A New Cement to Glue Nonconforming Grids with Robin Interface Conditions: The Finite Element Case
|
|
|
- Julius Clarke
- 10 years ago
- Views:
Transcription
1 A New Cement to Glue Nonconforming Grids wit Robin Interface Conditions: Te Finite Element Case Martin J. Gander, Caroline Japet 2, Yvon Maday 3, and Frédéric Nataf 4 McGill University, Dept. of Matematics and Statistics, Montreal (ttp:// 2 Université Paris 3, Laboratoire d Analyse, Géométrie et Applications 3 Université Pierre et Marie Curie, Laboratoire Jacques Louis Lions (ttp:// 4 CNRS, UMR 764, CMAP, Ecole Polytecnique, 928 Palaiseau (ttp:// Summary. We present and analyze a new nonconforming domain decomposition metod based on a Scwarz metod wit Robin transmission conditions. We prove tat te metod is well posed and convergent. Our error analysis is valid in two dimensions for piecewise polynomials of low and ig order and also in tree dimensions for P elements. We furter present an efficient algoritm in two dimensions to perform te required projections between arbitrary grids. We finally illustrate te new metod wit numerical results. Introduction We propose a domain decomposition metod based on te Scwarz algoritm tat permits te use of optimized interface conditions on nonconforming grids. Suc interface conditions ave been sown to be a ey ingredient for efficient domain decomposition metods in te case of conforming approximations (see Després [99], Nataf et al. [995], Japet [998], Cevalier and Nataf [998]). Our goal is to use tese interface conditions on nonconforming grids, because tis simplifies greatly te parallel generation and adaptation of meses per subdomain. Te mortar metod, first introduced in Bernardi et al. [994], also permits te use of nonconforming grids, and it is well suited to te use of Diriclet-Neumann (Gastaldi et al. [996]) or Neumann-Neumann metods applied to te Scur complement matrix. But te mortar metod can not be used easily wit optimized transmission conditions in te framewor of Scwarz metods. In Acdou et al. [22], te case of finite volume discretizations as been introduced and analyzed. Tis paper is a first step in te finite element case; we consider only interface conditions of order ere.
2 26 Martin J. Gander, Caroline Japet, Yvon Maday, and Frédéric Nataf 2 Definition of te metod and te iterative solver We consider te model problem (Id )u = f in Ω, u = on Ω, () were f is given in L 2 (Ω) and Ω is a C, (or convex) domain in IR d, d = 2 or 3. We assume tat it is decomposed into K non-overlapping subdomains Ω = K Ω, were Ω, K are C, or convex polygons in two or polyedrons in tree dimensions. We also assume tat tis domain decomposition is conforming. Let n be te unit outward normal for Ω and Γ,l = Ω Ω l. Te variational statement of problem () consists of writing te problem as follows: Find u H (Ω) suc tat ( u v + uv)dx = fvdx, v H (Ω). (2) Ω Ω We introduce now te space H (Ω ) = {ϕ H (Ω ), ϕ = over Ω Ω }, and te constrained space K K V ={(v,q) ( H (Ω )) ( H /2 ( Ω )), v =v l and q = q l on Γ,l }. Problem (2) is ten equivalent to te following: Find (u,p) V suc tat Ω ( u v + u v )dx = H /2 ( Ω ) < p, v > H /2 ( Ω ) Ω f v dx, v K H (Ω ). Being equivalent wit te original problem, were p = u n over Ω, tis problem is naturally well posed. We now describe te iterative procedure in te continuous case, and ten its discrete, non-conforming analog. 2. Te continuous case We introduce for α IR, α >, te zerot order transmission condition p + αu = p l + αu l over Γ,l and te following algoritm: let (u n, pn ) H (Ω ) H /2 ( Ω ) be an approximation of (u, p) in Ω at step n. Ten, (u n+, p n+ ) is te solution in H (Ω ) H /2 ( Ω ) of
3 Nonconforming Grids wit Robin Interface Conditions 26 ( u n+ v + u n+ ) v dx H /2 ( Ω ) < p n+, v > H /2 ( Ω ) Ω = f v dx, v H (Ω ), Ω < p n+ +αu n+, v > Γ,l=< p n l +αun l, v > Γ,l, v H /2 (Γ,l ). Convergence of tis algoritm is sown in Després [99] using energy estimates and summarized in te following Teorem. Assume tat f is in L 2 (Ω) and (p ) K l H/2 (Γ,l ). Ten, algoritm (3) converges in te sense tat lim u n n ( u H (Ω ) + p n p ) H /2 ( Ω ) =, for K, were u solves (), u = u Ω, p = u n on Ω for K. 2.2 Te discrete case We introduce now te discrete spaces: eac Ω is provided wit its own mes T, K, suc tat Ω = T T T. For T T, let T be te diameter of T and te discretization parameter, = max K (max T T T ). Let ρ T be te diameter of te circle in two dimensions or spere in tree dimensions inscribed in T. We suppose tat T is uniformly regular: tere exists σ and τ independent of suc tat T T, σ T σ and τ T. We consider tat te sets belonging to te meses are of simplicial type (triangles or tetraedra), but te following analysis can be applied as well for quadrangular or exaedral meses. Let P M (T) denote te space of all polynomials defined over T of total degree less tan or equal to M for our Lagrangian finite elements. Ten, we define over eac subdomain two conforming spaces Y and X by Y = {v, C (Ω ), v, T P M (T), T T }, X = {v, Y, v, Ω Ω = }. (4) Te space of traces over eac Γ,l of elements of Y is denoted by Y,l. In te sequel we assume for te sae of simplicity tat referring to a pair (, l) implies tat Γ,l,l is not empty. Wit eac suc interface we associate a subspace W of Y,l lie in te mortar element metod; for two dimensions, see Bernardi et al. [994], and for tree dimensions see Belgacem and Maday [997] and Braess and Damen [998]. To be more specific, we recall te situation in two dimensions: if te space X consists of continuous piecewise polynomials of degree M, ten it is readily noticed tat te restriction of X,l to Γ consists of finite element functions adapted to te (possibly curved) side Γ,l of piecewise polynomials of degree M. Tis side as two end points wic we denote by x,l and x,l n and wic belong to te set of vertices of te (3)
4 262 Martin J. Gander, Caroline Japet, Yvon Maday, and Frédéric Nataf corresponding triangulation of Γ,l : x,l, x,l,...,x,l is ten te subspace of tose elements of Y,l M over bot [x,l, x,l n, x,l,l n. Te space W tat are polynomials of degree ] and [x,l n, x,l n ]. As before, te space W,l product space of te W over eac l suc tat Γ,l. Te discrete constrained space is ten defined by K K V = {(u,p ) ( X) ( W ), is te,l ((p, + αu, ) ( p,l + αu,l ))ψ,,l =, ψ,,l W }, Γ,l and te discrete problem is te following: Find (u,p ) V suc tat v = (v,,...v,k ) K X, ( u, v, +u, v, ) dx p, v, ds= f v, dx. (5) Ω Ω Ω Te discrete algoritm is ten as follows: let (u n,, pn, ) X W be a discrete approximation of (u,p) in Ω at step n. Ten, (u n+ ) is te,, pn+, solution in X W of ( ) u n+, v,+u n+, v, dx p n+, v,ds= f v, dx, v, X, (6) Ω Ω Ω (p n+, + αun+, )ψ,,l = ( p n,l + αu n,l,l)ψ,,l, ψ,,l W. (7) Γ,l Γ,l Remar. Let π,l denote te ortogonal projection operator from L 2 (Γ,l ) onto. Ten (7) corresponds to W,l p n+, + απ,l(u n+, ) = π,l( p n,l + αun,l ) over Γ,l. (8) Remar 2. A fundamental difference between tis metod and te original mortar metod in Bernardi et al. [994] is tat te interface conditions are cosen in a symmetric way: tere is no master and no slave, see also Gander et al. [2]. Equation (8) is te transmission condition on Γ,l for Ω, and te transmission condition on Γ,l for Ω l is p n+,l + απ l, (u n+,l ) = π l,( p n, + αun, ) over Γ,l. (9) In order to analyze te convergence of tis iterative sceme, we define for any p in K L2 ( Ω ) te norm p 2, = ( K l= l p 2 ) H 2, 2 (Γ,l )
5 were. H 2 (Γ,l ) Nonconforming Grids wit Robin Interface Conditions 263 stands for te dual norm of H 2 (Γ,l ). Convergence of te algoritm (6)-(7) can be sown again using an energy estimate, see Japet et al. [23]. Teorem 2. Assume tat α c for some constant c small enoug. Ten, te discrete problem (5) as a unique solution (u,p ) V. Te algoritm (6)-(7) is well posed and converges in te sense tat lim n ( un, u, H (Ω ) + p n, p, ) =, for K. H 2 (Γ,l ) l 3 Best approximation properties In tis part we give best approximation results of (u,p) by elements in V. Te proofs can be found in Japet et al. [23] for te two dimensional case wit te degree of te finite element approximations M 3 and in tree dimensions for first order approximations. Teorem 3. Assume tat te solution u of () is in H 2 (Ω) H (Ω) and u = u Ω H 2+m (Ω ) wit M m, and let p,l = u n over eac Γ,l. Ten, tere exists a constant c independent of and α suc tat u u + p p 2, c(α2+m + +m ) + c( m α + +m ) u H 2+m (Ω ) p,l. H +m 2 (Γ,l ) Assuming more regularity on te normal derivatives on te interfaces, we ave Teorem 4. Assume tat te solution u of () is in H 2 (Ω) H (Ω) and u = u Ω H 2+m (Ω ) wit M m, and p,l = u n is in H 3 2 +m (Γ,l ). Ten tere exists a constant c independent of and α suc tat u u + p p 2, c(α 2+m + +m ) + c( +m α + 2+m )(log ) β(m) l u H 2+m (Ω ) p,l 3. H +m 2 (Γ,l ) Remar 3. Te Robin parameter α can depend on in te previous teorems, lie te optimal Robin parameter α opt in section 5. l
6 264 Martin J. Gander, Caroline Japet, Yvon Maday, and Frédéric Nataf 4 Efficient projection algoritm Te projection (8) between non conforming grids is not an easy tas in an algoritm, already for two dimensional problems, since one needs to find te intersections of corresponding arbitrary grid cells. A sort and efficient algoritm as been proposed in Gander et al. [2] in te finite volume case wit projections on piecewise constant functions. In our case, we denote by n te dimension of W,l, and we introduce te sape functions {ψ,l i } i n of W,l. Ten, to compute te rigt and side in (7), we need to compute te interface matrix M = ( ψ,l i Γ,l ψ l, j ) i,j n. In te same spirit as in Gander et al. [2], te following sort algoritm in Matlab computes te interface matrix M for non-matcing grids in one pass. function M=InterfaceMatrix(ta,tb); n=lengt(tb); m=lengt(ta); ta(m)=tb(n); % must be numerically equal j=; M=zeros(n,lengt(ta)); for i=:n-, tm=tb(i); wile ta(j+)<tb(i+), M(i:i+,j:j+)=M(i:i+,j:j+)+intMortar(ta(j),ta(j+),... tb(i),tb(i+),tm,ta(j+),j== j==m-,i== i==n-); j=j+; tm=ta(j); end; M(i:i+,j:j+)=M(i:i+,j:j+)+intMortar(ta(j),ta(j+),... tb(i),tb(i+),tm,tb(i+),j== j==m-,i== i==n-); end; It taes two vectors ta and tb wit ordered entries, wic represent two non-matcing grids at te interface, wit ta()=tb(), ta(end)=tb(end), and computes te matrix M(i,j)= Γ,l b i a j, were b i is te at function for te node tb(i) and a j is te at function for te node ta(j). Te mortar condition of constant sape functions at te corners is taen into account, and from te resulting matrix M te first and last row and column needs to be removed. Tis algoritm as linear complexity; it does a single pass witout any special cases or any additional grid. It advances automatically on watever side te next cell boundary is coming and andles any possible cases of non-matcing grids at a one dimensional interface. 5 Numerical results On te unit square Ω = (, ) (, ) we consider te problem
7 y Nonconforming Grids wit Robin Interface Conditions 265 (Id )u(x, y) = x 3 (y 2 2) 6xy 2 + ( + x 2 + y 2 )sin(xy), (x, y) Ω, u = x 3 y 2 + sin(xy), (x, y) Ω, wose exact solution is u(x, y) = x 3 y 2 + sin(xy). We decompose te unit square into four non-overlapping subdomains wit meses generated in an independent manner, as sown in Figure on te left. Te computed solution Initial Mes Computed solution x.8.6 y x Fig.. Initial mes and computed solution after two refinements. is te solution at convergence ( of te discrete algoritm (6)-(7), wit) stopping criterion max,l/γ,l ((p Γ,l, + αu, ) ( p,l + αu,l ))ψ,l < 8, and α =. On Figure on te rigt, we sow te computed solution. Figure 2 on te left corresponds to te best approximation error of Teorem 4. On te rigt, we compare in te case of two subdomains te optimal log(h discrete error) log() 7 2 subdomains Nonconforming case alpa_opt 65 6 log(error) 2 number of iterations log() alpa Fig. 2. H error versus on te left and number of iterations versus α on te rigt. numerical α to te teoretical value, wic minimizes te convergence rate at te continuous level: α opt = [(π 2 π + )(( min ) 2 + )] 4. Te nonconforming meses ave 289 and 56 nodes respectively, and te discretization parame-
8 266 Martin J. Gander, Caroline Japet, Yvon Maday, and Frédéric Nataf ters are =.65 and 2 =.32. We observe tat te optimal numerical α is very close to α opt. References Y. Acdou, C. Japet, Y. Maday, and F. Nataf. A new cement to glue nonconforming grids wit Robin interface conditions: te finite volume case. Numer. Mat., 92(4):593 62, 22. F. B. Belgacem and Y. Maday. Te mortar element metod for tree dimensional finite elements. RAIRO Matematical Modelling and Numerical Analysis, 3(2):289 32, 997. C. Bernardi, Y. Maday, and A. T. Patera. A new non conforming approac to domain decomposition: Te mortar element metod. In H. Brezis and J.-L. Lions, editors, Collège de France Seminar. Pitman, 994. Tis paper appeared as a tecnical report about five years earlier. D. Braess and W. Damen. Stability estimates of te mortar finite element metod for 3-dimensional problems. East-West J. Numer. Mat., 6(4): , 998. P. Cevalier and F. Nataf. Symmetrized metod wit optimized second-order conditions for te Helmoltz equation. In Domain decomposition metods, (Boulder, CO, 997), pages Amer. Mat. Soc., Providence, RI, 998. B. Després. Domain decomposition metod and te elmoltz problem. In SIAM, editor, Matematical and Numerical aspects of wave propagation penomena, pages Piladelpia PA, 99. M. J. Gander, L. Halpern, and F. Nataf. Optimal Scwarz waveform relaxation for te one dimensional wave equation. Tecnical Report 469, CMAP, Ecole Polytecnique, September 2. F. Gastaldi, L. Gastaldi, and A. Quarteroni. Adaptive domain decomposition metods for advection dominated equations. East-West J. Numer. Mat., 4:65 26, 996. C. Japet. Optimized Krylov-Ventcell metod. Application to convectiondiffusion problems. In P. E. Bjørstad, M. S. Espedal, and D. E. Keyes, editors, Proceedings of te 9t international conference on domain decomposition metods, pages ddm.org, 998. C. Japet, Y. Maday, and F. Nataf. A new cement to glue nonconforming grids wit robin interface conditions: Te finite element case. to be submitted, 23. F. Nataf, F. Rogier, and E. de Sturler. Domain decomposition metods for fluid dynamics, Navier-Stoes equations and related nonlinear analysis. Edited by A. Sequeira, Plenum Press Corporation, pages , 995.
Verifying Numerical Convergence Rates
1 Order of accuracy Verifying Numerical Convergence Rates We consider a numerical approximation of an exact value u. Te approximation depends on a small parameter, suc as te grid size or time step, and
FINITE DIFFERENCE METHODS
FINITE DIFFERENCE METHODS LONG CHEN Te best known metods, finite difference, consists of replacing eac derivative by a difference quotient in te classic formulation. It is simple to code and economic to
OPTIMAL DISCONTINUOUS GALERKIN METHODS FOR THE ACOUSTIC WAVE EQUATION IN HIGHER DIMENSIONS
OPTIMAL DISCONTINUOUS GALERKIN METHODS FOR THE ACOUSTIC WAVE EQUATION IN HIGHER DIMENSIONS ERIC T. CHUNG AND BJÖRN ENGQUIST Abstract. In tis paper, we developed and analyzed a new class of discontinuous
The finite element immersed boundary method: model, stability, and numerical results
Te finite element immersed boundary metod: model, stability, and numerical results Lucia Gastaldi Università di Brescia ttp://dm.ing.unibs.it/gastaldi/ INdAM Worksop, Cortona, September 18, 2006 Joint
Projective Geometry. Projective Geometry
Euclidean versus Euclidean geometry describes sapes as tey are Properties of objects tat are uncanged by rigid motions» Lengts» Angles» Parallelism Projective geometry describes objects as tey appear Lengts,
Part II: Finite Difference/Volume Discretisation for CFD
Part II: Finite Difference/Volume Discretisation for CFD Finite Volume Metod of te Advection-Diffusion Equation A Finite Difference/Volume Metod for te Incompressible Navier-Stokes Equations Marker-and-Cell
The EOQ Inventory Formula
Te EOQ Inventory Formula James M. Cargal Matematics Department Troy University Montgomery Campus A basic problem for businesses and manufacturers is, wen ordering supplies, to determine wat quantity of
Introduction to the Finite Element Method
Introduction to the Finite Element Method 09.06.2009 Outline Motivation Partial Differential Equations (PDEs) Finite Difference Method (FDM) Finite Element Method (FEM) References Motivation Figure: cross
Research on the Anti-perspective Correction Algorithm of QR Barcode
Researc on te Anti-perspective Correction Algoritm of QR Barcode Jianua Li, Yi-Wen Wang, YiJun Wang,Yi Cen, Guoceng Wang Key Laboratory of Electronic Tin Films and Integrated Devices University of Electronic
ACT Math Facts & Formulas
Numbers, Sequences, Factors Integers:..., -3, -2, -1, 0, 1, 2, 3,... Rationals: fractions, tat is, anyting expressable as a ratio of integers Reals: integers plus rationals plus special numbers suc as
An Additive Neumann-Neumann Method for Mortar Finite Element for 4th Order Problems
An Additive eumann-eumann Method for Mortar Finite Element for 4th Order Problems Leszek Marcinkowski Department of Mathematics, University of Warsaw, Banacha 2, 02-097 Warszawa, Poland, [email protected]
An inquiry into the multiplier process in IS-LM model
An inquiry into te multiplier process in IS-LM model Autor: Li ziran Address: Li ziran, Room 409, Building 38#, Peing University, Beijing 00.87,PRC. Pone: (86) 00-62763074 Internet Address: [email protected]
Computer Science and Engineering, UCSD October 7, 1999 Goldreic-Levin Teorem Autor: Bellare Te Goldreic-Levin Teorem 1 Te problem We æx a an integer n for te lengt of te strings involved. If a is an n-bit
Geometric Stratification of Accounting Data
Stratification of Accounting Data Patricia Gunning * Jane Mary Horgan ** William Yancey *** Abstract: We suggest a new procedure for defining te boundaries of te strata in igly skewed populations, usual
1 The Collocation Method
CS410 Assignment 7 Due: 1/5/14 (Fri) at 6pm You must wor eiter on your own or wit one partner. You may discuss bacground issues and general solution strategies wit oters, but te solutions you submit must
Distances in random graphs with infinite mean degrees
Distances in random graps wit infinite mean degrees Henri van den Esker, Remco van der Hofstad, Gerard Hoogiemstra and Dmitri Znamenski April 26, 2005 Abstract We study random graps wit an i.i.d. degree
SAT Subject Math Level 1 Facts & Formulas
Numbers, Sequences, Factors Integers:..., -3, -2, -1, 0, 1, 2, 3,... Reals: integers plus fractions, decimals, and irrationals ( 2, 3, π, etc.) Order Of Operations: Aritmetic Sequences: PEMDAS (Parenteses
Training Robust Support Vector Regression via D. C. Program
Journal of Information & Computational Science 7: 12 (2010) 2385 2394 Available at ttp://www.joics.com Training Robust Support Vector Regression via D. C. Program Kuaini Wang, Ping Zong, Yaoong Zao College
Optimized Data Indexing Algorithms for OLAP Systems
Database Systems Journal vol. I, no. 2/200 7 Optimized Data Indexing Algoritms for OLAP Systems Lucian BORNAZ Faculty of Cybernetics, Statistics and Economic Informatics Academy of Economic Studies, Bucarest
Domain Decomposition Methods. Partial Differential Equations
Domain Decomposition Methods for Partial Differential Equations ALFIO QUARTERONI Professor ofnumericalanalysis, Politecnico di Milano, Italy, and Ecole Polytechnique Federale de Lausanne, Switzerland ALBERTO
Instantaneous Rate of Change:
Instantaneous Rate of Cange: Last section we discovered tat te average rate of cange in F(x) can also be interpreted as te slope of a scant line. Te average rate of cange involves te cange in F(x) over
A Multigrid Tutorial part two
A Multigrid Tutorial part two William L. Briggs Department of Matematics University of Colorado at Denver Van Emden Henson Center for Applied Scientific Computing Lawrence Livermore National Laboratory
Comparison between two approaches to overload control in a Real Server: local or hybrid solutions?
Comparison between two approaces to overload control in a Real Server: local or ybrid solutions? S. Montagna and M. Pignolo Researc and Development Italtel S.p.A. Settimo Milanese, ITALY Abstract Tis wor
Note nine: Linear programming CSE 101. 1 Linear constraints and objective functions. 1.1 Introductory example. Copyright c Sanjoy Dasgupta 1
Copyrigt c Sanjoy Dasgupta Figure. (a) Te feasible region for a linear program wit two variables (see tet for details). (b) Contour lines of te objective function: for different values of (profit). Te
Derivatives Math 120 Calculus I D Joyce, Fall 2013
Derivatives Mat 20 Calculus I D Joyce, Fall 203 Since we ave a good understanding of its, we can develop derivatives very quickly. Recall tat we defined te derivative f x of a function f at x to be te
2.1: The Derivative and the Tangent Line Problem
.1.1.1: Te Derivative and te Tangent Line Problem Wat is te deinition o a tangent line to a curve? To answer te diiculty in writing a clear deinition o a tangent line, we can deine it as te iting position
To motivate the notion of a variogram for a covariance stationary process, { Ys ( ): s R}
4. Variograms Te covariogram and its normalized form, te correlogram, are by far te most intuitive metods for summarizing te structure of spatial dependencies in a covariance stationary process. However,
Schedulability Analysis under Graph Routing in WirelessHART Networks
Scedulability Analysis under Grap Routing in WirelessHART Networks Abusayeed Saifulla, Dolvara Gunatilaka, Paras Tiwari, Mo Sa, Cenyang Lu, Bo Li Cengjie Wu, and Yixin Cen Department of Computer Science,
In other words the graph of the polynomial should pass through the points
Capter 3 Interpolation Interpolation is te problem of fitting a smoot curve troug a given set of points, generally as te grap of a function. It is useful at least in data analysis (interpolation is a form
SAMPLE DESIGN FOR THE TERRORISM RISK INSURANCE PROGRAM SURVEY
ASA Section on Survey Researc Metods SAMPLE DESIG FOR TE TERRORISM RISK ISURACE PROGRAM SURVEY G. ussain Coudry, Westat; Mats yfjäll, Statisticon; and Marianne Winglee, Westat G. ussain Coudry, Westat,
1.6. Analyse Optimum Volume and Surface Area. Maximum Volume for a Given Surface Area. Example 1. Solution
1.6 Analyse Optimum Volume and Surface Area Estimation and oter informal metods of optimizing measures suc as surface area and volume often lead to reasonable solutions suc as te design of te tent in tis
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
Can a Lump-Sum Transfer Make Everyone Enjoy the Gains. from Free Trade?
Can a Lump-Sum Transfer Make Everyone Enjoy te Gains from Free Trade? Yasukazu Icino Department of Economics, Konan University June 30, 2010 Abstract I examine lump-sum transfer rules to redistribute te
The modelling of business rules for dashboard reporting using mutual information
8 t World IMACS / MODSIM Congress, Cairns, Australia 3-7 July 2009 ttp://mssanz.org.au/modsim09 Te modelling of business rules for dasboard reporting using mutual information Gregory Calbert Command, Control,
M(0) = 1 M(1) = 2 M(h) = M(h 1) + M(h 2) + 1 (h > 1)
Insertion and Deletion in VL Trees Submitted in Partial Fulfillment of te Requirements for Dr. Eric Kaltofen s 66621: nalysis of lgoritms by Robert McCloskey December 14, 1984 1 ackground ccording to Knut
Improved dynamic programs for some batcing problems involving te maximum lateness criterion A P M Wagelmans Econometric Institute Erasmus University Rotterdam PO Box 1738, 3000 DR Rotterdam Te Neterlands
2 Limits and Derivatives
2 Limits and Derivatives 2.7 Tangent Lines, Velocity, and Derivatives A tangent line to a circle is a line tat intersects te circle at exactly one point. We would like to take tis idea of tangent line
Lecture 10: What is a Function, definition, piecewise defined functions, difference quotient, domain of a function
Lecture 10: Wat is a Function, definition, piecewise defined functions, difference quotient, domain of a function A function arises wen one quantity depends on anoter. Many everyday relationsips between
Inner product. Definition of inner product
Math 20F Linear Algebra Lecture 25 1 Inner product Review: Definition of inner product. Slide 1 Norm and distance. Orthogonal vectors. Orthogonal complement. Orthogonal basis. Definition of inner product
SAT Math Must-Know Facts & Formulas
SAT Mat Must-Know Facts & Formuas Numbers, Sequences, Factors Integers:..., -3, -2, -1, 0, 1, 2, 3,... Rationas: fractions, tat is, anyting expressabe as a ratio of integers Reas: integers pus rationas
- 1 - Handout #22 May 23, 2012 Huffman Encoding and Data Compression. CS106B Spring 2012. Handout by Julie Zelenski with minor edits by Keith Schwarz
CS106B Spring 01 Handout # May 3, 01 Huffman Encoding and Data Compression Handout by Julie Zelenski wit minor edits by Keit Scwarz In te early 1980s, personal computers ad ard disks tat were no larger
Tangent Lines and Rates of Change
Tangent Lines and Rates of Cange 9-2-2005 Given a function y = f(x), ow do you find te slope of te tangent line to te grap at te point P(a, f(a))? (I m tinking of te tangent line as a line tat just skims
FORCED AND NATURAL CONVECTION HEAT TRANSFER IN A LID-DRIVEN CAVITY
FORCED AND NATURAL CONVECTION HEAT TRANSFER IN A LID-DRIVEN CAVITY Guillermo E. Ovando Cacón UDIM, Instituto Tecnológico de Veracruz, Calzada Miguel Angel de Quevedo 2779, CP. 9860, Veracruz, Veracruz,
Recall that two vectors in are perpendicular or orthogonal provided that their dot
Orthogonal Complements and Projections Recall that two vectors in are perpendicular or orthogonal provided that their dot product vanishes That is, if and only if Example 1 The vectors in are orthogonal
3. INNER PRODUCT SPACES
. INNER PRODUCT SPACES.. Definition So far we have studied abstract vector spaces. These are a generalisation of the geometric spaces R and R. But these have more structure than just that of a vector space.
Metric Spaces. Chapter 7. 7.1. Metrics
Chapter 7 Metric Spaces A metric space is a set X that has a notion of the distance d(x, y) between every pair of points x, y X. The purpose of this chapter is to introduce metric spaces and give some
How To Ensure That An Eac Edge Program Is Successful
Introduction Te Economic Diversification and Growt Enterprises Act became effective on 1 January 1995. Te creation of tis Act was to encourage new businesses to start or expand in Newfoundland and Labrador.
Duality of linear conic problems
Duality of linear conic problems Alexander Shapiro and Arkadi Nemirovski Abstract It is well known that the optimal values of a linear programming problem and its dual are equal to each other if at least
Math Test Sections. The College Board: Expanding College Opportunity
Taking te SAT I: Reasoning Test Mat Test Sections Te materials in tese files are intended for individual use by students getting ready to take an SAT Program test; permission for any oter use must be sougt
Mathematics Course 111: Algebra I Part IV: Vector Spaces
Mathematics Course 111: Algebra I Part IV: Vector Spaces D. R. Wilkins Academic Year 1996-7 9 Vector Spaces A vector space over some field K is an algebraic structure consisting of a set V on which are
PATTERN RECOGNITION AND MACHINE LEARNING CHAPTER 4: LINEAR MODELS FOR CLASSIFICATION
PATTERN RECOGNITION AND MACHINE LEARNING CHAPTER 4: LINEAR MODELS FOR CLASSIFICATION Introduction In the previous chapter, we explored a class of regression models having particularly simple analytical
Høgskolen i Narvik Sivilingeniørutdanningen STE6237 ELEMENTMETODER. Oppgaver
Høgskolen i Narvik Sivilingeniørutdanningen STE637 ELEMENTMETODER Oppgaver Klasse: 4.ID, 4.IT Ekstern Professor: Gregory A. Chechkin e-mail: [email protected] Narvik 6 PART I Task. Consider two-point
Perimeter, Area and Volume of Regular Shapes
Perimeter, Area and Volume of Regular Sapes Perimeter of Regular Polygons Perimeter means te total lengt of all sides, or distance around te edge of a polygon. For a polygon wit straigt sides tis is te
Equilibria in sequential bargaining games as solutions to systems of equations
Economics Letters 84 (2004) 407 411 www.elsevier.com/locate/econbase Equilibria in sequential bargaining games as solutions to systems of equations Tasos Kalandrakis* Department of Political Science, Yale
Binary Image Reconstruction
A network flow algorithm for reconstructing binary images from discrete X-rays Kees Joost Batenburg Leiden University and CWI, The Netherlands [email protected] Abstract We present a new algorithm
Multivariate time series analysis: Some essential notions
Capter 2 Multivariate time series analysis: Some essential notions An overview of a modeling and learning framework for multivariate time series was presented in Capter 1. In tis capter, some notions on
Linear Threshold Units
Linear Threshold Units w x hx (... w n x n w We assume that each feature x j and each weight w j is a real number (we will relax this later) We will study three different algorithms for learning linear
MATHEMATICS FOR ENGINEERING DIFFERENTIATION TUTORIAL 1 - BASIC DIFFERENTIATION
MATHEMATICS FOR ENGINEERING DIFFERENTIATION TUTORIAL 1 - BASIC DIFFERENTIATION Tis tutorial is essential pre-requisite material for anyone stuing mecanical engineering. Tis tutorial uses te principle of
OPTIMAL FLEET SELECTION FOR EARTHMOVING OPERATIONS
New Developments in Structural Engineering and Construction Yazdani, S. and Sing, A. (eds.) ISEC-7, Honolulu, June 18-23, 2013 OPTIMAL FLEET SELECTION FOR EARTHMOVING OPERATIONS JIALI FU 1, ERIK JENELIUS
Integrating Benders decomposition within Constraint Programming
Integrating Benders decomposition within Constraint Programming Hadrien Cambazard, Narendra Jussien email: {hcambaza,jussien}@emn.fr École des Mines de Nantes, LINA CNRS FRE 2729 4 rue Alfred Kastler BP
An Intuitive Framework for Real-Time Freeform Modeling
An Intuitive Framework for Real-Time Freeform Modeling Mario Botsc Leif Kobbelt Computer Grapics Group RWTH Aacen University Abstract We present a freeform modeling framework for unstructured triangle
CHAPTER 7. Di erentiation
CHAPTER 7 Di erentiation 1. Te Derivative at a Point Definition 7.1. Let f be a function defined on a neigborood of x 0. f is di erentiable at x 0, if te following it exists: f 0 fx 0 + ) fx 0 ) x 0 )=.
New Vocabulary volume
-. Plan Objectives To find te volume of a prism To find te volume of a cylinder Examples Finding Volume of a Rectangular Prism Finding Volume of a Triangular Prism 3 Finding Volume of a Cylinder Finding
Cyber Epidemic Models with Dependences
Cyber Epidemic Models wit Dependences Maocao Xu 1, Gaofeng Da 2 and Souuai Xu 3 1 Department of Matematics, Illinois State University [email protected] 2 Institute for Cyber Security, University of Texas
Channel Allocation in Non-Cooperative Multi-Radio Multi-Channel Wireless Networks
Cannel Allocation in Non-Cooperative Multi-Radio Multi-Cannel Wireless Networks Dejun Yang, Xi Fang, Guoliang Xue Arizona State University Abstract Wile tremendous efforts ave been made on cannel allocation
Surface bundles over S 1, the Thurston norm, and the Whitehead link
Surface bundles over S 1, the Thurston norm, and the Whitehead link Michael Landry August 16, 2014 The Thurston norm is a powerful tool for studying the ways a 3-manifold can fiber over the circle. In
Solutions by: KARATUĞ OZAN BiRCAN. PROBLEM 1 (20 points): Let D be a region, i.e., an open connected set in
KOÇ UNIVERSITY, SPRING 2014 MATH 401, MIDTERM-1, MARCH 3 Instructor: BURAK OZBAGCI TIME: 75 Minutes Solutions by: KARATUĞ OZAN BiRCAN PROBLEM 1 (20 points): Let D be a region, i.e., an open connected set
Mean Value Coordinates
Mean Value Coordinates Michael S. Floater Abstract: We derive a generalization of barycentric coordinates which allows a vertex in a planar triangulation to be expressed as a convex combination of its
Orthogonal Projections
Orthogonal Projections and Reflections (with exercises) by D. Klain Version.. Corrections and comments are welcome! Orthogonal Projections Let X,..., X k be a family of linearly independent (column) vectors
Compute the derivative by definition: The four step procedure
Compute te derivative by definition: Te four step procedure Given a function f(x), te definition of f (x), te derivative of f(x), is lim 0 f(x + ) f(x), provided te limit exists Te derivative function
Discussion on the paper Hypotheses testing by convex optimization by A. Goldenschluger, A. Juditsky and A. Nemirovski.
Discussion on the paper Hypotheses testing by convex optimization by A. Goldenschluger, A. Juditsky and A. Nemirovski. Fabienne Comte, Celine Duval, Valentine Genon-Catalot To cite this version: Fabienne
The Derivative as a Function
Section 2.2 Te Derivative as a Function 200 Kiryl Tsiscanka Te Derivative as a Function DEFINITION: Te derivative of a function f at a number a, denoted by f (a), is if tis limit exists. f (a) f(a+) f(a)
We shall turn our attention to solving linear systems of equations. Ax = b
59 Linear Algebra We shall turn our attention to solving linear systems of equations Ax = b where A R m n, x R n, and b R m. We already saw examples of methods that required the solution of a linear system
Determine the perimeter of a triangle using algebra Find the area of a triangle using the formula
Student Name: Date: Contact Person Name: Pone Number: Lesson 0 Perimeter, Area, and Similarity of Triangles Objectives Determine te perimeter of a triangle using algebra Find te area of a triangle using
Algebra Unpacked Content For the new Common Core standards that will be effective in all North Carolina schools in the 2012-13 school year.
This document is designed to help North Carolina educators teach the Common Core (Standard Course of Study). NCDPI staff are continually updating and improving these tools to better serve teachers. Algebra
Catalogue no. 12-001-XIE. Survey Methodology. December 2004
Catalogue no. 1-001-XIE Survey Metodology December 004 How to obtain more information Specific inquiries about tis product and related statistics or services sould be directed to: Business Survey Metods
Math 113 HW #5 Solutions
Mat 3 HW #5 Solutions. Exercise.5.6. Suppose f is continuous on [, 5] and te only solutions of te equation f(x) = 6 are x = and x =. If f() = 8, explain wy f(3) > 6. Answer: Suppose we ad tat f(3) 6. Ten
Haptic Manipulation of Virtual Materials for Medical Application
Haptic Manipulation of Virtual Materials for Medical Application HIDETOSHI WAKAMATSU, SATORU HONMA Graduate Scool of Healt Care Sciences Tokyo Medical and Dental University, JAPAN [email protected]
Section 2.3 Solving Right Triangle Trigonometry
Section.3 Solving Rigt Triangle Trigonometry Eample In te rigt triangle ABC, A = 40 and c = 1 cm. Find a, b, and B. sin 40 a a c 1 a 1sin 40 7.7cm cos 40 b c b 1 b 1cos40 9.cm A 40 1 b C B a B = 90 - A
On a Satellite Coverage
I. INTRODUCTION On a Satellite Coverage Problem DANNY T. CHI Kodak Berkeley Researc Yu T. su National Ciao Tbng University Te eart coverage area for a satellite in an Eart syncronous orbit wit a nonzero
Pre-trial Settlement with Imperfect Private Monitoring
Pre-trial Settlement wit Imperfect Private Monitoring Mostafa Beskar University of New Hampsire Jee-Hyeong Park y Seoul National University July 2011 Incomplete, Do Not Circulate Abstract We model pretrial
NOTES ON LINEAR TRANSFORMATIONS
NOTES ON LINEAR TRANSFORMATIONS Definition 1. Let V and W be vector spaces. A function T : V W is a linear transformation from V to W if the following two properties hold. i T v + v = T v + T v for all
2.3 Convex Constrained Optimization Problems
42 CHAPTER 2. FUNDAMENTAL CONCEPTS IN CONVEX OPTIMIZATION Theorem 15 Let f : R n R and h : R R. Consider g(x) = h(f(x)) for all x R n. The function g is convex if either of the following two conditions
How To Prove The Dirichlet Unit Theorem
Chapter 6 The Dirichlet Unit Theorem As usual, we will be working in the ring B of algebraic integers of a number field L. Two factorizations of an element of B are regarded as essentially the same if
THREE DIMENSIONAL GEOMETRY
Chapter 8 THREE DIMENSIONAL GEOMETRY 8.1 Introduction In this chapter we present a vector algebra approach to three dimensional geometry. The aim is to present standard properties of lines and planes,
SHARP BOUNDS FOR THE SUM OF THE SQUARES OF THE DEGREES OF A GRAPH
31 Kragujevac J. Math. 25 (2003) 31 49. SHARP BOUNDS FOR THE SUM OF THE SQUARES OF THE DEGREES OF A GRAPH Kinkar Ch. Das Department of Mathematics, Indian Institute of Technology, Kharagpur 721302, W.B.,
Tis Problem and Retail Inventory Management
Optimizing Inventory Replenisment of Retail Fasion Products Marsall Fiser Kumar Rajaram Anant Raman Te Warton Scool, University of Pennsylvania, 3620 Locust Walk, 3207 SH-DH, Piladelpia, Pennsylvania 19104-6366
Section 3.3. Differentiation of Polynomials and Rational Functions. Difference Equations to Differential Equations
Difference Equations to Differential Equations Section 3.3 Differentiation of Polynomials an Rational Functions In tis section we begin te task of iscovering rules for ifferentiating various classes of
How High a Degree is High Enough for High Order Finite Elements?
This space is reserved for the Procedia header, do not use it How High a Degree is High Enough for High Order Finite Elements? William F. National Institute of Standards and Technology, Gaithersburg, Maryland,
NP-Hardness Results Related to PPAD
NP-Hardness Results Related to PPAD Chuangyin Dang Dept. of Manufacturing Engineering & Engineering Management City University of Hong Kong Kowloon, Hong Kong SAR, China E-Mail: [email protected] Yinyu
Average and Instantaneous Rates of Change: The Derivative
9.3 verage and Instantaneous Rates of Cange: Te Derivative 609 OBJECTIVES 9.3 To define and find average rates of cange To define te derivative as a rate of cange To use te definition of derivative to
