Sharp Korn inequalities in thin domains: The rst and a half Korn inequality

Size: px
Start display at page:

Download "Sharp Korn inequalities in thin domains: The rst and a half Korn inequality"

Transcription

1 Sarp Korn inequalities in tin domains: Te rst and a alf Korn inequality Davit Harutyunyan (University of Uta) joint wit Yury Grabovsky (Temple University) SIAM, Analysis of Partial Dierential Equations, Decamber 7-10, Scottsdale, Arizona

2 Korn's Inequalities Assume Ω R n is open, bounded, connected and Lipscitz and u H 1 (Ω, R n ), were u = (u 1, u 2,..., u n ) and u = ( u i ) n x. j i,j=1 Set e(u) = 1 2 ( u + ( u)t ), e ij (u) = u i + u j. x j x i Denote skew(r n ) = {L = Ax + b : A M n n, A T = A, b R n }. Assume V is a closed subspace of H 1 (Ω, R n ) suc tat V skew(r n ) = {0}.

3 Korn's Inequalities Korn's First and Second Inequalities 1. Tere exists a constant K 1 depending only on Ω suc tat ( K 1 (Ω) u 2 u 2 + e(u) ), 2 for any u H 1 (Ω, R n ) Ω Ω Ω 2. Tere exists a constant K 2 depending only on Ω and V suc tat K 2 (Ω, V ) u 2 e(u) 2, for any u V Ω Ω. 3. Tere exists a constant K > 0 depending only on Ω suc tat for any u H 1 (Ω, R n ), tere exists a skew-symmetric matrix A u suc tat K(Ω) u A u 2 e(u) 2 Ω Ω

4 Inequalities of Our Interest We are interested in sarp Korn inequalities. Question: How do K 1 (Ω) and K 2 (V, Ω) depend on Ω and V, wen Ω is tin? Ω is a tin domain (strips, rods, sells,...) wit tickness, ten K 1 (Ω) α and K 2 (V, Ω) β as 0. Find α and β. If for instance β is known and K 2 (V, Ω) C(V, Ω) β, wen is suciently small, ten wat is C(V, Ω)? Goal: Find te optimal constants in Korn's inequalities.

5 Examples Example 1 (Zero boundary conditions). If V = {u H 1 (Ω, R n ) : u(x) = 0 on Ω}, ten K 2 (V, Ω) = 1 2. Example 2 (Tin rectangle). If Ω = [0, ] [0, l], V = {u H 1 (Ω, R 2 ) : u(x, 0) = u(x, l) = 0}, ten K 2 (V, Ω) C 2.

6 Motivation Wy optimal constants? Te problem we were interested in: Buckling of cylindrical sells under axial compression, (2011). Critical buckling load, deformation modes? Koiter's formula (1945). λ() = C, were is te tickness of te sell, and C depends on te material. Te buckling modes are given by "Koiter's circle". It was known, tat te buckling load is igly sensitive to imperfections (sape, load). We aim to derive Koiter's formula and understand te sensitivity to imperfections applying te teory of buckling of slender structures, Grabovsky, Truskinovsky (2007).

7 Motivation If C = {(r, θ, z) : r [R, R + ], θ [0, 2π], z [0, L]}, and u = u r ē r + u θ ē θ + u z ē z, in cylindrical coordinates, te we impose te B.C.: Fixed bottom boundary conditions: u r (r, θ, 0) = u θ (r, θ, 0) = u z (r, θ, 0) = u r (r, θ, L) = u θ (r, θ, L) = 0, V 1, Breating cylinder u θ (r, θ, 0) = u z (r, θ, 0) = u θ (r, θ, L) = 0, u z (r, θ, L) = c, V 2.

8 Motivation, Problem Te teory of Grabovsky and Truskinovsky implies λ() ck(c ), were K(C ) is te optimal Korn's constant in te second Korn inequality for V 1 or V 2. Weter one as K(V i, C )? Answer: NO! K(V i, C ). Teorem (Grabovsky, H., 2012) If K(C ) lim 0 λ cl () = 0, ten te constitutively linearized quotient captures bot, te critical load and te buckling modes.

9 Korn's inequalities for perfect cylindrical sells Teorem (Grabovsky, H., 2012) Tere exist absolute constants C i > 0, i = 1, 2 suc tat for any u V i, tere olds u 2 C i C e(u) 2. C Tese estimates are sarp, in te sense tat te power of is optimal. If u = u r ē r + u θ ē θ + u z ē z, ten u = u r,r u θ,r u z,r u r,θ u θ r u θ,θ +u r u r z,θ r u r,z u θ,z u z,z.

10 Korn's inequalities for perfect cylindrical sells Ansatz. We assume R = 1, ten ( φ r (r, θ, z) = W,ηη φ θ (r, θ, z) = r 4 ( W,η θ 4, z θ 4, z ( φ z(r, θ, z) = (r 1)W,ηηz ) ) + r 1 θ 4, z ( ) θ 4 W,ηηη 4, z, ) ( θ W,z 4, z were te function W (η, z) is a smoot compactly supported function on ( 1, 1) (0, L), wile te function φ (θ, z) is extended as a 2π-periodic function in θ R. ),

11 Remarks on te Korn inequality, strategy If u = u r ē r + u θ ē θ + u z ē z, ten u = u r,r u θ,r u z,r u r,θ u θ r u θ,θ +u r u r z,θ r u r,z u θ,z u z,z. Prove te inequality block by block, wic means xing r, θ and z and proving 2D inequalities. For r, θ, z = const, we ave te blocks u θ,θ+u r r u θ,z, respectively. u z,θ r u z,z u r,r u r,z, u z,r u z,z u r,θ u θ r u θ,θ +u r r u r,r u θ,r,

12 Available Tools We needed Korn's inequalities wit constants decaying like or slower! For instance te cross section θ = const gives a Korn's second inequality on a tin rectangle: u r,r u r,z. u z,r u z,z Wat is available? θ = const gives a tin rectangle, Korn's second inequality on rectangles, K 2 Ryzak 2001?: not applicable. z = const gives a tin annulus, again optimal constant scales like 2, Dafermos 1968, for normalization conditions: not applicable. Uniform Korn-Poincaré inequality in tin domains, Lewicka, Müller 2011, tangential boundary conditions: not applicable. New inequalities are needed.

13 A Korn type inequality Standard approac: It is sucient to prove a second Korn inequality subject to Diriclet type boundary conditions for armonic displacements. Teorem (Grabovsky, H., 2012) Suppose w(x, y) is armonic in [0, ] [0, L], and satises w(x, 0) = w(x, L). Ten Te equality is attained at w y w w x + w x 2. w(x) = cos ( ( π x )) ( πy ) sin, L 2 L

14 Te rst and a alf Korn inequality for rectangles Teorem (Grabobsky, H., 2012) Suppose tat te vector eld U = (u, v) H 1 (Ω, R 2 ), were Ω = [0, ] [0, L], satises u(x, 0) = u(x, L). Ten for any (0, 1) and any L > 0 tere olds: ( ) u e(u) U e(u) 2. Tere are no boundary conditions imposed on v(x, y). Tis implies bot te rst (via Scwartz inequality) and te second (via Friedrics inequality) Korn inequalities. Te scaling of te constant is as needed.

15 Te rst and a alf Korn inequality for cylindrical sells Teorem (Grabobsky, H., 2012) Suppose U V 1 or U V 2. Ten tere exists a universal constant C > 0 suc, tat for any (0, 1) and any L > 0 tere olds: ( ) U 2 ur e(u) C + e(u) 2. Tis implies te second Korn inequality, but wit 2. Combine wit u r 3 C U 2 e(u).

16 Extensions An extension to R n for tin domains wit nonconstant tickness. Assume te operator n L(u) = i,j=1 a ij 2 u x i x j wit constant coecients satises n a ij x i x j λ x 2 for all x R n, (1) i,j=1 were λ > 0, and, n a ij Λ for all 1 j n. (2) i=1

17 Extensions For x = (x 1, x 2,..., x n ), let x = (x 2,..., x n ). Teorem (H., 2014) Let ω R n 1 be a bounded and simply-connected Lipscitz domain, let x 1 = ϕ(x ): ω R be a positive Lipscitz function wit H = sup x ω ϕ(x ) and = inf x ω ϕ(x ) > 0. Denote Ω = {x R n : x ω, 0 < x 1 < ϕ(x )} and assume tat te operator L(u) = n i,j=1 a 2 u ij x i x wit constant coecients satises conditions (1) j and (2). Ten tere exists a constant C depending on n, Λ, λ, L = Lip(ϕ) and te ratio m = H/ suc tat any u C 3 ( Ω) solution of L(u) = 0 satisfying te boundary conditions u(x) = 0 on te portion Γ = {x Ω : x ω} of te boundary of Ω fullls te inequality ( ) u u 2 ux1 C + u x1 2. C = C(n, λ, Λ, L, m).

18 Extensions Teorem (H., 2014) Let l > 0, let ϕ 1 C 1 [0, l] and let ϕ 2 and ϕ 1 be Lipscitz functions dened on [0, l]. Assume furtermore tat 0 < = min y [0,l] (ϕ 2 (y) ϕ 1 (y)) and H = min y [0,l] (ϕ 2 (y) ϕ 1 (y)). Denote Ω = {(x, y) R 2 : y (0, l), ϕ 1 (y) < x < ϕ 2 (y)}. Ten tere exists a constant C depending on m = H/, ρ 1 = ϕ 1 L (Ω), ρ 2 = ϕ 2 L (Ω) and ρ 1 = ϕ 1 L (Ω) suc tat if te rst component of te displacement U = (u, v) W 1,2 (Ω) satises te boundary conditions u(x) = 0 on te boundary portion Γ = {(x, y) Ω : y = 0 or y = l} in te trace sense, ten te strong second Korn inequality olds: ( ) u e(u) U 2 + e(u) 2. Te estimate is sarp. C = C(m, ρ 1, ρ 2, ρ 1).

19 Extensions Teorem (H., 2014) Let L > 0, ϕ 1, ϕ 2, Ω,, H, m, ρ 1, ρ 2 and ρ 1 be as in te previous teorem. Ten tere exists a constant C depending on m, ρ 1, ρ 2 and ρ 1 suc tat if te rst component u of te displacement U = (u, v) W 1,2 (Ω) is L-periodic, ten te second Korn inequality olds: ( ) u e(u) U 2 + e(u) 2. C = C(m, ρ 1, ρ 2, ρ 1). L periodicity is te periodicity of bot te function and te gradient.

20 Recent progress Consider a sell in te (r, θ, z) variables (θ and z are te principal directions): [ C = 2, ] [0, s] [0, L], 2 wit κ z = 0. (tis yields a zero Gaussian curvature). If U = (u r, u θ, u z ), ten 1 1 u r,r A θ u r,θ κ θ u θ A z u r,z 1 U = u θ,r A θ u θ,θ + A θ,z 1 A θ A z u z + κ θ u r A z u θ,z. 1 u z,z A θ u z,θ A θ,z 1 A θ A z u θ A z u z,z Assume K = sup κ θ <, K 1 = sup κ θ,θ <, 0 < a θ A θ b θ, 0 < a z A z b z, A z, A θ A. were a θ, a z, b θ, b z, A are constants. Tis includes cut cones and straigt cylinders wit arbitrary cross sections.

21 Recent progress Te spaces V 1 and V 2 are te same as before. C will be a constant depending only on te constants K, k, K 1, a z, a θ, b z, b θ and A. Teorem (Grabovsky, H., 2015) For any (0, 1) and any U V i, tere olds: ( ) U 2 ur e(u) C + e(u) 2 + u r 2.

22 Recent progress Teorem (Grabovsky, H., 2015) If κ θ > 0, ten for any (0, 1) and any U V i, tere olds: U 2 If κ θ = 0 in a box [θ 1, θ 2 ] [z 1, z 2 ], ten C e(u) 2. U 2 C 2 e(u) 2.

23 Work in progress Assume Ω is a sell of revolution given by C = [ r(z) 2, r(z) + ] [0, 2π] [0, L]. 2 Ten (conjecture) If κ z < 0, ten for any (0, 1) and any U V i, tere olds: If κ z > 0, ten U 2 C 4/3 e(u) 2. U 2 C e(u) 2. Teorem (Grabovsky, H., 2015) For any (0, 1) and any U V i, tere olds: ( ) U e(u) U 2 C + e(u) 2 + U 2.

Poisson Equation in Sobolev Spaces

Poisson Equation in Sobolev Spaces Poisson Equation in Sobolev Spaces OcMountain Dayligt Time. 6, 011 Today we discuss te Poisson equation in Sobolev spaces. It s existence, uniqueness, and regularity. Weak Solution. u = f in, u = g on

More information

(a) At what number x = a does f have a removable discontinuity? What value f(a) should be assigned to f at x = a in order to make f continuous at a?

(a) At what number x = a does f have a removable discontinuity? What value f(a) should be assigned to f at x = a in order to make f continuous at a? Solutions to Test 1 Fall 016 1pt 1. Te grap of a function f(x) is sown at rigt below. Part I. State te value of eac limit. If a limit is infinite, state weter it is or. If a limit does not exist (but is

More information

Test 2 Review. 1. Find the determinant of the matrix below using (a) cofactor expansion and (b) row reduction. A = 3 2 =

Test 2 Review. 1. Find the determinant of the matrix below using (a) cofactor expansion and (b) row reduction. A = 3 2 = Test Review Find te determinant of te matrix below using (a cofactor expansion and (b row reduction Answer: (a det + = (b Observe R R R R R R R R R Ten det B = (((det Hence det Use Cramer s rule to solve:

More information

4.2 - Richardson Extrapolation

4.2 - Richardson Extrapolation . - Ricardson Extrapolation. Small-O Notation: Recall tat te big-o notation used to define te rate of convergence in Section.: Definition Let x n n converge to a number x. Suppose tat n n is a sequence

More information

THE IDEA OF DIFFERENTIABILITY FOR FUNCTIONS OF SEVERAL VARIABLES Math 225

THE IDEA OF DIFFERENTIABILITY FOR FUNCTIONS OF SEVERAL VARIABLES Math 225 THE IDEA OF DIFFERENTIABILITY FOR FUNCTIONS OF SEVERAL VARIABLES Mat 225 As we ave seen, te definition of derivative for a Mat 111 function g : R R and for acurveγ : R E n are te same, except for interpretation:

More information

We name Functions f (x) or g(x) etc.

We name Functions f (x) or g(x) etc. Section 2 1B: Function Notation Bot of te equations y 2x +1 and y 3x 2 are functions. It is common to ave two or more functions in terms of x in te same problem. If I ask you wat is te value for y if x

More information

Math Spring 2013 Solutions to Assignment # 3 Completion Date: Wednesday May 15, (1/z) 2 (1/z 1) 2 = lim

Math Spring 2013 Solutions to Assignment # 3 Completion Date: Wednesday May 15, (1/z) 2 (1/z 1) 2 = lim Mat 311 - Spring 013 Solutions to Assignment # 3 Completion Date: Wednesday May 15, 013 Question 1. [p 56, #10 (a)] 4z Use te teorem of Sec. 17 to sow tat z (z 1) = 4. We ave z 4z (z 1) = z 0 4 (1/z) (1/z

More information

Section 15.6 Directional Derivatives and the Gradient Vector

Section 15.6 Directional Derivatives and the Gradient Vector Section 15.6 Directional Derivatives and te Gradient Vector Finding rates of cange in different directions Recall tat wen we first started considering derivatives of functions of more tan one variable,

More information

232 Calculus and Structures

232 Calculus and Structures 3 Calculus and Structures CHAPTER 17 JUSTIFICATION OF THE AREA AND SLOPE METHODS FOR EVALUATING BEAMS Calculus and Structures 33 Copyrigt Capter 17 JUSTIFICATION OF THE AREA AND SLOPE METHODS 17.1 THE

More information

Minimal surfaces of revolution

Minimal surfaces of revolution 5 April 013 Minimal surfaces of revolution Maggie Miller 1 Introduction In tis paper, we will prove tat all non-planar minimal surfaces of revolution can be generated by functions of te form f = 1 C cos(cx),

More information

Function Composition and Chain Rules

Function Composition and Chain Rules Function Composition and s James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 8, 2017 Outline 1 Function Composition and Continuity 2 Function

More information

(4.2) -Richardson Extrapolation

(4.2) -Richardson Extrapolation (.) -Ricardson Extrapolation. Small-O Notation: Recall tat te big-o notation used to define te rate of convergence in Section.: Suppose tat lim G 0 and lim F L. Te function F is said to converge to L as

More information

Math 212-Lecture 9. For a single-variable function z = f(x), the derivative is f (x) = lim h 0

Math 212-Lecture 9. For a single-variable function z = f(x), the derivative is f (x) = lim h 0 3.4: Partial Derivatives Definition Mat 22-Lecture 9 For a single-variable function z = f(x), te derivative is f (x) = lim 0 f(x+) f(x). For a function z = f(x, y) of two variables, to define te derivatives,

More information

Polynomial Interpolation

Polynomial Interpolation Capter 4 Polynomial Interpolation In tis capter, we consider te important problem of approximatinga function fx, wose values at a set of distinct points x, x, x,, x n are known, by a polynomial P x suc

More information

Gradient Descent etc.

Gradient Descent etc. 1 Gradient Descent etc EE 13: Networked estimation and control Prof Kan) I DERIVATIVE Consider f : R R x fx) Te derivative is defined as d fx) = lim dx fx + ) fx) Te cain rule states tat if d d f gx) )

More information

Section 2.7 Derivatives and Rates of Change Part II Section 2.8 The Derivative as a Function. at the point a, to be. = at time t = a is

Section 2.7 Derivatives and Rates of Change Part II Section 2.8 The Derivative as a Function. at the point a, to be. = at time t = a is Mat 180 www.timetodare.com Section.7 Derivatives and Rates of Cange Part II Section.8 Te Derivative as a Function Derivatives ( ) In te previous section we defined te slope of te tangent to a curve wit

More information

1. Consider the trigonometric function f(t) whose graph is shown below. Write down a possible formula for f(t).

1. Consider the trigonometric function f(t) whose graph is shown below. Write down a possible formula for f(t). . Consider te trigonometric function f(t) wose grap is sown below. Write down a possible formula for f(t). Tis function appears to be an odd, periodic function tat as been sifted upwards, so we will use

More information

3. Using your answers to the two previous questions, evaluate the Mratio

3. Using your answers to the two previous questions, evaluate the Mratio MASSACHUSETTS INSTITUTE OF TECHNOLOGY DEPARTMENT OF MECHANICAL ENGINEERING CAMBRIDGE, MASSACHUSETTS 0219 2.002 MECHANICS AND MATERIALS II HOMEWORK NO. 4 Distributed: Friday, April 2, 2004 Due: Friday,

More information

Continuity and Differentiability of the Trigonometric Functions

Continuity and Differentiability of the Trigonometric Functions [Te basis for te following work will be te definition of te trigonometric functions as ratios of te sides of a triangle inscribed in a circle; in particular, te sine of an angle will be defined to be te

More information

Differentiation in higher dimensions

Differentiation in higher dimensions Capter 2 Differentiation in iger dimensions 2.1 Te Total Derivative Recall tat if f : R R is a 1-variable function, and a R, we say tat f is differentiable at x = a if and only if te ratio f(a+) f(a) tends

More information

MANY scientific and engineering problems can be

MANY scientific and engineering problems can be A Domain Decomposition Metod using Elliptical Arc Artificial Boundary for Exterior Problems Yajun Cen, and Qikui Du Abstract In tis paper, a Diriclet-Neumann alternating metod using elliptical arc artificial

More information

A SHORT INTRODUCTION TO BANACH LATTICES AND

A SHORT INTRODUCTION TO BANACH LATTICES AND CHAPTER A SHORT INTRODUCTION TO BANACH LATTICES AND POSITIVE OPERATORS In tis capter we give a brief introduction to Banac lattices and positive operators. Most results of tis capter can be found, e.g.,

More information

ERROR BOUNDS FOR THE METHODS OF GLIMM, GODUNOV AND LEVEQUE BRADLEY J. LUCIER*

ERROR BOUNDS FOR THE METHODS OF GLIMM, GODUNOV AND LEVEQUE BRADLEY J. LUCIER* EO BOUNDS FO THE METHODS OF GLIMM, GODUNOV AND LEVEQUE BADLEY J. LUCIE* Abstract. Te expected error in L ) attimet for Glimm s sceme wen applied to a scalar conservation law is bounded by + 2 ) ) /2 T

More information

1 Calculus. 1.1 Gradients and the Derivative. Q f(x+h) f(x)

1 Calculus. 1.1 Gradients and the Derivative. Q f(x+h) f(x) Calculus. Gradients and te Derivative Q f(x+) δy P T δx R f(x) 0 x x+ Let P (x, f(x)) and Q(x+, f(x+)) denote two points on te curve of te function y = f(x) and let R denote te point of intersection of

More information

Math 31A Discussion Notes Week 4 October 20 and October 22, 2015

Math 31A Discussion Notes Week 4 October 20 and October 22, 2015 Mat 3A Discussion Notes Week 4 October 20 and October 22, 205 To prepare for te first midterm, we ll spend tis week working eamples resembling te various problems you ve seen so far tis term. In tese notes

More information

Recall from our discussion of continuity in lecture a function is continuous at a point x = a if and only if

Recall from our discussion of continuity in lecture a function is continuous at a point x = a if and only if Computational Aspects of its. Keeping te simple simple. Recall by elementary functions we mean :Polynomials (including linear and quadratic equations) Eponentials Logaritms Trig Functions Rational Functions

More information

Some Review Problems for First Midterm Mathematics 1300, Calculus 1

Some Review Problems for First Midterm Mathematics 1300, Calculus 1 Some Review Problems for First Midterm Matematics 00, Calculus. Consider te trigonometric function f(t) wose grap is sown below. Write down a possible formula for f(t). Tis function appears to be an odd,

More information

LIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT

LIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT LIMITS AND DERIVATIVES Te limit of a function is defined as te value of y tat te curve approaces, as x approaces a particular value. Te limit of f (x) as x approaces a is written as f (x) approaces, as

More information

Solutions to the Multivariable Calculus and Linear Algebra problems on the Comprehensive Examination of January 31, 2014

Solutions to the Multivariable Calculus and Linear Algebra problems on the Comprehensive Examination of January 31, 2014 Solutions to te Multivariable Calculus and Linear Algebra problems on te Compreensive Examination of January 3, 24 Tere are 9 problems ( points eac, totaling 9 points) on tis portion of te examination.

More information

6. Non-uniform bending

6. Non-uniform bending . Non-uniform bending Introduction Definition A non-uniform bending is te case were te cross-section is not only bent but also seared. It is known from te statics tat in suc a case, te bending moment in

More information

Nonlinear weakly curved rod by Γ -convergence

Nonlinear weakly curved rod by Γ -convergence Noname manuscript No. (will be inserted by te editor Nonlinear weakly curved rod by Γ -convergence Igor Velčić te date of receipt and acceptance sould be inserted later Abstract We present a nonlinear

More information

Crouzeix-Velte Decompositions and the Stokes Problem

Crouzeix-Velte Decompositions and the Stokes Problem Crouzeix-Velte Decompositions and te Stokes Problem PD Tesis Strauber Györgyi Eötvös Loránd University of Sciences, Insitute of Matematics, Matematical Doctoral Scool Director of te Doctoral Scool: Dr.

More information

Analytic Functions. Differentiable Functions of a Complex Variable

Analytic Functions. Differentiable Functions of a Complex Variable Analytic Functions Differentiable Functions of a Complex Variable In tis capter, we sall generalize te ideas for polynomials power series of a complex variable we developed in te previous capter to general

More information

MA119-A Applied Calculus for Business Fall Homework 4 Solutions Due 9/29/ :30AM

MA119-A Applied Calculus for Business Fall Homework 4 Solutions Due 9/29/ :30AM MA9-A Applied Calculus for Business 006 Fall Homework Solutions Due 9/9/006 0:0AM. #0 Find te it 5 0 + +.. #8 Find te it. #6 Find te it 5 0 + + = (0) 5 0 (0) + (0) + =.!! r + +. r s r + + = () + 0 () +

More information

Mass Lumping for Constant Density Acoustics

Mass Lumping for Constant Density Acoustics Lumping 1 Mass Lumping for Constant Density Acoustics William W. Symes ABSTRACT Mass lumping provides an avenue for efficient time-stepping of time-dependent problems wit conforming finite element spatial

More information

MVT and Rolle s Theorem

MVT and Rolle s Theorem AP Calculus CHAPTER 4 WORKSHEET APPLICATIONS OF DIFFERENTIATION MVT and Rolle s Teorem Name Seat # Date UNLESS INDICATED, DO NOT USE YOUR CALCULATOR FOR ANY OF THESE QUESTIONS In problems 1 and, state

More information

lecture 26: Richardson extrapolation

lecture 26: Richardson extrapolation 43 lecture 26: Ricardson extrapolation 35 Ricardson extrapolation, Romberg integration Trougout numerical analysis, one encounters procedures tat apply some simple approximation (eg, linear interpolation)

More information

Mathematics 123.3: Solutions to Lab Assignment #5

Mathematics 123.3: Solutions to Lab Assignment #5 Matematics 3.3: Solutions to Lab Assignment #5 Find te derivative of te given function using te definition of derivative. State te domain of te function and te domain of its derivative..: f(x) 6 x Solution:

More information

5 Ordinary Differential Equations: Finite Difference Methods for Boundary Problems

5 Ordinary Differential Equations: Finite Difference Methods for Boundary Problems 5 Ordinary Differential Equations: Finite Difference Metods for Boundary Problems Read sections 10.1, 10.2, 10.4 Review questions 10.1 10.4, 10.8 10.9, 10.13 5.1 Introduction In te previous capters we

More information

1. Introduction. We consider the model problem: seeking an unknown function u satisfying

1. Introduction. We consider the model problem: seeking an unknown function u satisfying A DISCONTINUOUS LEAST-SQUARES FINITE ELEMENT METHOD FOR SECOND ORDER ELLIPTIC EQUATIONS XIU YE AND SHANGYOU ZHANG Abstract In tis paper, a discontinuous least-squares (DLS) finite element metod is introduced

More information

A Finite Element Primer

A Finite Element Primer A Finite Element Primer David J. Silvester Scool of Matematics, University of Mancester d.silvester@mancester.ac.uk. Version.3 updated 4 October Contents A Model Diffusion Problem.................... x.

More information

Polynomial Interpolation

Polynomial Interpolation Capter 4 Polynomial Interpolation In tis capter, we consider te important problem of approximating a function f(x, wose values at a set of distinct points x, x, x 2,,x n are known, by a polynomial P (x

More information

A = h w (1) Error Analysis Physics 141

A = h w (1) Error Analysis Physics 141 Introduction In all brances of pysical science and engineering one deals constantly wit numbers wic results more or less directly from experimental observations. Experimental observations always ave inaccuracies.

More information

Differential Calculus (The basics) Prepared by Mr. C. Hull

Differential Calculus (The basics) Prepared by Mr. C. Hull Differential Calculus Te basics) A : Limits In tis work on limits, we will deal only wit functions i.e. tose relationsips in wic an input variable ) defines a unique output variable y). Wen we work wit

More information

Finite Difference Method

Finite Difference Method Capter 8 Finite Difference Metod 81 2nd order linear pde in two variables General 2nd order linear pde in two variables is given in te following form: L[u] = Au xx +2Bu xy +Cu yy +Du x +Eu y +Fu = G According

More information

4. The slope of the line 2x 7y = 8 is (a) 2/7 (b) 7/2 (c) 2 (d) 2/7 (e) None of these.

4. The slope of the line 2x 7y = 8 is (a) 2/7 (b) 7/2 (c) 2 (d) 2/7 (e) None of these. Mat 11. Test Form N Fall 016 Name. Instructions. Te first eleven problems are wort points eac. Te last six problems are wort 5 points eac. For te last six problems, you must use relevant metods of algebra

More information

CLOSED CONVEX SHELLS Meunargia T. Mixed forms of stress-strain relations are given in the form. λ + 2µ θ + 1

CLOSED CONVEX SHELLS Meunargia T. Mixed forms of stress-strain relations are given in the form. λ + 2µ θ + 1 Seminar of I. Vekua Institute of Applied Matematics REPORTS, Vol. 43, 207 CLOSED CONVEX SHELLS Meunargia T. Abstract. If Ω is a closed convex sell, ten S : x 3 = 0 is an ovaloid. It is proved tat in tis

More information

10 Derivatives ( )

10 Derivatives ( ) Instructor: Micael Medvinsky 0 Derivatives (.6-.8) Te tangent line to te curve yf() at te point (a,f(a)) is te line l m + b troug tis point wit slope Alternatively one can epress te slope as f f a m lim

More information

1. Questions (a) through (e) refer to the graph of the function f given below. (A) 0 (B) 1 (C) 2 (D) 4 (E) does not exist

1. Questions (a) through (e) refer to the graph of the function f given below. (A) 0 (B) 1 (C) 2 (D) 4 (E) does not exist Mat 1120 Calculus Test 2. October 18, 2001 Your name Te multiple coice problems count 4 points eac. In te multiple coice section, circle te correct coice (or coices). You must sow your work on te oter

More information

Semigroups of Operators

Semigroups of Operators Lecture 11 Semigroups of Operators In tis Lecture we gater a few notions on one-parameter semigroups of linear operators, confining to te essential tools tat are needed in te sequel. As usual, X is a real

More information

Discrete Monogenic Functions in Image processing

Discrete Monogenic Functions in Image processing Discrete Function Teory Discrete Monogenic Functions in Image processing U. Käler CIDMA and Departamento de Matemática Universidade de Aveiro ukaeler@ua.pt MOIMA Scloss Herrenausen Hannover, June 20-24,

More information

Sample Problems for Exam II

Sample Problems for Exam II Sample Problems for Exam 1. Te saft below as lengt L, Torsional stiffness GJ and torque T is applied at point C, wic is at a distance of 0.6L from te left (point ). Use Castigliano teorem to Calculate

More information

MATH1901 Differential Calculus (Advanced)

MATH1901 Differential Calculus (Advanced) MATH1901 Dierential Calculus (Advanced) Capter 3: Functions Deinitions : A B A and B are sets assigns to eac element in A eactl one element in B A is te domain o te unction B is te codomain o te unction

More information

Weierstraß-Institut. im Forschungsverbund Berlin e.v. Preprint ISSN

Weierstraß-Institut. im Forschungsverbund Berlin e.v. Preprint ISSN Weierstraß-Institut für Angewandte Analysis und Stocastik im Forscungsverbund Berlin e.v. Preprint ISSN 0946 8633 Stability of infinite dimensional control problems wit pointwise state constraints Micael

More information

Smoothed projections in finite element exterior calculus

Smoothed projections in finite element exterior calculus Smooted projections in finite element exterior calculus Ragnar Winter CMA, University of Oslo Norway based on joint work wit: Douglas N. Arnold, Minnesota, Ricard S. Falk, Rutgers, and Snorre H. Cristiansen,

More information

FINITE DIFFERENCE APPROXIMATIONS FOR NONLINEAR FIRST ORDER PARTIAL DIFFERENTIAL EQUATIONS

FINITE DIFFERENCE APPROXIMATIONS FOR NONLINEAR FIRST ORDER PARTIAL DIFFERENTIAL EQUATIONS UNIVERSITATIS IAGELLONICAE ACTA MATHEMATICA, FASCICULUS XL 2002 FINITE DIFFERENCE APPROXIMATIONS FOR NONLINEAR FIRST ORDER PARTIAL DIFFERENTIAL EQUATIONS by Anna Baranowska Zdzis law Kamont Abstract. Classical

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL IFFERENTIATION FIRST ERIVATIVES Te simplest difference formulas are based on using a straigt line to interpolate te given data; tey use two data pints to estimate te derivative. We assume tat

More information

Name: Answer Key No calculators. Show your work! 1. (21 points) All answers should either be,, a (finite) real number, or DNE ( does not exist ).

Name: Answer Key No calculators. Show your work! 1. (21 points) All answers should either be,, a (finite) real number, or DNE ( does not exist ). Mat - Final Exam August 3 rd, Name: Answer Key No calculators. Sow your work!. points) All answers sould eiter be,, a finite) real number, or DNE does not exist ). a) Use te grap of te function to evaluate

More information

Spotlight on Laplace s Equation

Spotlight on Laplace s Equation 16 Spotlight on Laplace s Equation Reference: Sections 1.1,1.2, and 1.5. Laplace s equation is the undriven, linear, second-order PDE 2 u = (1) We defined diffusivity on page 587. where 2 is the Laplacian

More information

Part VIII, Chapter 39. Fluctuation-based stabilization Model problem

Part VIII, Chapter 39. Fluctuation-based stabilization Model problem Part VIII, Capter 39 Fluctuation-based stabilization Tis capter presents a unified analysis of recent stabilization tecniques for te standard Galerkin approximation of first-order PDEs using H 1 - conforming

More information

Quantum Numbers and Rules

Quantum Numbers and Rules OpenStax-CNX module: m42614 1 Quantum Numbers and Rules OpenStax College Tis work is produced by OpenStax-CNX and licensed under te Creative Commons Attribution License 3.0 Abstract Dene quantum number.

More information

Convexity and Smoothness

Convexity and Smoothness Capter 4 Convexity and Smootness 4.1 Strict Convexity, Smootness, and Gateaux Differentiablity Definition 4.1.1. Let X be a Banac space wit a norm denoted by. A map f : X \{0} X \{0}, f f x is called a

More information

PECULIARITIES OF THE WAVE FIELD LOCALIZATION IN THE FUNCTIONALLY GRADED LAYER

PECULIARITIES OF THE WAVE FIELD LOCALIZATION IN THE FUNCTIONALLY GRADED LAYER Materials Pysics and Mecanics (5) 5- Received: Marc 7, 5 PECULIARITIES OF THE WAVE FIELD LOCALIZATION IN THE FUNCTIONALLY GRADED LAYER Т.I. Belyankova *, V.V. Kalincuk Soutern Scientific Center of Russian

More information

NUMERICAL DIFFERENTIATION. James T. Smith San Francisco State University. In calculus classes, you compute derivatives algebraically: for example,

NUMERICAL DIFFERENTIATION. James T. Smith San Francisco State University. In calculus classes, you compute derivatives algebraically: for example, NUMERICAL DIFFERENTIATION James T Smit San Francisco State University In calculus classes, you compute derivatives algebraically: for example, f( x) = x + x f ( x) = x x Tis tecnique requires your knowing

More information

MAT 1339-S14 Class 2

MAT 1339-S14 Class 2 MAT 1339-S14 Class 2 July 07, 2014 Contents 1 Rate of Cange 1 1.5 Introduction to Derivatives....................... 1 2 Derivatives 5 2.1 Derivative of Polynomial function.................... 5 2.2 Te

More information

7.1 Using Antiderivatives to find Area

7.1 Using Antiderivatives to find Area 7.1 Using Antiderivatives to find Area Introduction finding te area under te grap of a nonnegative, continuous function f In tis section a formula is obtained for finding te area of te region bounded between

More information

Calculus I Practice Exam 1A

Calculus I Practice Exam 1A Calculus I Practice Exam A Calculus I Practice Exam A Tis practice exam empasizes conceptual connections and understanding to a greater degree tan te exams tat are usually administered in introductory

More information

MIXED DISCONTINUOUS GALERKIN APPROXIMATION OF THE MAXWELL OPERATOR. SIAM J. Numer. Anal., Vol. 42 (2004), pp

MIXED DISCONTINUOUS GALERKIN APPROXIMATION OF THE MAXWELL OPERATOR. SIAM J. Numer. Anal., Vol. 42 (2004), pp MIXED DISCONTINUOUS GALERIN APPROXIMATION OF THE MAXWELL OPERATOR PAUL HOUSTON, ILARIA PERUGIA, AND DOMINI SCHÖTZAU SIAM J. Numer. Anal., Vol. 4 (004), pp. 434 459 Abstract. We introduce and analyze a

More information

Chapter Primer on Differentiation

Chapter Primer on Differentiation Capter 0.01 Primer on Differentiation After reaing tis capter, you soul be able to: 1. unerstan te basics of ifferentiation,. relate te slopes of te secant line an tangent line to te erivative of a function,.

More information

3.1 Extreme Values of a Function

3.1 Extreme Values of a Function .1 Etreme Values of a Function Section.1 Notes Page 1 One application of te derivative is finding minimum and maimum values off a grap. In precalculus we were only able to do tis wit quadratics by find

More information

Grade: 11 International Physics Olympiad Qualifier Set: 2

Grade: 11 International Physics Olympiad Qualifier Set: 2 Grade: 11 International Pysics Olympiad Qualifier Set: 2 --------------------------------------------------------------------------------------------------------------- Max Marks: 60 Test ID: 12111 Time

More information

Exam 1 Review Solutions

Exam 1 Review Solutions Exam Review Solutions Please also review te old quizzes, and be sure tat you understand te omework problems. General notes: () Always give an algebraic reason for your answer (graps are not sufficient),

More information

Math 1210 Midterm 1 January 31st, 2014

Math 1210 Midterm 1 January 31st, 2014 Mat 110 Midterm 1 January 1st, 01 Tis exam consists of sections, A and B. Section A is conceptual, wereas section B is more computational. Te value of every question is indicated at te beginning of it.

More information

INTRODUCTION AND MATHEMATICAL CONCEPTS

INTRODUCTION AND MATHEMATICAL CONCEPTS Capter 1 INTRODUCTION ND MTHEMTICL CONCEPTS PREVIEW Tis capter introduces you to te basic matematical tools for doing pysics. You will study units and converting between units, te trigonometric relationsips

More information

Solution. Solution. f (x) = (cos x)2 cos(2x) 2 sin(2x) 2 cos x ( sin x) (cos x) 4. f (π/4) = ( 2/2) ( 2/2) ( 2/2) ( 2/2) 4.

Solution. Solution. f (x) = (cos x)2 cos(2x) 2 sin(2x) 2 cos x ( sin x) (cos x) 4. f (π/4) = ( 2/2) ( 2/2) ( 2/2) ( 2/2) 4. December 09, 20 Calculus PracticeTest s Name: (4 points) Find te absolute extrema of f(x) = x 3 0 on te interval [0, 4] Te derivative of f(x) is f (x) = 3x 2, wic is zero only at x = 0 Tus we only need

More information

Section 2.1 The Definition of the Derivative. We are interested in finding the slope of the tangent line at a specific point.

Section 2.1 The Definition of the Derivative. We are interested in finding the slope of the tangent line at a specific point. Popper 6: Review of skills: Find tis difference quotient. f ( x ) f ( x) if f ( x) x Answer coices given in audio on te video. Section.1 Te Definition of te Derivative We are interested in finding te slope

More information

Math 34A Practice Final Solutions Fall 2007

Math 34A Practice Final Solutions Fall 2007 Mat 34A Practice Final Solutions Fall 007 Problem Find te derivatives of te following functions:. f(x) = 3x + e 3x. f(x) = x + x 3. f(x) = (x + a) 4. Is te function 3t 4t t 3 increasing or decreasing wen

More information

University Mathematics 2

University Mathematics 2 University Matematics 2 1 Differentiability In tis section, we discuss te differentiability of functions. Definition 1.1 Differentiable function). Let f) be a function. We say tat f is differentiable at

More information

Error analysis of a finite element method for the Willmore flow of graphs

Error analysis of a finite element method for the Willmore flow of graphs Interfaces and Free Boundaries 8 6, 46 Error analysis of a finite element metod for te Willmore flow of graps KLAUS DECKELNICK Institut für Analysis und Numerik, Otto-von-Guericke-Universität Magdeburg,

More information

Lecture XVII. Abstract We introduce the concept of directional derivative of a scalar function and discuss its relation with the gradient operator.

Lecture XVII. Abstract We introduce the concept of directional derivative of a scalar function and discuss its relation with the gradient operator. Lecture XVII Abstract We introduce te concept of directional derivative of a scalar function and discuss its relation wit te gradient operator. Directional derivative and gradient Te directional derivative

More information

An approximation method using approximate approximations

An approximation method using approximate approximations Applicable Analysis: An International Journal Vol. 00, No. 00, September 2005, 1 13 An approximation metod using approximate approximations FRANK MÜLLER and WERNER VARNHORN, University of Kassel, Germany,

More information

RIGIDITY OF TIME-FLAT SURFACES IN THE MINKOWSKI SPACETIME

RIGIDITY OF TIME-FLAT SURFACES IN THE MINKOWSKI SPACETIME RIGIDITY OF TIME-FLAT SURFACES IN THE MINKOWSKI SPACETIME PO-NING CHEN, MU-TAO WANG, AND YE-KAI WANG Abstract. A time-flat condition on spacelike 2-surfaces in spacetime is considered ere. Tis condition

More information

Superconvergence of energy-conserving discontinuous Galerkin methods for. linear hyperbolic equations. Abstract

Superconvergence of energy-conserving discontinuous Galerkin methods for. linear hyperbolic equations. Abstract Superconvergence of energy-conserving discontinuous Galerkin metods for linear yperbolic equations Yong Liu, Ci-Wang Su and Mengping Zang 3 Abstract In tis paper, we study superconvergence properties of

More information

16.20 HANDOUT #2 Fall, 2002 Review of General Elasticity

16.20 HANDOUT #2 Fall, 2002 Review of General Elasticity 6.20 HANDOUT #2 Fall, 2002 Review of General Elasticity NOTATION REVIEW (e.g., for strain) Engineering Contracted Engineering Tensor Tensor ε x = ε = ε xx = ε ε y = ε 2 = ε yy = ε 22 ε z = ε 3 = ε zz =

More information

Math 161 (33) - Final exam

Math 161 (33) - Final exam Name: Id #: Mat 161 (33) - Final exam Fall Quarter 2015 Wednesday December 9, 2015-10:30am to 12:30am Instructions: Prob. Points Score possible 1 25 2 25 3 25 4 25 TOTAL 75 (BEST 3) Read eac problem carefully.

More information

LAYER UNDULATIONS IN SMECTIC A LIQUID CRYSTALS

LAYER UNDULATIONS IN SMECTIC A LIQUID CRYSTALS LAYER UNDULATIONS IN SMECTIC A LIQUID CRYSTALS CARLOS J. GARCíA-CERVERA AND SOOKYUNG JOO Abstract. We investigate instabilities of smectic A liquid crystals wen a magnetic field is applied in te direction

More information

Smoothness of solutions with respect to multi-strip integral boundary conditions for nth order ordinary differential equations

Smoothness of solutions with respect to multi-strip integral boundary conditions for nth order ordinary differential equations 396 Nonlinear Analysis: Modelling and Control, 2014, Vol. 19, No. 3, 396 412 ttp://dx.doi.org/10.15388/na.2014.3.6 Smootness of solutions wit respect to multi-strip integral boundary conditions for nt

More information

Tangent Lines-1. Tangent Lines

Tangent Lines-1. Tangent Lines Tangent Lines- Tangent Lines In geometry, te tangent line to a circle wit centre O at a point A on te circle is defined to be te perpendicular line at A to te line OA. Te tangent lines ave te special property

More information

Week #15 - Word Problems & Differential Equations Section 8.2

Week #15 - Word Problems & Differential Equations Section 8.2 Week #1 - Word Problems & Differential Equations Section 8. From Calculus, Single Variable by Huges-Hallett, Gleason, McCallum et. al. Copyrigt 00 by Jon Wiley & Sons, Inc. Tis material is used by permission

More information

SECTION 3.2: DERIVATIVE FUNCTIONS and DIFFERENTIABILITY

SECTION 3.2: DERIVATIVE FUNCTIONS and DIFFERENTIABILITY (Section 3.2: Derivative Functions and Differentiability) 3.2.1 SECTION 3.2: DERIVATIVE FUNCTIONS and DIFFERENTIABILITY LEARNING OBJECTIVES Know, understand, and apply te Limit Definition of te Derivative

More information

1 The Euler Forward scheme (schéma d'euler explicite)

1 The Euler Forward scheme (schéma d'euler explicite) TP : Finite dierence metod for a European option M2 Modélisation aléatoire - Université Denis-Diderot Cours EDP en Finance et Métodes Numériques. December 2016 1 Te Euler Forward sceme (scéma d'euler explicite)

More information

Nonlinear elliptic-parabolic problems

Nonlinear elliptic-parabolic problems Nonlinear elliptic-parabolic problems Inwon C. Kim and Norbert Požár Abstract We introduce a notion of viscosity solutions for a general class of elliptic-parabolic pase transition problems. Tese include

More information

Chapter 9 - Solved Problems

Chapter 9 - Solved Problems Capter 9 - Solved Problems Solved Problem 9.. Consider an internally stable feedback loop wit S o (s) = s(s + ) s + 4s + Determine weter Lemma 9. or Lemma 9. of te book applies to tis system. Solutions

More information

. Compute the following limits.

. Compute the following limits. Today: Tangent Lines and te Derivative at a Point Warmup:. Let f(x) =x. Compute te following limits. f( + ) f() (a) lim f( +) f( ) (b) lim. Let g(x) = x. Compute te following limits. g(3 + ) g(3) (a) lim

More information

Department of Mathematics, K.T.H.M. College, Nashik F.Y.B.Sc. Calculus Practical (Academic Year )

Department of Mathematics, K.T.H.M. College, Nashik F.Y.B.Sc. Calculus Practical (Academic Year ) F.Y.B.Sc. Calculus Practical (Academic Year 06-7) Practical : Graps of Elementary Functions. a) Grap of y = f(x) mirror image of Grap of y = f(x) about X axis b) Grap of y = f( x) mirror image of Grap

More information

EXISTENCE OF SOLUTIONS FOR A CLASS OF VARIATIONAL INEQUALITIES

EXISTENCE OF SOLUTIONS FOR A CLASS OF VARIATIONAL INEQUALITIES Journal of Matematics and Statistics 9 (4: 35-39, 3 ISSN: 549-3644 3 doi:.3844/jmssp.3.35.39 Publised Online 9 (4 3 (ttp://www.tescipub.com/jmss.toc EXISTENCE OF SOLUTIONS FOR A CLASS OF ARIATIONAL INEQUALITIES

More information

1. State whether the function is an exponential growth or exponential decay, and describe its end behaviour using limits.

1. State whether the function is an exponential growth or exponential decay, and describe its end behaviour using limits. Questions 1. State weter te function is an exponential growt or exponential decay, and describe its end beaviour using its. (a) f(x) = 3 2x (b) f(x) = 0.5 x (c) f(x) = e (d) f(x) = ( ) x 1 4 2. Matc te

More information

Lecture 10: Carnot theorem

Lecture 10: Carnot theorem ecture 0: Carnot teorem Feb 7, 005 Equivalence of Kelvin and Clausius formulations ast time we learned tat te Second aw can be formulated in two ways. e Kelvin formulation: No process is possible wose

More information

1 2 x Solution. The function f x is only defined when x 0, so we will assume that x 0 for the remainder of the solution. f x. f x h f x.

1 2 x Solution. The function f x is only defined when x 0, so we will assume that x 0 for the remainder of the solution. f x. f x h f x. Problem. Let f x x. Using te definition of te derivative prove tat f x x Solution. Te function f x is only defined wen x 0, so we will assume tat x 0 for te remainder of te solution. By te definition of

More information

Numerical analysis of a free piston problem

Numerical analysis of a free piston problem MATHEMATICAL COMMUNICATIONS 573 Mat. Commun., Vol. 15, No. 2, pp. 573-585 (2010) Numerical analysis of a free piston problem Boris Mua 1 and Zvonimir Tutek 1, 1 Department of Matematics, University of

More information