases where the studied domain has not permanent magnetization zones (permanent magnets) the terms of the last sum are canceled ( K x = K y = K z = 0). 5. The establish of FEM equations For every node of the discretization mesh it must be known the coordinates (x y z) the adjacent finite elements and the neighboring nodes. In order to establish the rules for writing the equations system two local numbering are introduced: N vi is the number of the neighbor nodes to the node i; M ai is the number of adjacent elements to the node i. The concrete values for N vi and M ai depends on the position of every node i = 1 n in the discretization mesh. For instance for any node i from inside of the tetrahedral mesh N vi = 12 and M ai = 20 3]. The magnetic scalar potential V Hi of the node i appears only in elementary functionless F F and F p which belong to the tetrahedral adjacent to the node i. Thus the equation from the system (42) concerning to any node i from inside of the discretization mesh which has M ai a adjacent elements will be ( a F ) ( a ) F ( a F p ) = 0 (43) where are made the notations CV j = c ji V Hi c jj V Hj c jk V Hk c jl V Hl CV k = c ki V Hi c kj V Hj c kk V Hk c kl V Hl (44) CV l = c li V Hi c lj V Hj c lk V Hk c ll V Hl with which the expressions of elementary functionless are: F 1 = 1 36v 1 (A xx ) 1 (CV j)2 1 ( ) A yy (CV 1 k)2 1 (A zz ) 1 (CV l)2 1 ( ) A xy (CV j) 1 1 (CV k) 1 ( ) A yz (CV k) 1 1 (CV l) ] 1 (A zx ) 1 (CV l) 1 (CV j) F a = 1 36v a (A xx ) a (CV j)2 a ( ) A yy (CV a k)2 a (A zz ) a (CV l)2 a ( ) A xy a (CV j) a (CV k) a ( ) A yz (CV k) a a (CV l) a ] (A zx ) a (CV l) a (CV j) a (45) Electronic Journal. 5

6 F 1 = 1 (A xx ) 1 (CV j)2 1 ( ) A yy (CV 1 k)2 1 (A zz ) 1 (CV l)2 1 ( ) A xy (CV j) 1 1 (CV k) 1 ( ) A yz (CV k) 1 1 (CV l) ] 1 (A zx ) 1 (CV l) 1 (CV j) F a = 1 36v a (A xx ) a (CV j)2 a ( ) A yy (CV a k)2 a (A zz ) a (CV l)2 a ( ) A xy a (CV j) a (CV k) a ( ) A yz (CV k) a a (CV l) a ] (A zx ) a (CV l) a (CV j) a 36v 1 F p1 = 1 (K 6 x ) 1 (CV j) 1 ( ) ] K y (CV k) 1 1 (K z ) 1 (CV l) F pa = 1 6 (K x ) a (CV j) a ( K y ) a (CV k) a (K z ) a (CV l) a ]. (46) (47) In the relations ( ) the subscripts ( a) written after the parenthesis show that the quantities ( CV ( j CV k CV l) (V Hi V Hj V Hk V Hl ) c rs (r = j k l; s = i j k l) A xx A yy A zz A xy A yz ) ( A zx A xx A yy A zz A xy A yz A zx) correspond to the finite element with the same index and (v 1 v 2... v a ) are the adjacent tetrahedral volumes of the node i for what the relation is written. The algebraic complements c rs of the matrix (C) written with the nodes coordinates i j k l which determine the finite element are constant quantities for an established discretization mesh. The elementary functionals F and F p are different by zero only for the finite elements from the zone with permanent magnetization where the functionals F are null. If the element is in the zone without permanent magnet F 0 and F = F p = 0. Derive the relations ( ) the general forms of these three kind of terms from functional becomes: F = 1 18v { A xx c 2 jia yyc 2 kia zzc 2 lia xyc ji c ki A yzc ki c li A zxc li c ji ] VHi A xx c jic jj A yy c kic kj A zz c lic lj 1 2 A xy (c jic kj c ki c jj ) 1 2 A yz (c ki c lj c li c kj ) 1 2 A zx (c li c jj c ji c lj ) ] V Hj A xx c jic jk A yy c kic kk A zz c lic lk 1 2 A xy (c jic kk c ki c jk ) Electronic Journal. 6

7 1 2 A yz (c kic lk c li c kk ) 1 2 A zx (c lic jk c ji c lk ) ] V Hk A xx c jic jl A yy c kic kl A zz c lic ll 1 2 A xy (c jic kl c ki c jl ) 1 2 A yz (c ki c ll c li c kl ) 1 2 A zx (c li c jl c ji c ll ) ] V Hl } (48) F = 1 { A xx 18v c2 ji A yy c2 ki A zz c2 li A xy c jic ki A yz c kic li A zx c ] lic ji VHi A xxc ji c jj A yyc ki c kj A zzc li c lj 1 2 A xy (c ji c kj c ki c jj ) 1 2 A yz (c kic lj c li c kj ) 1 2 A zx (c lic jj c ji c lj ) ] V Hj A xxc ji c jk A yyc ki c kk A zzc li c lk 1 2 A xy (c ji c kk c ki c jk ) 1 2 A yz (c kic lk c li c kk ) 1 2 A zx (c lic jk c ji c lk ) ] V Hk A xxc ji c jl A yyc ki c kl A zzc li c ll 1 2 A xy (c ji c kl c ki c jl ) 1 2 A yz (c kic ll c li c kl ) 1 2 A zx (c lic jl c ji c ll ) ] V Hl } (49) F p = 1 V 6 Hi where = a. ( K x c ji K y c ki K z c ) li (50) We notice that for specify equation i of the system (42) the term having the form (50) represents the free terms of the equation because it doesn t contain the magnetic scalar potentials of the nodes (the unknowns of the problem). After the introduction of the terms ( ) in relation (43) results the general form of an equation from the system (42) written for any node i from inside of the discretization mesh N vi C i V Hi C it V Ht = T L i ; i = 1 n (51) t=1 where we note that: a 1 ( ) C i = Axx c 2 18v jia yy c 2 kia zz c 2 lia xy c ji c ki A yz c ki c li A zx c li c ji (52) t t t=1 Electronic Journal. 7

8 C it = w t=1 1 18v t Axx c ji c jj A yy c ki c kj A zz c li c lj 1 2 A xy (c ji c kj c ki c jj ) 1 2 A yz (c ki c lj c li c kj ) 1 2 A zx (c li c jj c ji c lj ) ] t (53) T L i = 1 6 a t=1 ( K xc ji K y c ki K z c li )t. (54) In relations (52 53) obtained by writing more concentrated the relations (48 49) the terms (A xx ) t (A yy ) t (A zz ) t (A xy ) t (A yz ) t (A zx ) t contain the components of the tensors of the ferromagnetic materials permeability (µ u µ v µ w ) of the air gap (µ u = µ v = µ w = µ 0 ) or of the permanent magnet (µ pu µ pv µ pw ) ( s.1]) as the finite element t adjacent to the node i for which is written the relation (51) is situated in the ferromagnetic material zone in air gap or in permanent magnet. The current index t from the expressions ( ) refers to the finite element = t which could particularized for all the nodes i = 1 n of the discretization mesh identifying the elements (1 M ai ) from around of each node. The quantity w from the relation (53) represent the number of finite element (of the M ai adjacent to the node i) to which any neighbor node (of the N vi neighbor to the node i) is adjacent. For the analyzed case (i an inner node) w = 5 3]. The coefficients c rs from the relations ( ) are obtained by identifying the nodes j k and l of each finite element around the common node i for what the relation (51) is written. Therefore for each node i with unknown magnetic scalar potential an equation having the form (51) could be written. In relation with the concrete position of each node i the number of the neighbor nodes N vi respectively of the adjacent elements M ai of the node i gets particularly values. For the nodes on the boundary surface with non-null Neumann conditions of the studied domain in equation (43) we introduce supplementary particular terms correspond to these conditions (the last two sums from energetic functional (34)). 6. Conclusions If we write the equation (51) for all the nodes i = 1 n with unknowns magnetic scalar potentials of the 3D discretization mesh in which the field problem is analyzed a compatible system of algebraic equations is obtained. The values of the magnetic scalar potentials are gotten by numerical computation of Electronic Journal. 8

9 the system. After that we can get (s.eq ) the components of the magnetic field intensity for each finite element = 1 m: ( ) VH (H x ) = = 1 (c ji V Hj c jj V Hj c jk V Hk c jl V Hl ) 6v (55) ( ) VH (H y ) = = 1 (c ki V Hi c kj V Hj c kk V Hk c kl V Hl ) 6v (56) ( ) VH (H z ) = = 1 (c li V Hi c lj V Hj c lk V Hk c ll V Hl ) z 6v. (57) The components of the magnetic flux density B are determined from H and the tensors of magnetic permeability in the following way: in air-gap B = µ 0 H ; in ferromagnetic materials B = µ H ; in permanent magnets B = µ p H. In conclusion by numerical computation of equation system (51) we get H and B ( = 1 m) in each finite element of the studied domain which is 3D inhomogeneous nonlinear and anisotrop. After we know H and B we can determine other quantities which we are interested in such as: magnetic voltage magnetic flux through certain surfaces forces (torque) applied on coils or electric conductors placed within the air-gap and so on. References 1] I.Bere Inhomogeneous non-linear and anisotropic systems with random magnetisation main directions. Part one: The useful form of functional 3D for computation the field created by permanent magnets Electronic journal Differential equations and control processes N pp(26-35). ( 2] I.Bere Relative permeability of nonlinear and anisotrop permanent magnets Proceedings of the scientific communications A. Vlaicu University Arad 1996 pp(9-14). 3] K.H.Bachmann a.a. Kleine Enzyklopadie der Mathematik Ed. Tehnica Bucuresti 1980 pp( ). Electronic Journal. 9

Assignment 11 (C + C ) = (C + C ) = (C + C) i(c C ) ] = i(c C) (AB) = (AB) = B A = BA 0 = [A, B] = [A, B] = (AB BA) = (AB) AB

Assignment 11 (C + C ) = (C + C ) = (C + C) i(c C ) ] = i(c C) (AB) = (AB) = B A = BA 0 = [A, B] = [A, B] = (AB BA) = (AB) AB Arfken 3.4.6 Matrix C is not Hermition. But which is Hermitian. Likewise, Assignment 11 (C + C ) = (C + C ) = (C + C) [ i(c C ) ] = i(c C ) = i(c C) = i ( C C ) Arfken 3.4.9 The matrices A and B are both

More information

GG303 Lecture 6 8/27/09 1 SCALARS, VECTORS, AND TENSORS

GG303 Lecture 6 8/27/09 1 SCALARS, VECTORS, AND TENSORS GG303 Lecture 6 8/27/09 1 SCALARS, VECTORS, AND TENSORS I Main Topics A Why deal with tensors? B Order of scalars, vectors, and tensors C Linear transformation of scalars and vectors (and tensors) II Why

More information

Linear Algebra Practice Final

Linear Algebra Practice Final . Let (a) First, Linear Algebra Practice Final Summer 3 3 A = 5 3 3 rref([a ) = 5 so if we let x 5 = t, then x 4 = t, x 3 =, x = t, and x = t, so that t t x = t = t t whence ker A = span(,,,, ) and a basis

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY DEPARTMENT OF MATERIALS SCIENCE AND ENGINEERING CAMBRIDGE, MASSACHUSETTS 02139

MASSACHUSETTS INSTITUTE OF TECHNOLOGY DEPARTMENT OF MATERIALS SCIENCE AND ENGINEERING CAMBRIDGE, MASSACHUSETTS 02139 MASSACHUSETTS NSTTUTE OF TECHNOLOGY DEPARTMENT OF MATERALS SCENCE AND ENGNEERNG CAMBRDGE, MASSACHUSETTS 39 3. MECHANCAL PROPERTES OF MATERALS PROBLEM SET SOLUTONS Reading Ashby, M.F., 98, Tensors: Notes

More information

A NEW APPROACH OF REFRACTION FOR 3D FIELD IN ANISOTROPIC PERMANENT MAGNETS WITH RANDOM MAGNETIZATION MAIN DIRECTIONS IOAN BERE

A NEW APPROACH OF REFRACTION FOR 3D FIELD IN ANISOTROPIC PERMANENT MAGNETS WITH RANDOM MAGNETIZATION MAIN DIRECTIONS IOAN BERE DIFFERENTIAL EQUATIONS AND CONTROL PROCESSES, 00 Electronic Journal, reg. P375 at 07.03.97 ISSN 87-7 http://www.newa.ru/journal http://www.math.spbu.ru/user/diffjournal e-mail: jodiff@mail.ru Applications

More information

Maxwell s Equations:

Maxwell s Equations: Course Instructor Dr. Raymond C. Rumpf Office: A-337 Phone: (915) 747-6958 E-Mail: rcrumpf@utep.edu Maxwell s Equations: Physical Interpretation EE-3321 Electromagnetic Field Theory Outline Maxwell s Equations

More information

Cartesian Tensors. e 2. e 1. General vector (formal definition to follow) denoted by components

Cartesian Tensors. e 2. e 1. General vector (formal definition to follow) denoted by components Cartesian Tensors Reference: Jeffreys Cartesian Tensors 1 Coordinates and Vectors z x 3 e 3 y x 2 e 2 e 1 x x 1 Coordinates x i, i 123,, Unit vectors: e i, i 123,, General vector (formal definition to

More information

Two Posts to Fill On School Board

Two Posts to Fill On School Board Y Y 9 86 4 4 qz 86 x : ( ) z 7 854 Y x 4 z z x x 4 87 88 Y 5 x q x 8 Y 8 x x : 6 ; : 5 x ; 4 ( z ; ( ) ) x ; z 94 ; x 3 3 3 5 94 ; ; ; ; 3 x : 5 89 q ; ; x ; x ; ; x : ; ; ; ; ; ; 87 47% : () : / : 83

More information

Elementary maths for GMT

Elementary maths for GMT Elementary maths for GMT Linear Algebra Part 2: Matrices, Elimination and Determinant m n matrices The system of m linear equations in n variables x 1, x 2,, x n a 11 x 1 + a 12 x 2 + + a 1n x n = b 1

More information

' Liberty and Umou Ono and Inseparablo "

' Liberty and Umou Ono and Inseparablo 3 5? #< q 8 2 / / ) 9 ) 2 ) > < _ / ] > ) 2 ) ) 5 > x > [ < > < ) > _ ] ]? <

More information

NIELINIOWA OPTYKA MOLEKULARNA

NIELINIOWA OPTYKA MOLEKULARNA NIELINIOWA OPTYKA MOLEKULARNA chapter 1 by Stanisław Kielich translated by:tadeusz Bancewicz http://zon8.physd.amu.edu.pl/~tbancewi Poznan,luty 2008 ELEMENTS OF THE VECTOR AND TENSOR ANALYSIS Reference

More information

Invertible Matrices over Idempotent Semirings

Invertible Matrices over Idempotent Semirings Chamchuri Journal of Mathematics Volume 1(2009) Number 2, 55 61 http://www.math.sc.chula.ac.th/cjm Invertible Matrices over Idempotent Semirings W. Mora, A. Wasanawichit and Y. Kemprasit Received 28 Sep

More information

1 Multiply Eq. E i by λ 0: (λe i ) (E i ) 2 Multiply Eq. E j by λ and add to Eq. E i : (E i + λe j ) (E i )

1 Multiply Eq. E i by λ 0: (λe i ) (E i ) 2 Multiply Eq. E j by λ and add to Eq. E i : (E i + λe j ) (E i ) Direct Methods for Linear Systems Chapter Direct Methods for Solving Linear Systems Per-Olof Persson persson@berkeleyedu Department of Mathematics University of California, Berkeley Math 18A Numerical

More information

A.1 Appendix on Cartesian tensors

A.1 Appendix on Cartesian tensors 1 Lecture Notes on Fluid Dynamics (1.63J/2.21J) by Chiang C. Mei, February 6, 2007 A.1 Appendix on Cartesian tensors [Ref 1] : H Jeffreys, Cartesian Tensors; [Ref 2] : Y. C. Fung, Foundations of Solid

More information

V o l u m e 5, N u m b e r 5 2, 1 6 P a g e s. Gold B e U ClUt Stamps Double Stamp D a y E v e r y Wednesday

V o l u m e 5, N u m b e r 5 2, 1 6 P a g e s. Gold B e U ClUt Stamps Double Stamp D a y E v e r y Wednesday 1 6 5 J 9 6 " " z k ; k x k k k z z k j " " ( k " " k 8 1959 " " x k j 5 25 ; ; k k qz ; x 13 x k * k ( ) k k : qz 13 k k k j ; q k x ; x 615 26 ( : k z 113 99751 z k k q ; 15 k k k j q " " k j x x ( *»

More information

Finite Element Modeling of Electromagnetic Systems

Finite Element Modeling of Electromagnetic Systems Finite Element Modeling of Electromagnetic Systems Mathematical and numerical tools Unit of Applied and Computational Electromagnetics (ACE) Dept. of Electrical Engineering - University of Liège - Belgium

More information

Properties of the stress tensor

Properties of the stress tensor Appendix C Properties of the stress tensor Some of the basic properties of the stress tensor and traction vector are reviewed in the following. C.1 The traction vector Let us assume that the state of stress

More information

Course 2BA1: Hilary Term 2007 Section 8: Quaternions and Rotations

Course 2BA1: Hilary Term 2007 Section 8: Quaternions and Rotations Course BA1: Hilary Term 007 Section 8: Quaternions and Rotations David R. Wilkins Copyright c David R. Wilkins 005 Contents 8 Quaternions and Rotations 1 8.1 Quaternions............................ 1 8.

More information

Matrix Differentiation

Matrix Differentiation Matrix Differentiation CS5240 Theoretical Foundations in Multimedia Leow Wee Kheng Department of Computer Science School of Computing National University of Singapore Leow Wee Kheng (NUS) Matrix Differentiation

More information

OWELL WEEKLY JOURNAL

OWELL WEEKLY JOURNAL Y \»< - } Y Y Y & #»»» q ] q»»»>) & - - - } ) x ( - { Y» & ( x - (» & )< - Y X - & Q Q» 3 - x Q Y 6 \Y > Y Y X 3 3-9 33 x - - / - -»- --

More information

Chapter 1 Matrices and Systems of Equations

Chapter 1 Matrices and Systems of Equations Chapter 1 Matrices and Systems of Equations System of Linear Equations 1. A linear equation in n unknowns is an equation of the form n i=1 a i x i = b where a 1,..., a n, b R and x 1,..., x n are variables.

More information

FMIA. Fluid Mechanics and Its Applications 113 Series Editor: A. Thess. Moukalled Mangani Darwish. F. Moukalled L. Mangani M.

FMIA. Fluid Mechanics and Its Applications 113 Series Editor: A. Thess. Moukalled Mangani Darwish. F. Moukalled L. Mangani M. FMIA F. Moukalled L. Mangani M. Darwish An Advanced Introduction with OpenFOAM and Matlab This textbook explores both the theoretical foundation of the Finite Volume Method (FVM) and its applications in

More information

Continuum Mechanics. Continuum Mechanics and Constitutive Equations

Continuum Mechanics. Continuum Mechanics and Constitutive Equations Continuum Mechanics Continuum Mechanics and Constitutive Equations Continuum mechanics pertains to the description of mechanical behavior of materials under the assumption that the material is a uniform

More information

Computational Linear Algebra

Computational Linear Algebra Computational Linear Algebra PD Dr. rer. nat. habil. Ralf Peter Mundani Computation in Engineering / BGU Scientific Computing in Computer Science / INF Winter Term 2017/18 Part 2: Direct Methods PD Dr.

More information

ELASTICITY (MDM 10203)

ELASTICITY (MDM 10203) LASTICITY (MDM 10203) Lecture Module 5: 3D Constitutive Relations Dr. Waluyo Adi Siswanto University Tun Hussein Onn Malaysia Generalised Hooke's Law In one dimensional system: = (basic Hooke's law) Considering

More information

Tensor Visualization. CSC 7443: Scientific Information Visualization

Tensor Visualization. CSC 7443: Scientific Information Visualization Tensor Visualization Tensor data A tensor is a multivariate quantity Scalar is a tensor of rank zero s = s(x,y,z) Vector is a tensor of rank one v = (v x,v y,v z ) For a symmetric tensor of rank 2, its

More information

II. Determinant Functions

II. Determinant Functions Supplemental Materials for EE203001 Students II Determinant Functions Chung-Chin Lu Department of Electrical Engineering National Tsing Hua University May 22, 2003 1 Three Axioms for a Determinant Function

More information

M E 320 Professor John M. Cimbala Lecture 10

M E 320 Professor John M. Cimbala Lecture 10 M E 320 Professor John M. Cimbala Lecture 10 Today, we will: Finish our example problem rates of motion and deformation of fluid particles Discuss the Reynolds Transport Theorem (RTT) Show how the RTT

More information

Course no. 4. The Theory of Electromagnetic Field

Course no. 4. The Theory of Electromagnetic Field Cose no. 4 The Theory of Electromagnetic Field Technical University of Cluj-Napoca http://www.et.utcluj.ro/cs_electromagnetics2006_ac.htm http://www.et.utcluj.ro/~lcret March 19-2009 Chapter 3 Magnetostatics

More information

Higher dimensional Kerr-Schild spacetimes 1

Higher dimensional Kerr-Schild spacetimes 1 Higher dimensional Kerr-Schild spacetimes 1 Marcello Ortaggio Institute of Mathematics Academy of Sciences of the Czech Republic Bremen August 2008 1 Joint work with V. Pravda and A. Pravdová, arxiv:0808.2165

More information

Eddy Current Losses in the Tank Wall of Power Transformers

Eddy Current Losses in the Tank Wall of Power Transformers Eddy Current Losses in the Tank Wall of Power Transformers Erich Schmidt Institute of Electrical Drives and Machines, Vienna University of Technology A 14 Vienna, Austria, Gusshausstrasse 25 29 Phone:

More information

Finite Element Method in Geotechnical Engineering

Finite Element Method in Geotechnical Engineering Finite Element Method in Geotechnical Engineering Short Course on + Dynamics Boulder, Colorado January 5-8, 2004 Stein Sture Professor of Civil Engineering University of Colorado at Boulder Contents Steps

More information

L8. Basic concepts of stress and equilibrium

L8. Basic concepts of stress and equilibrium L8. Basic concepts of stress and equilibrium Duggafrågor 1) Show that the stress (considered as a second order tensor) can be represented in terms of the eigenbases m i n i n i. Make the geometrical representation

More information

LOWELL WEEKLY JOURNAL

LOWELL WEEKLY JOURNAL Y -» $ 5 Y 7 Y Y -Y- Q x Q» 75»»/ q } # ]»\ - - $ { Q» / X x»»- 3 q $ 9 ) Y q - 5 5 3 3 3 7 Q q - - Q _»»/Q Y - 9 - - - )- [ X 7» -» - )»? / /? Q Y»» # X Q» - -?» Q ) Q \ Q - - - 3? 7» -? #»»» 7 - / Q

More information

Math Problem set # 7

Math Problem set # 7 Math 128 - Problem set # 7 Clifford algebras. April 8, 2004 due April 22 Because of disruptions due the the Jewish holidays and surgery on my knee there will be no class next week (April 13 or 15). (Doctor

More information

Linear Algebra. Linear Equations and Matrices. Copyright 2005, W.R. Winfrey

Linear Algebra. Linear Equations and Matrices. Copyright 2005, W.R. Winfrey Copyright 2005, W.R. Winfrey Topics Preliminaries Systems of Linear Equations Matrices Algebraic Properties of Matrix Operations Special Types of Matrices and Partitioned Matrices Matrix Transformations

More information

Index Notation for Vector Calculus

Index Notation for Vector Calculus Index Notation for Vector Calculus by Ilan Ben-Yaacov and Francesc Roig Copyright c 2006 Index notation, also commonly known as subscript notation or tensor notation, is an extremely useful tool for performing

More information

Matrix Factorization and Analysis

Matrix Factorization and Analysis Chapter 7 Matrix Factorization and Analysis Matrix factorizations are an important part of the practice and analysis of signal processing. They are at the heart of many signal-processing algorithms. Their

More information

5.6. PSEUDOINVERSES 101. A H w.

5.6. PSEUDOINVERSES 101. A H w. 5.6. PSEUDOINVERSES 0 Corollary 5.6.4. If A is a matrix such that A H A is invertible, then the least-squares solution to Av = w is v = A H A ) A H w. The matrix A H A ) A H is the left inverse of A and

More information

Determinants. Chia-Ping Chen. Linear Algebra. Professor Department of Computer Science and Engineering National Sun Yat-sen University 1/40

Determinants. Chia-Ping Chen. Linear Algebra. Professor Department of Computer Science and Engineering National Sun Yat-sen University 1/40 1/40 Determinants Chia-Ping Chen Professor Department of Computer Science and Engineering National Sun Yat-sen University Linear Algebra About Determinant A scalar function on the set of square matrices

More information

Useful Formulae ( )

Useful Formulae ( ) Appendix A Useful Formulae (985-989-993-) 34 Jeremić et al. A.. CHAPTER SUMMARY AND HIGHLIGHTS page: 35 of 536 A. Chapter Summary and Highlights A. Stress and Strain This section reviews small deformation

More information

Linear Algebra V = T = ( 4 3 ).

Linear Algebra V = T = ( 4 3 ). Linear Algebra Vectors A column vector is a list of numbers stored vertically The dimension of a column vector is the number of values in the vector W is a -dimensional column vector and V is a 5-dimensional

More information

Getting started: CFD notation

Getting started: CFD notation PDE of p-th order Getting started: CFD notation f ( u,x, t, u x 1,..., u x n, u, 2 u x 1 x 2,..., p u p ) = 0 scalar unknowns u = u(x, t), x R n, t R, n = 1,2,3 vector unknowns v = v(x, t), v R m, m =

More information

PHYS 705: Classical Mechanics. Rigid Body Motion Introduction + Math Review

PHYS 705: Classical Mechanics. Rigid Body Motion Introduction + Math Review 1 PHYS 705: Classical Mechanics Rigid Body Motion Introduction + Math Review 2 How to describe a rigid body? Rigid Body - a system of point particles fixed in space i r ij j subject to a holonomic constraint:

More information

Mechanics of Biomaterials

Mechanics of Biomaterials Mechanics of Biomaterials Lecture 7 Presented by Andrian Sue AMME498/998 Semester, 206 The University of Sydney Slide Mechanics Models The University of Sydney Slide 2 Last Week Using motion to find forces

More information

ECS 178 Course Notes QUATERNIONS

ECS 178 Course Notes QUATERNIONS ECS 178 Course Notes QUATERNIONS Kenneth I. Joy Institute for Data Analysis and Visualization Department of Computer Science University of California, Davis Overview The quaternion number system was discovered

More information

THE I Establiifrad June, 1893

THE I Establiifrad June, 1893 89 : 8 Y Y 2 96 6 - - : - 2 q - 26 6 - - q 2 2 2 4 6 4«4 ' V () 8 () 6 64-4 '2" () 6 ( ) * 'V ( 4 ) 94-4 q ( / ) K ( x- 6% j 9*V 2'%" 222 27 q - - K 79-29 - K x 2 2 j - -% K 4% 2% 6% ' K - 2 47 x - - j

More information

Finite Element Method (FEM)

Finite Element Method (FEM) Finite Element Method (FEM) The finite element method (FEM) is the oldest numerical technique applied to engineering problems. FEM itself is not rigorous, but when combined with integral equation techniques

More information

William Stallings Copyright 2010

William Stallings Copyright 2010 A PPENDIX E B ASIC C ONCEPTS FROM L INEAR A LGEBRA William Stallings Copyright 2010 E.1 OPERATIONS ON VECTORS AND MATRICES...2 Arithmetic...2 Determinants...4 Inverse of a Matrix...5 E.2 LINEAR ALGEBRA

More information

Complex Hadamard matrices and 3-class association schemes

Complex Hadamard matrices and 3-class association schemes Complex Hadamard matrices and 3-class association schemes Akihiro Munemasa 1 1 Graduate School of Information Sciences Tohoku University (joint work with Takuya Ikuta) June 26, 2013 The 30th Algebraic

More information

Math 3108: Linear Algebra

Math 3108: Linear Algebra Math 3108: Linear Algebra Instructor: Jason Murphy Department of Mathematics and Statistics Missouri University of Science and Technology 1 / 323 Contents. Chapter 1. Slides 3 70 Chapter 2. Slides 71 118

More information

INVERSE TRIDIAGONAL Z MATRICES

INVERSE TRIDIAGONAL Z MATRICES INVERSE TRIDIAGONAL Z MATRICES (Linear and Multilinear Algebra, 45() : 75-97, 998) J J McDonald Department of Mathematics and Statistics University of Regina Regina, Saskatchewan S4S 0A2 M Neumann Department

More information

Waves in Linear Optical Media

Waves in Linear Optical Media 1/53 Waves in Linear Optical Media Sergey A. Ponomarenko Dalhousie University c 2009 S. A. Ponomarenko Outline Plane waves in free space. Polarization. Plane waves in linear lossy media. Dispersion relations

More information

Q SON,' (ESTABLISHED 1879L

Q SON,' (ESTABLISHED 1879L ( < 5(? Q 5 9 7 00 9 0 < 6 z 97 ( # ) $ x 6 < ( ) ( ( 6( ( ) ( $ z 0 z z 0 ) { ( % 69% ( ) x 7 97 z ) 7 ) ( ) 6 0 0 97 )( 0 x 7 97 5 6 ( ) 0 6 ) 5 ) 0 ) 9%5 z» 0 97 «6 6» 96? 0 96 5 0 ( ) ( ) 0 x 6 0

More information

Linear Systems and Matrices

Linear Systems and Matrices Department of Mathematics The Chinese University of Hong Kong 1 System of m linear equations in n unknowns (linear system) a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.......

More information

Dot Products, Transposes, and Orthogonal Projections

Dot Products, Transposes, and Orthogonal Projections Dot Products, Transposes, and Orthogonal Projections David Jekel November 13, 2015 Properties of Dot Products Recall that the dot product or standard inner product on R n is given by x y = x 1 y 1 + +

More information

Numerical Computation of the Restoring Force in a Cylindrical Bearing Containing Magnetic Liquid

Numerical Computation of the Restoring Force in a Cylindrical Bearing Containing Magnetic Liquid SERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol. 5, No., November 008, 83-90 Numerical Computation of the Restoring Force in a Cylindrical Bearing Containing Magnetic Liquid Marian Greconici, Gheorghe Madescu,

More information

(K + L)(c x) = K(c x) + L(c x) (def of K + L) = K( x) + K( y) + L( x) + L( y) (K, L are linear) = (K L)( x) + (K L)( y).

(K + L)(c x) = K(c x) + L(c x) (def of K + L) = K( x) + K( y) + L( x) + L( y) (K, L are linear) = (K L)( x) + (K L)( y). Exercise 71 We have L( x) = x 1 L( v 1 ) + x 2 L( v 2 ) + + x n L( v n ) n = x i (a 1i w 1 + a 2i w 2 + + a mi w m ) i=1 ( n ) ( n ) ( n ) = x i a 1i w 1 + x i a 2i w 2 + + x i a mi w m i=1 Therefore y

More information

PERMANENTLY WEAK AMENABILITY OF REES SEMIGROUP ALGEBRAS. Corresponding author: jabbari 1. Introduction

PERMANENTLY WEAK AMENABILITY OF REES SEMIGROUP ALGEBRAS. Corresponding author: jabbari 1. Introduction International Journal of Analysis and Applications Volume 16, Number 1 (2018), 117-124 URL: https://doi.org/10.28924/2291-8639 DOI: 10.28924/2291-8639-16-2018-117 PERMANENTLY WEAK AMENABILITY OF REES SEMIGROUP

More information

Uniformity of the Universe

Uniformity of the Universe Outline Universe is homogenous and isotropic Spacetime metrics Friedmann-Walker-Robertson metric Number of numbers needed to specify a physical quantity. Energy-momentum tensor Energy-momentum tensor of

More information

Continuum mechanism: Stress and strain

Continuum mechanism: Stress and strain Continuum mechanics deals with the relation between forces (stress, σ) and deformation (strain, ε), or deformation rate (strain rate, ε). Solid materials, rigid, usually deform elastically, that is the

More information

The Matrix Representation of a Three-Dimensional Rotation Revisited

The Matrix Representation of a Three-Dimensional Rotation Revisited Physics 116A Winter 2010 The Matrix Representation of a Three-Dimensional Rotation Revisited In a handout entitled The Matrix Representation of a Three-Dimensional Rotation, I provided a derivation of

More information

Contents. Physical Properties. Scalar, Vector. Second Rank Tensor. Transformation. 5 Representation Quadric. 6 Neumann s Principle

Contents. Physical Properties. Scalar, Vector. Second Rank Tensor. Transformation. 5 Representation Quadric. 6 Neumann s Principle Physical Properties Contents 1 Physical Properties 2 Scalar, Vector 3 Second Rank Tensor 4 Transformation 5 Representation Quadric 6 Neumann s Principle Physical Properties of Crystals - crystalline- translational

More information

Chapter 2: Basic Governing Equations

Chapter 2: Basic Governing Equations -1 Reynolds Transport Theorem (RTT) - Continuity Equation -3 The Linear Momentum Equation -4 The First Law of Thermodynamics -5 General Equation in Conservative Form -6 General Equation in Non-Conservative

More information

Problem Set 2 Due Tuesday, September 27, ; p : 0. (b) Construct a representation using five d orbitals that sit on the origin as a basis: 1

Problem Set 2 Due Tuesday, September 27, ; p : 0. (b) Construct a representation using five d orbitals that sit on the origin as a basis: 1 Problem Set 2 Due Tuesday, September 27, 211 Problems from Carter: Chapter 2: 2a-d,g,h,j 2.6, 2.9; Chapter 3: 1a-d,f,g 3.3, 3.6, 3.7 Additional problems: (1) Consider the D 4 point group and use a coordinate

More information

Introduction to Liquid Crystalline Elastomers

Introduction to Liquid Crystalline Elastomers Introduction to Liquid Crystalline Elastomers Harald Pleiner Max Planck Institute for Polymer Research, Mainz, Germany "Ferroelectric Phenomena in Liquid Crystals" LCI, Kent State University, Ohio, USA

More information

Product of derivations on C -algebras

Product of derivations on C -algebras Int. J. Nonlinear Anal. Appl. 7 (2016) No. 2, 109-114 ISSN: 2008-6822 (electronic) http://www.ijnaa.semnan.ac.ir Product of derivations on C -algebras Sayed Khalil Ekrami a,, Madjid Mirzavaziri b, Hamid

More information

Group Representations

Group Representations Group Representations Alex Alemi November 5, 2012 Group Theory You ve been using it this whole time. Things I hope to cover And Introduction to Groups Representation theory Crystallagraphic Groups Continuous

More information

Crystal Micro-Mechanics

Crystal Micro-Mechanics Crystal Micro-Mechanics Lectre Classical definition of stress and strain Heng Nam Han Associate Professor School of Materials Science & Engineering College of Engineering Seol National University Seol

More information

Phys 201. Matrices and Determinants

Phys 201. Matrices and Determinants Phys 201 Matrices and Determinants 1 1.1 Matrices 1.2 Operations of matrices 1.3 Types of matrices 1.4 Properties of matrices 1.5 Determinants 1.6 Inverse of a 3 3 matrix 2 1.1 Matrices A 2 3 7 =! " 1

More information

Chapter Two Elements of Linear Algebra

Chapter Two Elements of Linear Algebra Chapter Two Elements of Linear Algebra Previously, in chapter one, we have considered single first order differential equations involving a single unknown function. In the next chapter we will begin to

More information

Matrices and Determinants

Matrices and Determinants Chapter1 Matrices and Determinants 11 INTRODUCTION Matrix means an arrangement or array Matrices (plural of matrix) were introduced by Cayley in 1860 A matrix A is rectangular array of m n numbers (or

More information

Medical Physics & Science Applications

Medical Physics & Science Applications Power Conversion & Electromechanical Devices Medical Physics & Science Applications Transportation Power Systems 1-5: Introduction to the Finite Element Method Introduction Finite Element Method is used

More information

Math 321: Linear Algebra

Math 321: Linear Algebra Math 32: Linear Algebra T. Kapitula Department of Mathematics and Statistics University of New Mexico September 8, 24 Textbook: Linear Algebra,by J. Hefferon E-mail: kapitula@math.unm.edu Prof. Kapitula,

More information

From discrete differential geometry to the classification of discrete integrable systems

From discrete differential geometry to the classification of discrete integrable systems From discrete differential geometry to the classification of discrete integrable systems Vsevolod Adler,, Yuri Suris Technische Universität Berlin Quantum Integrable Discrete Systems, Newton Institute,

More information

Elementary Row Operations on Matrices

Elementary Row Operations on Matrices King Saud University September 17, 018 Table of contents 1 Definition A real matrix is a rectangular array whose entries are real numbers. These numbers are organized on rows and columns. An m n matrix

More information

Matrix Algebra & Elementary Matrices

Matrix Algebra & Elementary Matrices Matrix lgebra & Elementary Matrices To add two matrices, they must have identical dimensions. To multiply them the number of columns of the first must equal the number of rows of the second. The laws below

More information

Stochastic Numerical Analysis

Stochastic Numerical Analysis Stochastic Numerical Analysis Prof. Mike Giles mike.giles@maths.ox.ac.uk Oxford University Mathematical Institute Stoch. NA, Lecture 3 p. 1 Multi-dimensional SDEs So far we have considered scalar SDEs

More information

Lecture 7. Properties of Materials

Lecture 7. Properties of Materials MIT 3.00 Fall 2002 c W.C Carter 55 Lecture 7 Properties of Materials Last Time Types of Systems and Types of Processes Division of Total Energy into Kinetic, Potential, and Internal Types of Work: Polarization

More information

ASSIGNMENT-1 GURU JAMBHESHWARUNIVERSITY OF SCIENCE & TECHNOLOGY, HISAR DIRECTORATE OF DISTANCE EDUCATION

ASSIGNMENT-1 GURU JAMBHESHWARUNIVERSITY OF SCIENCE & TECHNOLOGY, HISAR DIRECTORATE OF DISTANCE EDUCATION ASSIGNMENT-1 GURU JAMBHESHWARUNIVERSITY OF SCIENCE & TECHNOLOGY, HISAR Paper Code: MAL-631 Nomenclature of Paper:TOPOLOGY Q.1 Prove that in a topological space, E E d E E X. Q.2Characterize topology in

More information

LOWELL WEEKLY JOURNAL

LOWELL WEEKLY JOURNAL Y G y G Y 87 y Y 8 Y - $ X ; ; y y q 8 y $8 $ $ $ G 8 q < 8 6 4 y 8 7 4 8 8 < < y 6 $ q - - y G y G - Y y y 8 y y y Y Y 7-7- G - y y y ) y - y y y y - - y - y 87 7-7- G G < G y G y y 6 X y G y y y 87 G

More information

Comparisons of Linear Characteristic for Shape of Stator Teeth of Hall Effect Torque Sensor

Comparisons of Linear Characteristic for Shape of Stator Teeth of Hall Effect Torque Sensor Journal of Magnetics 17(4), 285-290 (2012) ISSN (Print) 1226-1750 ISSN (Online) 2233-6656 http://dx.doi.org/10.4283/jmag.2012.17.4.285 Comparisons of Linear Characteristic for Shape of Stator Teeth of

More information

CH.3. COMPATIBILITY EQUATIONS. Multimedia Course on Continuum Mechanics

CH.3. COMPATIBILITY EQUATIONS. Multimedia Course on Continuum Mechanics CH.3. COMPATIBILITY EQUATIONS Multimedia Course on Continuum Mechanics Overview Introduction Lecture 1 Compatibility Conditions Lecture Compatibility Equations of a Potential Vector Field Lecture 3 Compatibility

More information

3 2 6 Solve the initial value problem u ( t) 3. a- If A has eigenvalues λ =, λ = 1 and corresponding eigenvectors 1

3 2 6 Solve the initial value problem u ( t) 3. a- If A has eigenvalues λ =, λ = 1 and corresponding eigenvectors 1 Math Problem a- If A has eigenvalues λ =, λ = 1 and corresponding eigenvectors 1 3 6 Solve the initial value problem u ( t) = Au( t) with u (0) =. 3 1 u 1 =, u 1 3 = b- True or false and why 1. if A is

More information

Lecture10: Plasma Physics 1. APPH E6101x Columbia University

Lecture10: Plasma Physics 1. APPH E6101x Columbia University Lecture10: Plasma Physics 1 APPH E6101x Columbia University Last Lecture - Conservation principles in magnetized plasma frozen-in and conservation of particles/flux tubes) - Alfvén waves without plasma

More information

Math review. Math review

Math review. Math review Math review 1 Math review 3 1 series approximations 3 Taylor s Theorem 3 Binomial approximation 3 sin(x), for x in radians and x close to zero 4 cos(x), for x in radians and x close to zero 5 2 some geometry

More information

Neatest and Promptest Manner. E d i t u r ami rul)lihher. FOIt THE CIIILDIIES'. Trifles.

Neatest and Promptest Manner. E d i t u r ami rul)lihher. FOIt THE CIIILDIIES'. Trifles. » ~ $ ) 7 x X ) / ( 8 2 X 39 ««x» ««! «! / x? \» «({? «» q «(? (?? x! «? 8? ( z x x q? ) «q q q ) x z x 69 7( X X ( 3»«! ( ~«x ««x ) (» «8 4 X «4 «4 «8 X «x «(» X) ()»» «X «97 X X X 4 ( 86) x) ( ) z z

More information

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

Math 1060 Linear Algebra Homework Exercises 1 1. Find the complete solutions (if any!) to each of the following systems of simultaneous equations: Homework Exercises 1 1 Find the complete solutions (if any!) to each of the following systems of simultaneous equations: (i) x 4y + 3z = 2 3x 11y + 13z = 3 2x 9y + 2z = 7 x 2y + 6z = 2 (ii) x 4y + 3z =

More information

On finite element methods for 3D time dependent convection diffusion reaction equations with small diffusion

On finite element methods for 3D time dependent convection diffusion reaction equations with small diffusion On finite element methods for 3D time dependent convection diffusion reaction equations with small diffusion Volker John and Ellen Schmeyer FR 6.1 Mathematik, Universität des Saarlandes, Postfach 15 11

More information

Working papers of the Department of Economics University of Perugia (IT)

Working papers of the Department of Economics University of Perugia (IT) ISSN 385-75 Working papers of the Department of Economics University of Perugia (IT) The Heat Kernel on Homogeneous Trees and the Hypergeometric Function Hacen Dib Mauro Pagliacci Working paper No 6 December

More information

Jim Lambers MAT 610 Summer Session Lecture 1 Notes

Jim Lambers MAT 610 Summer Session Lecture 1 Notes Jim Lambers MAT 60 Summer Session 2009-0 Lecture Notes Introduction This course is about numerical linear algebra, which is the study of the approximate solution of fundamental problems from linear algebra

More information

1 First and second variational formulas for area

1 First and second variational formulas for area 1 First and second variational formulas for area In this chapter, we will derive the first and second variational formulas for the area of a submanifold. This will be useful in our later discussion on

More information

NOTES on LINEAR ALGEBRA 1

NOTES on LINEAR ALGEBRA 1 School of Economics, Management and Statistics University of Bologna Academic Year 207/8 NOTES on LINEAR ALGEBRA for the students of Stats and Maths This is a modified version of the notes by Prof Laura

More information

Matrices. 1 a a2 1 b b 2 1 c c π

Matrices. 1 a a2 1 b b 2 1 c c π Matrices 2-3-207 A matrix is a rectangular array of numbers: 2 π 4 37 42 0 3 a a2 b b 2 c c 2 Actually, the entries can be more general than numbers, but you can think of the entries as numbers to start

More information

Symmetry and Properties of Crystals (MSE638) Stress and Strain Tensor

Symmetry and Properties of Crystals (MSE638) Stress and Strain Tensor Symmetry and Properties of Crystals (MSE638) Stress and Strain Tensor Somnath Bhowmick Materials Science and Engineering, IIT Kanpur April 6, 2018 Tensile test and Hooke s Law Upto certain strain (0.75),

More information

ON SUM OF SQUARES DECOMPOSITION FOR A BIQUADRATIC MATRIX FUNCTION

ON SUM OF SQUARES DECOMPOSITION FOR A BIQUADRATIC MATRIX FUNCTION Annales Univ. Sci. Budapest., Sect. Comp. 33 (2010) 273-284 ON SUM OF SQUARES DECOMPOSITION FOR A BIQUADRATIC MATRIX FUNCTION L. László (Budapest, Hungary) Dedicated to Professor Ferenc Schipp on his 70th

More information

PEAT SEISMOLOGY Lecture 2: Continuum mechanics

PEAT SEISMOLOGY Lecture 2: Continuum mechanics PEAT8002 - SEISMOLOGY Lecture 2: Continuum mechanics Nick Rawlinson Research School of Earth Sciences Australian National University Strain Strain is the formal description of the change in shape of a

More information

NONLINEAR CONTINUUM FORMULATIONS CONTENTS

NONLINEAR CONTINUUM FORMULATIONS CONTENTS NONLINEAR CONTINUUM FORMULATIONS CONTENTS Introduction to nonlinear continuum mechanics Descriptions of motion Measures of stresses and strains Updated and Total Lagrangian formulations Continuum shell

More information

Regular Expressions [1] Regular Expressions. Regular expressions can be seen as a system of notations for denoting ɛ-nfa

Regular Expressions [1] Regular Expressions. Regular expressions can be seen as a system of notations for denoting ɛ-nfa Regular Expressions [1] Regular Expressions Regular expressions can be seen as a system of notations for denoting ɛ-nfa They form an algebraic representation of ɛ-nfa algebraic : expressions with equations

More information

Quantum Information & Quantum Computing

Quantum Information & Quantum Computing Math 478, Phys 478, CS4803, February 9, 006 1 Georgia Tech Math, Physics & Computing Math 478, Phys 478, CS4803 Quantum Information & Quantum Computing Problems Set 1 Due February 9, 006 Part I : 1. Read

More information