Exercises - Chapter 1 - Chapter 2 (Correction)

Size: px
Start display at page:

Download "Exercises - Chapter 1 - Chapter 2 (Correction)"

Transcription

1 Université de Nice Sophia-Antipolis Master MathMods - Finite Elements - 28/29 Exercises - Chapter 1 - Chapter 2 Correction) Exercise 1. a) Let I =], l[, l R. Show that Cl) >, u C Ī) Cl) u H 1 I), u DĪ). 1) Let u DĪ). Let x,y Ī. The fondamental theorem of analysis gives ux) = uy) + x y u s)ds, which leads to l ux) uy) + u s) ds, By means of Cauchy-Schwarz inequality, one gets ux) uy) + l l u s) ds) Integrating the above inequality over [, l] in the y variable, and applying once again the Cauchy-Schwarz inequality, give or equivalently l ux) l ) 1 l uy) 2 2 l dy + l l u s) ds) 1 2 2, ux) max 1/ l, ) ) l u L 2 I) + u L 2 I). By using the the Cauchy-Schwarz inequality in R 2, denoting Cl) = 2 max 1/ l, ) l, and taking the supremum on x Ī, one obtains the result. Conclude that H 1 I) C Ī) in dimension 1. Let u H 1 I). Since DĪ) is dense in H1 I) for the norm H 1 I), there exists a sequence u n ) n DĪ) which converges to u in H1 I) for the norm H 1 I). Then the inequality 1) holds for each fonction u n : Cl) >, u n C Ī) Cl) u n H 1 I), n. 2) Since u n ) n is a Cauchy sequence in H 1 I), the sequence u n ) n is Cauchy in C Ī) for the uniform norm C Ī) by the inequality 2). The space C Ī) equipped with the norm C Ī) is complete: there exists w C Ī) such that u n) n converges to w in C Ī) for the norm C Ī). 1

2 On the one hand u n ) n converges to w in C Ī) for the norm C Ī) implies u n C Ī) w C Ī), and u n) n converges to u in H 1 I) for the norm H 1 I) leads u n H 1 I) u H 1 I). On the other hand u n ) n converges to u in H 1 I) for the norm H 1 I), leads to u n u a.e.. The sequence u n ) n converges to v in C Ī) for the norm C Ī), implies u n w in each point of Ī. This implies u = w a.e.. Then w is the continuous representant of the class u in H 1 I). Finally H 1 I) C Ī) in dimension 1. b) Let Ω = B,1/2) be the ball of radius 1/2 about the origine,) in R 2. Let v be the function defined on Ω by k vx) = ln x,k R. Study the continuity of v in the neighbourhood of the origine,), and then prove that for k < 1/2, v H 1 Ω). Conclude. Continuity lim ln x = + implies v is not bounded in the neighbourhood of the origine,) for x,) k >. Then v is continuous in Ω = B,1/2) for k. Regarding the belonging of v to H 1 Ω) The derivative of v with respect to x i, i = 1,2, is v x) = signln x )k x i x i x 2 k 1. ln x By the change of variables from cartesian coordinates to polar coordinates B, 1/2) ],1/2[ ],2π[, x = x 1,x 2 ) r,θ), one gets 2k 2 /2 v 2 H 1 I) = 2π 2k /2 ln r ln r r dr + 2πk 2 r 2 r dr. lim r = and for all α R,α, lim rln r) α =, imply the first integral is finite for all r r k R. The second integral is finite if only if 2k < i.e. k < 1/2. Then for k < 1/2, v H 1 Ω). Finally k < 1/2, v H 1 Ω) and v is not continuous in Ω. Exercise 2. Let be the following boundary value problem u x) = fx) on [,1], u) =, u 1) = α, 3) where f is a given function of L 2,1) and α R. a) Let V = {v H 1,1),v) = }. Prove that v 1,Ω = Ω = [,1], is a norm on V and V is a Hilbert space. ) 1 Ω v x) 2 dx 2, where 2

3 The critical point to prove that v 1,Ω = ) 1 Ω v x) 2 dx 2 is a norm, is to show that v 1,Ω = implies v = in H 1,1). Let v to be such a function. Then v = a.e. which implies v = constant a.e.. In dimension 1, v has a continuous representant, let call it w. Since v) =, one has w) = = constant and w =. Therefore v = w = a.e.. The norm v 1,Ω is equivalent to the norm v H 1,1)on H 1,1). v 1,Ω v 2 1,Ω + v 2 L 2,1)) 1 2 = v H 1,1). The converse inequality is obtained as follows. Let v V, then v H 1,1) in dimension 1 and v owns a continuous representant, let call it v. Then one has which implies vx) = v) + x v y)dy, x [,1], 1 vx) x2 v y) dy) 1 2 2, x [,1], Taking the square of the above inequality and then integrating in x over,1), one gets which leads to vx) 2 dx 1 2 v y) 2 dy, v 2 H 1,1) 3 2 v 2 1,Ω. 4) Let γ be the mapping γ : H 1,1) R, v v). Since H 1,1) C [,1]) in dimension 1, the mapping γ is well-defined. The mapping γ is linear and γv) = v) v C [,1]) C v H 1,1), where C >. This shows that γ is continuous. Then V = Ker γ is a closed subset of the Hilbert H 1,1). Therefore V is a Hilbert space. b) Give the variational problem and show that it has a unique solution. The variational problem Let v D[,1]). Multiplying the PDE 3) by v and integrating over [,1], one gets u x)vx)dx = fx)vx)dx. Integrating by part the left-hand side, one gets ) u x)v x)dx u 1)v1) u )v) = By taking v V et using u 1) = α, one obtains u x)v x)dx = α v1) + 3 fx)vx)dx. fx)vx)dx.

4 Let a : V V R, u,v) u x)v x)dx, L : V R, v αv1) + fx)vx)dx. The variational problem is the following: Find u V solution of v V, au,v) = Lv). 5) The solution of the variational problem The space V is a Hilbert space. The mapping a is a bilinear symmetric, continuous, coercive form on V : au,v) u 1,Ω v 1,Ω u,v V, av,v) = v 2 1,Ω v V. The mapping L is a linear continuous form on V : Lv) α v1) + f L 2,1) v L 2,1) α v C [,1]) + f L 2,1) v H 1,1) α C v H 1,1) + f L 2,1) v H 1,1) max α C, f L 2,1)) v H 1,1) β v 1,Ω, v V, 3 with β = 2 max α C, f L 2,1)). Finally thanks to Lax-Milgram theorem, there exists a unique solution u for the above variational problem. c) Recover formally the initial problem. Recovering the PDE Let u be the solution of the variational problem 5). Let one takes v D],1[) V in the variational problem 5). u x)v x)dx = α v1) + Since v D],1[), one has v1) = and u x)v x)dx = fx)vx)dx. fx)vx)dx. 6) One has also f L 2,1) D ],1[), u L 2,1) D ],1[). Then 6) rewrites as Then the PDE is u, v D D],1[) = f, v D, D],1[), or u, v D D],1[) = f, v D D],1[), or u f, v D D],1[) =. Since f L 2,1), the above PDE turns into u f = in D ],1[). u = f in L 2,1) a.e.. 7) 4

5 Recovering the boundary conditions Let one takes v V, multiplying 7) by v and integrating one gets u x)v x)dx = Then integrating by part and using v) =, one obtains fx)vx)dx. u x)v x)dx u 1)v1) = fx)vx)dx. The comparison of the above equation with the variational problem 5) gives u 1) = α. Obviously one has u) = since u V. Therefore the boundary value problem is u = f a.e. on [,1], u) =, u 1) = α, 8) where f is a given function of L 2,1) and α R. Exercise 3. a) Give the variational formulation of the boundary value problem u x) + ux) = fx) on [,1], u ) =, u 1) =, where f is a given function of L 2,1). Let V = H 1,1). Let a : V V R, u,v) u x)v x)dx + ux)vx)dx, L : V R, v fx)vx)dx. The variational problem of the PDE 3) is the following: Find u V solution of v V, au,v) = Lv). 9) b) Show that the variational problem has a unique solution. The solution of the variational problem The space V = H 1,1) is a Hilbert space. The mapping a is a bilinear symmetric, continuous, coercive form on V : au,v) u L 2,1) v L 2,1) + u L 2,1) v L 2,1), by Cauchy-Schwarz inequality in L 2,1) ) 1/2 1/2 u 2 L 2,1) + u 2 L 2,1) u 2 L 2,1) + u 2 L,1)), by Cauchy-Schwarz 2 = u H 1,1) v H 1,1) u,v V, av,v) = v 2 H 1,1) v V. inequality in R 2 5

6 The mapping L is a linear continuous form on V : Lv) f L 2,1) v L 2,1) f L 2,1) v H 1,1), v V. By Lax-Milgram theorem, there exists a unique solution u for the above variational problem. c) Recover formally the initial problem. Recovering the PDE Let u be the solution of the variational problem 9). Let one takes v D],1[) V in the variational problem 9). Since f L 2,1) D ],1[), u L 2,1) D ],1[), the variational problem 9) turns to Then the PDE is u, v D D],1[) + u, v D D],1[) = f, v D D],1[), or u, v D D],1[) + u, v D D],1[) = f, v D D],1[), or u + u f, v D D],1[) =. u + u f = in D ],1[). Since f L 2,1) and u L 2,1), one has u L 2,1) and the above PDE turns into u + u = f in L 2,1) a.e.. 1) Recovering the boundary conditions Let one takes v V = H 1,1), multiplying 9) by v and integrating one gets Then integrating by part gives u x)v x)dx u x)v x)dx = fx)vx)dx. ) u 1)v1) u )v) = fx)vx)dx. Then the comparison of the above equation with the variational problem 9) gives u ) = when taking v V = H 1,1) with v1) = and v). Then when taking v V = H 1,1) with v), one gets u ) =. Therefore the boundary value problem is u + u = f a.e. on [,1], u ) =, u 1) =, 11) where f is a given function of L 2,1). Exercise 4. Let Ω be a bounded subset of R n where n 1, with regular boundary Ω. Let be the following problem: Find u H 1 Ω) solution of v H 1 Ω), u v dx = Ω where f is a given function of L 2 Ω). Ω fv dx 12) 6

7 Show that this problem has a unique solution and give the associated initial boundary value problem. The solution of the variational problem Let a : H 1Ω) H1 Ω) R, u,v) Ω u v dx, L : H1 Ω) R, v Ω fv dx. The space V = H 1 Ω) is a Hilbert space. The trace mapping γ : H 1 Ω) L 2 Ω), u u Ω is linear continuous. Its kernel Ker γ = H 1Ω) is a closed subset of the Hilbert space H1 Ω). Therefore H 1 Ω) is a Hilbert space. Thanks to Poincaré theorem, the mapping u u 1,Ω = equivalent to the norm H 1 Ω) on H 1 Ω). ) /2 Ω ux) 2 dx is a norm The mapping a is a bilinear symmetric, continuous, coercive form on H 1 Ω): au,v) u L 2 Ω) v L 2 Ω) = u 1,Ω u 1,Ω, u,v H 1 Ω), av,v) = v 2 1,Ω v H1 Ω). The mapping L is a linear continuous form on H 1Ω): Lv) f L 2 Ω) v L 2 Ω) f L 2 Ω) v H 1 Ω) C f L 2 Ω) v 1,Ω, v H 1 Ω). By Lax-Milgram theorem, there exists a unique solution u for the above variational problem. Recovering the PDE Let u be the solution of the variational problem 12). Let one takes v DΩ) H 1 Ω) in the variational problem 12). Since f L 2 Ω) D Ω), u L 2 Ω) D Ω), the variational problem 12) turns to u, v D DΩ) = f, v D DΩ), or u, v D DΩ) = f, v D DΩ), or u f, v D DΩ) =. Then the PDE is u f = in D Ω). Since f L 2 Ω) and u L 2 Ω), one has u L 2 Ω) and the above PDE turns into u = f in L 2 Ω) a.e.. 13) Recovering the boundary conditions The solution of the the variational problem 12) u H 1 Ω), then u = on Ω. Therefore the boundary value problem is { u = f a.e. in Ω, u = on Ω, 14) where f is a given function of L 2 Ω). 7

Finite Elements. Colin Cotter. February 22, Colin Cotter FEM

Finite Elements. Colin Cotter. February 22, Colin Cotter FEM Finite Elements February 22, 2019 In the previous sections, we introduced the concept of finite element spaces, which contain certain functions defined on a domain. Finite element spaces are examples of

More information

Theory of PDE Homework 2

Theory of PDE Homework 2 Theory of PDE Homework 2 Adrienne Sands April 18, 2017 In the following exercises we assume the coefficients of the various PDE are smooth and satisfy the uniform ellipticity condition. R n is always an

More information

1. Subspaces A subset M of Hilbert space H is a subspace of it is closed under the operation of forming linear combinations;i.e.,

1. Subspaces A subset M of Hilbert space H is a subspace of it is closed under the operation of forming linear combinations;i.e., Abstract Hilbert Space Results We have learned a little about the Hilbert spaces L U and and we have at least defined H 1 U and the scale of Hilbert spaces H p U. Now we are going to develop additional

More information

Numerical Solutions to Partial Differential Equations

Numerical Solutions to Partial Differential Equations Numerical Solutions to Partial Differential Equations Zhiping Li LMAM and School of Mathematical Sciences Peking University Sobolev Embedding Theorems Embedding Operators and the Sobolev Embedding Theorem

More information

WELL POSEDNESS OF PROBLEMS I

WELL POSEDNESS OF PROBLEMS I Finite Element Method 85 WELL POSEDNESS OF PROBLEMS I Consider the following generic problem Lu = f, where L : X Y, u X, f Y and X, Y are two Banach spaces We say that the above problem is well-posed (according

More information

Your first day at work MATH 806 (Fall 2015)

Your first day at work MATH 806 (Fall 2015) Your first day at work MATH 806 (Fall 2015) 1. Let X be a set (with no particular algebraic structure). A function d : X X R is called a metric on X (and then X is called a metric space) when d satisfies

More information

One-dimensional and nonlinear problems

One-dimensional and nonlinear problems Solving PDE s with FEniCS One-dimensional and nonlinear problems L. Ridgway Scott The Institute for Biophysical Dynamics, The Computation Institute, and the Departments of Computer Science and Mathematics,

More information

LECTURE 1: SOURCES OF ERRORS MATHEMATICAL TOOLS A PRIORI ERROR ESTIMATES. Sergey Korotov,

LECTURE 1: SOURCES OF ERRORS MATHEMATICAL TOOLS A PRIORI ERROR ESTIMATES. Sergey Korotov, LECTURE 1: SOURCES OF ERRORS MATHEMATICAL TOOLS A PRIORI ERROR ESTIMATES Sergey Korotov, Institute of Mathematics Helsinki University of Technology, Finland Academy of Finland 1 Main Problem in Mathematical

More information

CONVERGENCE THEORY. G. ALLAIRE CMAP, Ecole Polytechnique. 1. Maximum principle. 2. Oscillating test function. 3. Two-scale convergence

CONVERGENCE THEORY. G. ALLAIRE CMAP, Ecole Polytechnique. 1. Maximum principle. 2. Oscillating test function. 3. Two-scale convergence 1 CONVERGENCE THEOR G. ALLAIRE CMAP, Ecole Polytechnique 1. Maximum principle 2. Oscillating test function 3. Two-scale convergence 4. Application to homogenization 5. General theory H-convergence) 6.

More information

EXAMINATION SOLUTIONS

EXAMINATION SOLUTIONS 1 Marks & (a) If f is continuous on (, ), then xf is continuously differentiable 5 on (,) and F = (xf)/x as well (as the quotient of two continuously differentiable functions with the denominator never

More information

Variational Formulations

Variational Formulations Chapter 2 Variational Formulations In this chapter we will derive a variational (or weak) formulation of the elliptic boundary value problem (1.4). We will discuss all fundamental theoretical results that

More information

2.3 Variational form of boundary value problems

2.3 Variational form of boundary value problems 2.3. VARIATIONAL FORM OF BOUNDARY VALUE PROBLEMS 21 2.3 Variational form of boundary value problems Let X be a separable Hilbert space with an inner product (, ) and norm. We identify X with its dual X.

More information

Appendix A Functional Analysis

Appendix A Functional Analysis Appendix A Functional Analysis A.1 Metric Spaces, Banach Spaces, and Hilbert Spaces Definition A.1. Metric space. Let X be a set. A map d : X X R is called metric on X if for all x,y,z X it is i) d(x,y)

More information

Simple Examples on Rectangular Domains

Simple Examples on Rectangular Domains 84 Chapter 5 Simple Examples on Rectangular Domains In this chapter we consider simple elliptic boundary value problems in rectangular domains in R 2 or R 3 ; our prototype example is the Poisson equation

More information

Fact Sheet Functional Analysis

Fact Sheet Functional Analysis Fact Sheet Functional Analysis Literature: Hackbusch, W.: Theorie und Numerik elliptischer Differentialgleichungen. Teubner, 986. Knabner, P., Angermann, L.: Numerik partieller Differentialgleichungen.

More information

Chapter 1 Foundations of Elliptic Boundary Value Problems 1.1 Euler equations of variational problems

Chapter 1 Foundations of Elliptic Boundary Value Problems 1.1 Euler equations of variational problems Chapter 1 Foundations of Elliptic Boundary Value Problems 1.1 Euler equations of variational problems Elliptic boundary value problems often occur as the Euler equations of variational problems the latter

More information

Weak Formulation of Elliptic BVP s

Weak Formulation of Elliptic BVP s Weak Formulation of Elliptic BVP s There are a large number of problems of physical interest that can be formulated in the abstract setting in which the Lax-Milgram lemma is applied to an equation expressed

More information

Second Order Elliptic PDE

Second Order Elliptic PDE Second Order Elliptic PDE T. Muthukumar tmk@iitk.ac.in December 16, 2014 Contents 1 A Quick Introduction to PDE 1 2 Classification of Second Order PDE 3 3 Linear Second Order Elliptic Operators 4 4 Periodic

More information

HARMONIC ANALYSIS. Date:

HARMONIC ANALYSIS. Date: HARMONIC ANALYSIS Contents. Introduction 2. Hardy-Littlewood maximal function 3. Approximation by convolution 4. Muckenhaupt weights 4.. Calderón-Zygmund decomposition 5. Fourier transform 6. BMO (bounded

More information

CHAPTER II HILBERT SPACES

CHAPTER II HILBERT SPACES CHAPTER II HILBERT SPACES 2.1 Geometry of Hilbert Spaces Definition 2.1.1. Let X be a complex linear space. An inner product on X is a function, : X X C which satisfies the following axioms : 1. y, x =

More information

Boundary Value Problems and Iterative Methods for Linear Systems

Boundary Value Problems and Iterative Methods for Linear Systems Boundary Value Problems and Iterative Methods for Linear Systems 1. Equilibrium Problems 1.1. Abstract setting We want to find a displacement u V. Here V is a complete vector space with a norm v V. In

More information

Sobolevology. 1. Definitions and Notation. When α = 1 this seminorm is the same as the Lipschitz constant of the function f. 2.

Sobolevology. 1. Definitions and Notation. When α = 1 this seminorm is the same as the Lipschitz constant of the function f. 2. Sobolevology 1. Definitions and Notation 1.1. The domain. is an open subset of R n. 1.2. Hölder seminorm. For α (, 1] the Hölder seminorm of exponent α of a function is given by f(x) f(y) [f] α = sup x

More information

An introduction to some aspects of functional analysis

An introduction to some aspects of functional analysis An introduction to some aspects of functional analysis Stephen Semmes Rice University Abstract These informal notes deal with some very basic objects in functional analysis, including norms and seminorms

More information

Partial Differential Equations 2 Variational Methods

Partial Differential Equations 2 Variational Methods Partial Differential Equations 2 Variational Methods Martin Brokate Contents 1 Variational Methods: Some Basics 1 2 Sobolev Spaces: Definition 9 3 Elliptic Boundary Value Problems 2 4 Boundary Conditions,

More information

Analysis IV : Assignment 3 Solutions John Toth, Winter ,...). In particular for every fixed m N the sequence (u (n)

Analysis IV : Assignment 3 Solutions John Toth, Winter ,...). In particular for every fixed m N the sequence (u (n) Analysis IV : Assignment 3 Solutions John Toth, Winter 203 Exercise (l 2 (Z), 2 ) is a complete and separable Hilbert space. Proof Let {u (n) } n N be a Cauchy sequence. Say u (n) = (..., u 2, (n) u (n),

More information

Applied Math Qualifying Exam 11 October Instructions: Work 2 out of 3 problems in each of the 3 parts for a total of 6 problems.

Applied Math Qualifying Exam 11 October Instructions: Work 2 out of 3 problems in each of the 3 parts for a total of 6 problems. Printed Name: Signature: Applied Math Qualifying Exam 11 October 2014 Instructions: Work 2 out of 3 problems in each of the 3 parts for a total of 6 problems. 2 Part 1 (1) Let Ω be an open subset of R

More information

A brief introduction to finite element methods

A brief introduction to finite element methods CHAPTER A brief introduction to finite element methods 1. Two-point boundary value problem and the variational formulation 1.1. The model problem. Consider the two-point boundary value problem: Given a

More information

LECTURE # 0 BASIC NOTATIONS AND CONCEPTS IN THE THEORY OF PARTIAL DIFFERENTIAL EQUATIONS (PDES)

LECTURE # 0 BASIC NOTATIONS AND CONCEPTS IN THE THEORY OF PARTIAL DIFFERENTIAL EQUATIONS (PDES) LECTURE # 0 BASIC NOTATIONS AND CONCEPTS IN THE THEORY OF PARTIAL DIFFERENTIAL EQUATIONS (PDES) RAYTCHO LAZAROV 1 Notations and Basic Functional Spaces Scalar function in R d, d 1 will be denoted by u,

More information

Partial Differential Equations and Sobolev Spaces MAT-INF4300 autumn Snorre H. Christiansen November 10, 2016

Partial Differential Equations and Sobolev Spaces MAT-INF4300 autumn Snorre H. Christiansen November 10, 2016 Partial Differential Equations and Sobolev Spaces MAT-INF4300 autumn 2016 Snorre H. Christiansen November 10, 2016 1 2 Contents 1 Introduction 5 2 Notations for differential operators 7 3 Generalities

More information

A Note on the Variational Formulation of PDEs and Solution by Finite Elements

A Note on the Variational Formulation of PDEs and Solution by Finite Elements Advanced Studies in Theoretical Physics Vol. 12, 2018, no. 4, 173-179 HIKARI Ltd, www.m-hikari.com https://doi.org/10.12988/astp.2018.8412 A Note on the Variational Formulation of PDEs and Solution by

More information

Real Variables # 10 : Hilbert Spaces II

Real Variables # 10 : Hilbert Spaces II randon ehring Real Variables # 0 : Hilbert Spaces II Exercise 20 For any sequence {f n } in H with f n = for all n, there exists f H and a subsequence {f nk } such that for all g H, one has lim (f n k,

More information

Linear Analysis Lecture 5

Linear Analysis Lecture 5 Linear Analysis Lecture 5 Inner Products and V Let dim V < with inner product,. Choose a basis B and let v, w V have coordinates in F n given by x 1. x n and y 1. y n, respectively. Let A F n n be the

More information

By (a), B ε (x) is a closed subset (which

By (a), B ε (x) is a closed subset (which Solutions to Homework #3. 1. Given a metric space (X, d), a point x X and ε > 0, define B ε (x) = {y X : d(y, x) ε}, called the closed ball of radius ε centered at x. (a) Prove that B ε (x) is always a

More information

Solutions: Problem Set 4 Math 201B, Winter 2007

Solutions: Problem Set 4 Math 201B, Winter 2007 Solutions: Problem Set 4 Math 2B, Winter 27 Problem. (a Define f : by { x /2 if < x

More information

Université de Metz. Master 2 Recherche de Mathématiques 2ème semestre. par Ralph Chill Laboratoire de Mathématiques et Applications de Metz

Université de Metz. Master 2 Recherche de Mathématiques 2ème semestre. par Ralph Chill Laboratoire de Mathématiques et Applications de Metz Université de Metz Master 2 Recherche de Mathématiques 2ème semestre Systèmes gradients par Ralph Chill Laboratoire de Mathématiques et Applications de Metz Année 26/7 1 Contents Chapter 1. Introduction

More information

Sobolev Spaces. Chapter 10

Sobolev Spaces. Chapter 10 Chapter 1 Sobolev Spaces We now define spaces H 1,p (R n ), known as Sobolev spaces. For u to belong to H 1,p (R n ), we require that u L p (R n ) and that u have weak derivatives of first order in L p

More information

Elliptic PDEs of 2nd Order, Gilbarg and Trudinger

Elliptic PDEs of 2nd Order, Gilbarg and Trudinger Elliptic PDEs of 2nd Order, Gilbarg and Trudinger Chapter 2 Laplace Equation Yung-Hsiang Huang 207.07.07. Mimic the proof for Theorem 3.. 2. Proof. I think we should assume u C 2 (Ω Γ). Let W be an open

More information

Scientific Computing WS 2018/2019. Lecture 15. Jürgen Fuhrmann Lecture 15 Slide 1

Scientific Computing WS 2018/2019. Lecture 15. Jürgen Fuhrmann Lecture 15 Slide 1 Scientific Computing WS 2018/2019 Lecture 15 Jürgen Fuhrmann juergen.fuhrmann@wias-berlin.de Lecture 15 Slide 1 Lecture 15 Slide 2 Problems with strong formulation Writing the PDE with divergence and gradient

More information

TD 1: Hilbert Spaces and Applications

TD 1: Hilbert Spaces and Applications Université Paris-Dauphine Functional Analysis and PDEs Master MMD-MA 2017/2018 Generalities TD 1: Hilbert Spaces and Applications Exercise 1 (Generalized Parallelogram law). Let (H,, ) be a Hilbert space.

More information

Chapter 2 Finite Element Spaces for Linear Saddle Point Problems

Chapter 2 Finite Element Spaces for Linear Saddle Point Problems Chapter 2 Finite Element Spaces for Linear Saddle Point Problems Remark 2.1. Motivation. This chapter deals with the first difficulty inherent to the incompressible Navier Stokes equations, see Remark

More information

Power Series. Part 2 Differentiation & Integration; Multiplication of Power Series. J. Gonzalez-Zugasti, University of Massachusetts - Lowell

Power Series. Part 2 Differentiation & Integration; Multiplication of Power Series. J. Gonzalez-Zugasti, University of Massachusetts - Lowell Power Series Part 2 Differentiation & Integration; Multiplication of Power Series 1 Theorem 1 If a n x n converges absolutely for x < R, then a n f x n converges absolutely for any continuous function

More information

Finite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product

Finite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product Chapter 4 Hilbert Spaces 4.1 Inner Product Spaces Inner Product Space. A complex vector space E is called an inner product space (or a pre-hilbert space, or a unitary space) if there is a mapping (, )

More information

Lecture Notes on PDEs

Lecture Notes on PDEs Lecture Notes on PDEs Alberto Bressan February 26, 2012 1 Elliptic equations Let IR n be a bounded open set Given measurable functions a ij, b i, c : IR, consider the linear, second order differential

More information

MATH COURSE NOTES - CLASS MEETING # Introduction to PDEs, Fall 2011 Professor: Jared Speck

MATH COURSE NOTES - CLASS MEETING # Introduction to PDEs, Fall 2011 Professor: Jared Speck MATH 8.52 COURSE NOTES - CLASS MEETING # 6 8.52 Introduction to PDEs, Fall 20 Professor: Jared Speck Class Meeting # 6: Laplace s and Poisson s Equations We will now study the Laplace and Poisson equations

More information

MATH COURSE NOTES - CLASS MEETING # Introduction to PDEs, Spring 2018 Professor: Jared Speck

MATH COURSE NOTES - CLASS MEETING # Introduction to PDEs, Spring 2018 Professor: Jared Speck MATH 8.52 COURSE NOTES - CLASS MEETING # 6 8.52 Introduction to PDEs, Spring 208 Professor: Jared Speck Class Meeting # 6: Laplace s and Poisson s Equations We will now study the Laplace and Poisson equations

More information

Sobolev spaces. May 18

Sobolev spaces. May 18 Sobolev spaces May 18 2015 1 Weak derivatives The purpose of these notes is to give a very basic introduction to Sobolev spaces. More extensive treatments can e.g. be found in the classical references

More information

Sobolev Spaces 27 PART II. Review of Sobolev Spaces

Sobolev Spaces 27 PART II. Review of Sobolev Spaces Sobolev Spaces 27 PART II Review of Sobolev Spaces Sobolev Spaces 28 SOBOLEV SPACES WEAK DERIVATIVES I Given R d, define a multi index α as an ordered collection of integers α = (α 1,...,α d ), such that

More information

Numerical Functional Analysis

Numerical Functional Analysis Numerical Functional Analysis T. Betcke December 17, 28 These notes are in development and only for internal use at the University of Mancheser. For questions, comments or typos please e-mail timo.betcke@manchester.ac.uk.

More information

1 Background and Review Material

1 Background and Review Material 1 Background and Review Material 1.1 Vector Spaces Let V be a nonempty set and consider the following two operations on elements of V : (x,y) x + y maps V V V (addition) (1.1) (α, x) αx maps F V V (scalar

More information

Some Notes on Elliptic Regularity

Some Notes on Elliptic Regularity Some Notes on Elliptic Regularity Here we consider first the existence of weak solutions to elliptic problems of the form: { Lu = f, u = 0, (1) and then we consider the regularity of such solutions. The

More information

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms (February 24, 2017) 08a. Operators on Hilbert spaces Paul Garrett garrett@math.umn.edu http://www.math.umn.edu/ garrett/ [This document is http://www.math.umn.edu/ garrett/m/real/notes 2016-17/08a-ops

More information

Diffusion on the half-line. The Dirichlet problem

Diffusion on the half-line. The Dirichlet problem Diffusion on the half-line The Dirichlet problem Consider the initial boundary value problem (IBVP) on the half line (, ): v t kv xx = v(x, ) = φ(x) v(, t) =. The solution will be obtained by the reflection

More information

Contents: 1. Minimization. 2. The theorem of Lions-Stampacchia for variational inequalities. 3. Γ -Convergence. 4. Duality mapping.

Contents: 1. Minimization. 2. The theorem of Lions-Stampacchia for variational inequalities. 3. Γ -Convergence. 4. Duality mapping. Minimization Contents: 1. Minimization. 2. The theorem of Lions-Stampacchia for variational inequalities. 3. Γ -Convergence. 4. Duality mapping. 1 Minimization A Topological Result. Let S be a topological

More information

Regularity Theory a Fourth Order PDE with Delta Right Hand Side

Regularity Theory a Fourth Order PDE with Delta Right Hand Side Regularity Theory a Fourth Order PDE with Delta Right Hand Side Graham Hobbs Applied PDEs Seminar, 29th October 2013 Contents Problem and Weak Formulation Example - The Biharmonic Problem Regularity Theory

More information

[2] (a) Develop and describe the piecewise linear Galerkin finite element approximation of,

[2] (a) Develop and describe the piecewise linear Galerkin finite element approximation of, 269 C, Vese Practice problems [1] Write the differential equation u + u = f(x, y), (x, y) Ω u = 1 (x, y) Ω 1 n + u = x (x, y) Ω 2, Ω = {(x, y) x 2 + y 2 < 1}, Ω 1 = {(x, y) x 2 + y 2 = 1, x 0}, Ω 2 = {(x,

More information

Chapter 12. Partial di erential equations Di erential operators in R n. The gradient and Jacobian. Divergence and rotation

Chapter 12. Partial di erential equations Di erential operators in R n. The gradient and Jacobian. Divergence and rotation Chapter 12 Partial di erential equations 12.1 Di erential operators in R n The gradient and Jacobian We recall the definition of the gradient of a scalar function f : R n! R, as @f grad f = rf =,..., @f

More information

MA3051: Mathematical Analysis II

MA3051: Mathematical Analysis II MA3051: Mathematical Analysis II Course Notes Stephen Wills 2014/15 Contents 0 Assumed Knowledge 2 Sets and maps................................ 2 Sequences and series............................. 2 Metric

More information

Functional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability...

Functional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability... Functional Analysis Franck Sueur 2018-2019 Contents 1 Metric spaces 1 1.1 Definitions........................................ 1 1.2 Completeness...................................... 3 1.3 Compactness......................................

More information

Applied/Numerical Analysis Qualifying Exam

Applied/Numerical Analysis Qualifying Exam Applied/Numerical Analysis Qualifying Exam August 9, 212 Cover Sheet Applied Analysis Part Policy on misprints: The qualifying exam committee tries to proofread exams as carefully as possible. Nevertheless,

More information

Calculus of Variations. Final Examination

Calculus of Variations. Final Examination Université Paris-Saclay M AMS and Optimization January 18th, 018 Calculus of Variations Final Examination Duration : 3h ; all kind of paper documents (notes, books...) are authorized. The total score of

More information

MATH 425, FINAL EXAM SOLUTIONS

MATH 425, FINAL EXAM SOLUTIONS MATH 425, FINAL EXAM SOLUTIONS Each exercise is worth 50 points. Exercise. a The operator L is defined on smooth functions of (x, y by: Is the operator L linear? Prove your answer. L (u := arctan(xy u

More information

Functional Analysis Review

Functional Analysis Review Outline 9.520: Statistical Learning Theory and Applications February 8, 2010 Outline 1 2 3 4 Vector Space Outline A vector space is a set V with binary operations +: V V V and : R V V such that for all

More information

Functional Analysis Exercise Class

Functional Analysis Exercise Class Functional Analysis Exercise Class Week 9 November 13 November Deadline to hand in the homeworks: your exercise class on week 16 November 20 November Exercises (1) Show that if T B(X, Y ) and S B(Y, Z)

More information

CSE386C METHODS OF APPLIED MATHEMATICS Fall 2014, Final Exam, 9:00-noon, Tue, Dec 16, ACES 6.304

CSE386C METHODS OF APPLIED MATHEMATICS Fall 2014, Final Exam, 9:00-noon, Tue, Dec 16, ACES 6.304 CSE386C METHODS OF APPLIED MATHEMATICS Fall 2014, Final Exam, 9:00-noon, Tue, Dec 16, ACES 6.304 1. Let A be a closed operator defined on a dense subspace D(A) of a Hilbert space U. (a) Define the adjoint

More information

Applied/Numerical Analysis Qualifying Exam

Applied/Numerical Analysis Qualifying Exam Applied/Numerical Analysis Qualifying Exam August 13, 2011 Cover Sheet Applied Analysis Part Policy on misprints: The qualifying exam committee tries to proofread exams as carefully as possible. Nevertheless,

More information

CHAPTER VIII HILBERT SPACES

CHAPTER VIII HILBERT SPACES CHAPTER VIII HILBERT SPACES DEFINITION Let X and Y be two complex vector spaces. A map T : X Y is called a conjugate-linear transformation if it is a reallinear transformation from X into Y, and if T (λx)

More information

Notions such as convergent sequence and Cauchy sequence make sense for any metric space. Convergent Sequences are Cauchy

Notions such as convergent sequence and Cauchy sequence make sense for any metric space. Convergent Sequences are Cauchy Banach Spaces These notes provide an introduction to Banach spaces, which are complete normed vector spaces. For the purposes of these notes, all vector spaces are assumed to be over the real numbers.

More information

Friedrich symmetric systems

Friedrich symmetric systems viii CHAPTER 8 Friedrich symmetric systems In this chapter, we describe a theory due to Friedrich [13] for positive symmetric systems, which gives the existence and uniqueness of weak solutions of boundary

More information

TD M1 EDP 2018 no 2 Elliptic equations: regularity, maximum principle

TD M1 EDP 2018 no 2 Elliptic equations: regularity, maximum principle TD M EDP 08 no Elliptic equations: regularity, maximum principle Estimates in the sup-norm I Let be an open bounded subset of R d of class C. Let A = (a ij ) be a symmetric matrix of functions of class

More information

Chapter 5 A priori error estimates for nonconforming finite element approximations 5.1 Strang s first lemma

Chapter 5 A priori error estimates for nonconforming finite element approximations 5.1 Strang s first lemma Chapter 5 A priori error estimates for nonconforming finite element approximations 51 Strang s first lemma We consider the variational equation (51 a(u, v = l(v, v V H 1 (Ω, and assume that the conditions

More information

Applied Analysis (APPM 5440): Final exam 1:30pm 4:00pm, Dec. 14, Closed books.

Applied Analysis (APPM 5440): Final exam 1:30pm 4:00pm, Dec. 14, Closed books. Applied Analysis APPM 44: Final exam 1:3pm 4:pm, Dec. 14, 29. Closed books. Problem 1: 2p Set I = [, 1]. Prove that there is a continuous function u on I such that 1 ux 1 x sin ut 2 dt = cosx, x I. Define

More information

Math The Laplacian. 1 Green s Identities, Fundamental Solution

Math The Laplacian. 1 Green s Identities, Fundamental Solution Math. 209 The Laplacian Green s Identities, Fundamental Solution Let be a bounded open set in R n, n 2, with smooth boundary. The fact that the boundary is smooth means that at each point x the external

More information

Functions of Several Variables

Functions of Several Variables Jim Lambers MAT 419/519 Summer Session 2011-12 Lecture 2 Notes These notes correspond to Section 1.2 in the text. Functions of Several Variables We now generalize the results from the previous section,

More information

Traces, extensions and co-normal derivatives for elliptic systems on Lipschitz domains

Traces, extensions and co-normal derivatives for elliptic systems on Lipschitz domains Traces, extensions and co-normal derivatives for elliptic systems on Lipschitz domains Sergey E. Mikhailov Brunel University West London, Department of Mathematics, Uxbridge, UB8 3PH, UK J. Math. Analysis

More information

Tools from Lebesgue integration

Tools from Lebesgue integration Tools from Lebesgue integration E.P. van den Ban Fall 2005 Introduction In these notes we describe some of the basic tools from the theory of Lebesgue integration. Definitions and results will be given

More information

************************************* Partial Differential Equations II (Math 849, Spring 2019) Baisheng Yan

************************************* Partial Differential Equations II (Math 849, Spring 2019) Baisheng Yan ************************************* Partial Differential Equations II (Math 849, Spring 2019) by Baisheng Yan Department of Mathematics Michigan State University yan@math.msu.edu Contents Chapter 1.

More information

Real Analysis Notes. Thomas Goller

Real Analysis Notes. Thomas Goller Real Analysis Notes Thomas Goller September 4, 2011 Contents 1 Abstract Measure Spaces 2 1.1 Basic Definitions........................... 2 1.2 Measurable Functions........................ 2 1.3 Integration..............................

More information

SOLUTIONS TO SOME PROBLEMS

SOLUTIONS TO SOME PROBLEMS 23 FUNCTIONAL ANALYSIS Spring 23 SOLUTIONS TO SOME PROBLEMS Warning:These solutions may contain errors!! PREPARED BY SULEYMAN ULUSOY PROBLEM 1. Prove that a necessary and sufficient condition that the

More information

THE L 2 -HODGE THEORY AND REPRESENTATION ON R n

THE L 2 -HODGE THEORY AND REPRESENTATION ON R n THE L 2 -HODGE THEORY AND REPRESENTATION ON R n BAISHENG YAN Abstract. We present an elementary L 2 -Hodge theory on whole R n based on the minimization principle of the calculus of variations and some

More information

Maths 212: Homework Solutions

Maths 212: Homework Solutions Maths 212: Homework Solutions 1. The definition of A ensures that x π for all x A, so π is an upper bound of A. To show it is the least upper bound, suppose x < π and consider two cases. If x < 1, then

More information

The Dirichlet-to-Neumann operator

The Dirichlet-to-Neumann operator Lecture 8 The Dirichlet-to-Neumann operator The Dirichlet-to-Neumann operator plays an important role in the theory of inverse problems. In fact, from measurements of electrical currents at the surface

More information

arxiv: v1 [math.ap] 6 Dec 2011

arxiv: v1 [math.ap] 6 Dec 2011 LECTURE NOTES: THE GALERKIN METHOD arxiv:1112.1176v1 [math.ap] 6 Dec 211 Raghavendra Venkatraman 1 In these notes, we consider the analysis of Galerkin Method and its application to computing approximate

More information

Rule ST1 (Symmetry). α β = β α for 1-forms α and β. Like the exterior product, the symmetric tensor product is also linear in each slot :

Rule ST1 (Symmetry). α β = β α for 1-forms α and β. Like the exterior product, the symmetric tensor product is also linear in each slot : 2. Metrics as Symmetric Tensors So far we have studied exterior products of 1-forms, which obey the rule called skew symmetry: α β = β α. There is another operation for forming something called the symmetric

More information

Sobolev Spaces. Chapter Hölder spaces

Sobolev Spaces. Chapter Hölder spaces Chapter 2 Sobolev Spaces Sobolev spaces turn out often to be the proper setting in which to apply ideas of functional analysis to get information concerning partial differential equations. Here, we collect

More information

MA677 Assignment #3 Morgan Schreffler Due 09/19/12 Exercise 1 Using Hölder s inequality, prove Minkowski s inequality for f, g L p (R d ), p 1:

MA677 Assignment #3 Morgan Schreffler Due 09/19/12 Exercise 1 Using Hölder s inequality, prove Minkowski s inequality for f, g L p (R d ), p 1: Exercise 1 Using Hölder s inequality, prove Minkowski s inequality for f, g L p (R d ), p 1: f + g p f p + g p. Proof. If f, g L p (R d ), then since f(x) + g(x) max {f(x), g(x)}, we have f(x) + g(x) p

More information

Solving PDE s with FEniCS. L. Ridgway Scott. Laplace and Poisson

Solving PDE s with FEniCS. L. Ridgway Scott. Laplace and Poisson Solving PDE s with FEniCS Laplace and Poisson L. Ridgway Scott The Institute for Biophysical Dynamics, The Computation Institute, and the Departments of Computer Science and Mathematics, The University

More information

Integral Representation Formula, Boundary Integral Operators and Calderón projection

Integral Representation Formula, Boundary Integral Operators and Calderón projection Integral Representation Formula, Boundary Integral Operators and Calderón projection Seminar BEM on Wave Scattering Franziska Weber ETH Zürich October 22, 2010 Outline Integral Representation Formula Newton

More information

2 Two-Point Boundary Value Problems

2 Two-Point Boundary Value Problems 2 Two-Point Boundary Value Problems Another fundamental equation, in addition to the heat eq. and the wave eq., is Poisson s equation: n j=1 2 u x 2 j The unknown is the function u = u(x 1, x 2,..., x

More information

Differential Equations Preliminary Examination

Differential Equations Preliminary Examination Differential Equations Preliminary Examination Department of Mathematics University of Utah Salt Lake City, Utah 84112 August 2007 Instructions This examination consists of two parts, called Part A and

More information

Lecture Notes of the Autumn School Modelling and Optimization with Partial Differential Equations Hamburg, September 26-30, 2005

Lecture Notes of the Autumn School Modelling and Optimization with Partial Differential Equations Hamburg, September 26-30, 2005 Lecture Notes of the Autumn School Modelling and Optimization with Partial Differential Equations Hamburg, September 26-30, 2005 Michael Hinze, René Pinnau, Michael Ulbrich, and Stefan Ulbrich supported

More information

An introduction to the mathematical theory of finite elements

An introduction to the mathematical theory of finite elements Master in Seismic Engineering E.T.S.I. Industriales (U.P.M.) Discretization Methods in Engineering An introduction to the mathematical theory of finite elements Ignacio Romero ignacio.romero@upm.es October

More information

Chapter 1: The Finite Element Method

Chapter 1: The Finite Element Method Chapter 1: The Finite Element Method Michael Hanke Read: Strang, p 428 436 A Model Problem Mathematical Models, Analysis and Simulation, Part Applications: u = fx), < x < 1 u) = u1) = D) axial deformation

More information

Equations paraboliques: comportement qualitatif

Equations paraboliques: comportement qualitatif Université de Metz Master 2 Recherche de Mathématiques 2ème semestre Equations paraboliques: comportement qualitatif par Ralph Chill Laboratoire de Mathématiques et Applications de Metz Année 25/6 1 Contents

More information

Partial Differential Equations

Partial Differential Equations Part II Partial Differential Equations Year 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2015 Paper 4, Section II 29E Partial Differential Equations 72 (a) Show that the Cauchy problem for u(x,

More information

Lax Solution Part 4. October 27, 2016

Lax Solution Part 4.   October 27, 2016 Lax Solution Part 4 www.mathtuition88.com October 27, 2016 Textbook: Functional Analysis by Peter D. Lax Exercises: Ch 16: Q2 4. Ch 21: Q1, 2, 9, 10. Ch 28: 1, 5, 9, 10. 1 Chapter 16 Exercise 2 Let h =

More information

ELLIPTIC PARTIAL DIFFERENTIAL EQUATIONS EXERCISES I (HARMONIC FUNCTIONS)

ELLIPTIC PARTIAL DIFFERENTIAL EQUATIONS EXERCISES I (HARMONIC FUNCTIONS) ELLIPTIC PARTIAL DIFFERENTIAL EQUATIONS EXERCISES I (HARMONIC FUNCTIONS) MATANIA BEN-ARTZI. BOOKS [CH] R. Courant and D. Hilbert, Methods of Mathematical Physics, Vol. Interscience Publ. 962. II, [E] L.

More information

1 Constrained Optimization

1 Constrained Optimization 1 Constrained Optimization Let B be an M N matrix, a linear operator from the space IR N to IR M with adjoint B T. For (column vectors) x IR N and y IR M we have x B T y = Bx y. This vanishes for all y

More information

FINITE ELEMENT METHODS

FINITE ELEMENT METHODS FINITE ELEMENT METHODS Lecture notes arxiv:1709.08618v1 [math.na] 25 Sep 2017 Christian Clason September 25, 2017 christian.clason@uni-due.de https://udue.de/clason CONTENTS I BACKGROUND 1 overview of

More information

Lecture Notes: African Institute of Mathematics Senegal, January Topic Title: A short introduction to numerical methods for elliptic PDEs

Lecture Notes: African Institute of Mathematics Senegal, January Topic Title: A short introduction to numerical methods for elliptic PDEs Lecture Notes: African Institute of Mathematics Senegal, January 26 opic itle: A short introduction to numerical methods for elliptic PDEs Authors and Lecturers: Gerard Awanou (University of Illinois-Chicago)

More information

Class Meeting # 1: Introduction to PDEs

Class Meeting # 1: Introduction to PDEs MATH 18.152 COURSE NOTES - CLASS MEETING # 1 18.152 Introduction to PDEs, Spring 2017 Professor: Jared Speck Class Meeting # 1: Introduction to PDEs 1. What is a PDE? We will be studying functions u =

More information