1 Chien-Hong Cho ( 卓建宏 ) (National Chung Cheng University)( 中正大學 ) 2010/11/11 in NCKU On the finite difference approximation for hyperbolic blow-up problems.

Slides:



Advertisements
Similar presentations
Finite Difference Discretization of Elliptic Equations: 1D Problem Lectures 2 and 3.
Advertisements

Finite Difference Discretization of Hyperbolic Equations: Linear Problems Lectures 8, 9 and 10.
Boyce/DiPrima 9th ed, Ch 2.4: Differences Between Linear and Nonlinear Equations Elementary Differential Equations and Boundary Value Problems, 9th edition,
5.4 Basis And Dimension.
5.1 Real Vector Spaces.
Shortest Vector In A Lattice is NP-Hard to approximate
Boyce/DiPrima 9th ed, Ch 2.8: The Existence and Uniqueness Theorem Elementary Differential Equations and Boundary Value Problems, 9th edition, by William.
One-phase Solidification Problem: FEM approach via Parabolic Variational Inequalities Ali Etaati May 14 th 2008.
Norms and spaces Definition: The space of all square integrable funcions defined in the domain is a finite number not infinity L2 norm of f Examplecompute.
Quantum One: Lecture 3. Implications of Schrödinger's Wave Mechanics for Conservative Systems.
1cs542g-term Notes. 2 Solving Nonlinear Systems  Most thoroughly explored in the context of optimization  For systems arising in implicit time.
Total Recall Math, Part 2 Ordinary diff. equations First order ODE, one boundary/initial condition: Second order ODE.
1 L-BFGS and Delayed Dynamical Systems Approach for Unconstrained Optimization Xiaohui XIE Supervisor: Dr. Hon Wah TAM.
Chapter 5 Orthogonality
Ch 5.2: Series Solutions Near an Ordinary Point, Part I
Lecture 1 Linear Variational Problems (Part I). 1. Motivation For those participants wondering why we start a course dedicated to nonlinear problems by.
Laplace Transforms Important analytical method for solving linear ordinary differential equations. - Application to nonlinear ODEs? Must linearize first.
1 L-BFGS and Delayed Dynamical Systems Approach for Unconstrained Optimization Xiaohui XIE Supervisor: Dr. Hon Wah TAM.
Introduction to Numerical Methods I
Tutorial 10 Iterative Methods and Matrix Norms. 2 In an iterative process, the k+1 step is defined via: Iterative processes Eigenvector decomposition.
2. Solving Schrödinger’s Equation Superposition Given a few solutions of Schrödinger’s equation, we can make more of them Let  1 and  2 be two solutions.
Boyce/DiPrima 9th ed, Ch 11.2: Sturm-Liouville Boundary Value Problems Elementary Differential Equations and Boundary Value Problems, 9th edition, by.
Copyright © Cengage Learning. All rights reserved. 3 Differentiation Rules.
Numerical Methods for Partial Differential Equations
Error estimates for degenerate parabolic equation Yabin Fan CASA Seminar,
Numerical Methods for Partial Differential Equations CAAM 452 Spring 2005 Lecture 9 Instructor: Tim Warburton.
MATH 685/ CSI 700/ OR 682 Lecture Notes Lecture 10. Ordinary differential equations. Initial value problems.
1 Chapter 6 Numerical Methods for Ordinary Differential Equations.
ORDINARY DIFFERENTIAL EQUATION (ODE) LAPLACE TRANSFORM.
1 Engineering Mathematics Ⅰ 呂學育 博士 Oct. 6, Short tangent segments suggest the shape of the curve Direction Fields 輪廓 Slope= x y.
Interpolation. Interpolation is important concept in numerical analysis. Quite often functions may not be available explicitly but only the values of.
Diophantine Approximation and Basis Reduction
Algorithms for a large sparse nonlinear eigenvalue problem Yusaku Yamamoto Dept. of Computational Science & Engineering Nagoya University.
The importance of sequences and infinite series in calculus stems from Newton’s idea of representing functions as sums of infinite series.  For instance,
SECOND-ORDER DIFFERENTIAL EQUATIONS Series Solutions SECOND-ORDER DIFFERENTIAL EQUATIONS In this section, we will learn how to solve: Certain.
Extrapolation Models for Convergence Acceleration and Function ’ s Extension David Levin Tel-Aviv University MAIA Erice 2013.
1 Spring 2003 Prof. Tim Warburton MA557/MA578/CS557 Lecture 5a.
Math 3120 Differential Equations with Boundary Value Problems
Prepared by Mrs. Azduwin Binti Khasri
Integration of 3-body encounter. Figure taken from
Discontinuous Galerkin Methods Li, Yang FerienAkademie 2008.
Lecture #11 Stability of switched system: Arbitrary switching João P. Hespanha University of California at Santa Barbara Hybrid Control and Switched Systems.
7. Introduction to the numerical integration of PDE. As an example, we consider the following PDE with one variable; Finite difference method is one of.
Serge Andrianov Theory of Symplectic Formalism for Spin-Orbit Tracking Institute for Nuclear Physics Forschungszentrum Juelich Saint-Petersburg State University,
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
Chapter 6. Residues and Poles Weiqi Luo ( 骆伟祺 ) School of Software Sun Yat-Sen University : Office : # A313
Chapter 24 Sturm-Liouville problem Speaker: Lung-Sheng Chien Reference: [1] Veerle Ledoux, Study of Special Algorithms for solving Sturm-Liouville and.
AUTOMATIC CONTROL THEORY II Slovak University of Technology Faculty of Material Science and Technology in Trnava.
1 Spring 2003 Prof. Tim Warburton MA557/MA578/CS557 Lecture 24.
Fourier series, Discrete Time Fourier Transform and Characteristic functions.
Advanced Engineering Mathematics, 7 th Edition Peter V. O’Neil © 2012 Cengage Learning Engineering. All Rights Reserved. CHAPTER 4 Series Solutions.
Optimization of Nonlinear Singularly Perturbed Systems with Hypersphere Control Restriction A.I. Kalinin and J.O. Grudo Belarusian State University, Minsk,
Boyce/DiPrima 9 th ed, Ch 11.3: Non- Homogeneous Boundary Value Problems Elementary Differential Equations and Boundary Value Problems, 9 th edition, by.
3.6 First Passage Time Distribution
Runge Kutta schemes Taylor series method Numeric solutions of ordinary differential equations.
Bounded Solutions of Kinematic Aggregation Equations Andrea Bertozzi Department of Mathematics, UCLA Thanks to support from ARO, NSF, and ONR and to contributions.
DYNAMIC BEHAVIOR OF PROCESSES :
Class 3 Linear System Solution Using the Laplace Transform
Convergence of Fourier series It is known that a periodic signal x(t) has a Fourier series representation if it satisfies the following Dirichlet conditions:
Introduction to Numerical Methods I
Modeling of Traffic Flow Problems
Advanced Engineering Mathematics 6th Edition, Concise Edition
§7-4 Lyapunov Direct Method
Complex Variables. Complex Variables Open Disks or Neighborhoods Definition. The set of all points z which satisfy the inequality |z – z0|
Stability Analysis of Linear Systems
Charles University Charles University STAKAN III
Laplace Transforms Important analytical method for solving linear ordinary differential equations. - Application to nonlinear ODEs? Must linearize first.
Laplace Transforms Important analytical method for solving linear ordinary differential equations. - Application to nonlinear ODEs? Must linearize first.
Presentation transcript:

1 Chien-Hong Cho ( 卓建宏 ) (National Chung Cheng University)( 中正大學 ) 2010/11/11 in NCKU On the finite difference approximation for hyperbolic blow-up problems

2 Contents  A brief introduction for blow-up problems.  Review on the parabolic blow-up problem.  CLM equation Spectral method Finite difference method  Numerical results of the semi-linear wave equation. Sufficient condition for blow-up. Numerical scheme for semi-linear wave equation and blow-up result  Future work.

3 Blow-up problem for  Broadly speaking, singularity occurs in the solution, its derivative, or its high-order derivatives in finite time.  Here, we use blow-up in a narrow sense. We say that the solution of an initial-value problem blows up in finite time T if the solution becomes infinity as where T is called the blow-up time.

4 Example The solution of the ODE is. The solution tends to infinity as t tends to 1.

5 More examples Semi-linear heat equation (Fujita, Weissler, Friedman, Mcleod, …) The porous medium equation with a nonlinear source (Samarskii, Galaktionov, …) Semi-linear wave equation (John, Kato, Glassey, Levine, …) CLM equation (Constantin, Lax, Majda, …) Hyperbolic type (H denotes the Hilbert transform)

Problem Occurred in Numerical Calculation for a Blow-up Problem Ex: Consider the ODE and the difference scheme The numerical solution exists for all That is, the numerical solution exists globally, or equivalently, the numerical solution does not blow up in finite time T. or equivalently,

7 Main purpose We want to construct an appropriate finite difference scheme for blow-up problems. By the word ‘ appropriate ’ we mean a scheme that satisfies the following: convergence. blow-up in finite time. convergence for the numerical blow-up time.

8 1-dim semi-linear heat equation where. Then the solution blows up in finite time T : (Fujita(1966), Weissler(1984), Friedman and Mcleod(1985), etc..)

9 Finite difference scheme where : the approximation of at : the spatial mesh point. : the time grid point. : fixed.

10 (numerical blow-up time) Blow-up cannot be reproduced if we use uniform

11 The semi-linear case (a) H is monotone increasing and (b) is monotone increasing. (c) Then Namely, the finite difference solution blows up in finite time & the numerical blow-up time converges to T. Let T be the blow-up time. Assume that H satisfies

12 Remark  This was a toy problem. Although the convergence of the numerical blow-up time is proved, the convergence rate still remains open.  More fluid related problem? The finite difference approximation becomes much more difficult for blow-up problems of hyperbolic type than the parabolic ones. We consider two simple equations -- CLM equation and the semi-linear wave equation, which show the difficulties. Our recent results will also be reported.

13 CLM equation The Constantin-Lax-Majda equation Here H denotes the Hilbert transform: where the integral denotes Cauchy’s principal part. is periodic in x and

14 Remark  A 1-dim model for the vorticity equation. (see Constantin, Lax, Majda (1985))  The solution to CLM equation is given explicitly by Thus, the solution blow-up in finite time if and only if is nonempty, where

15 Let Then Thus, the solution is given by

16 Spectral method for CLM equation Let N be a positive integer. Consider the following spectral approximation : where, for is given by denotes the approximation of the solution u.

17 For simplicity, we consider the case of odd function: whence Then we have which tells that is a polynomial in t of order ( n-1). Theorem does not blow up for all N.

18 Finite difference method Let Then one has (Constantin, Lax, Majda, 1985) We define a finite difference approximation in such a way that approximates for. Here, is by definition the imaginary part of. Then we have The solution does not blow up.

19 Other difference scheme  Discretize the Hilbert transform in a different way.  Difficulties: (a) The equalities derived from the properties of the Hilbert transform are not true in the discrete version. (b) It is difficult to show that the maximum values of the finite difference solution propagate to the zero of I.D. due to the complexity of the discretized Hilbert transform.

20 1-dim semi-linear wave equation  The solution blows up in finite time T. That is,  Many sufficient conditions for blow-up were given. For example, Glassey, John, Kato, Levine, etc..

21 Levine ’ s Result (1974) Let the nonlinear term be and the initial data satisfy Then the solution blows up in finite time T.

22 Another sufficient condition for blow-up (Cho) Let Assume that Then blows up in finite time T. Independent of the Levine ’ s condition. More convenient for numerical analysis.

23 By Jensen’s inequality, This implies the blow-up of. Sketch of the proof Multiply to both sides, one has where K is a constant decided by the initial data.

24 Numerical Scheme where : the approximation of at : the spatial mesh point. : the time grid point. : fixed.

25 Remark If we put, then the scheme is in fact

26 Moreover, assume that converges to u (t, x) while u is smooth. Then the numerical blow-up time also converges. Namely, Theorem (Cho) Define Assume that H satisfies (H1) is monotone increasing. (H2) (H3) Then the solution blows up in finite time. That is, : constant decided by I.D.

27 Convergence while u is smooth  Suppose the solution u blows up at t = T.  u is smooth in  u j n converges to u in That is, as long as

28 Numerical examples

29 Numerical examples

30 Difficulty in proving convergence  Two level time meshes appear in the scheme and thus their relation plays an important role in the stability.  To show the convergence (while u is smooth), we need some a priori estimates or stability in some norms, which can be derived from the well- known “ energy conservation property ” of the wave equations for the uniform time mesh ( ), while the energy need not be conserved for non-uniform time mesh.

31 Remark  In fact, to prove the convergence (while u is smooth), we only need the stability for the finite difference solution of the linear wave equation. But for the non-uniform time mesh, only a little is known.  Samarskii & Matus ’ s scheme(2001); Matsuo ’ s ( 松 尾宇泰 ) scheme(2007): strong restriction on the spatial part of their scheme.

32 Linear wave equation We consider the initial-boundary-value Problem Then we have That is,

33 Finite difference scheme We consider and the well-known discrete energy which corresponds to the energy Then we have

34 Samarskii ’ s and Matsuo ’ s scheme  Samarskii et. al considered a difference equation in a finite dimensional space and then applied to the linear wave equation.  Matsuo used the so-called discrete variational method. Namely, he defined the discrete energy first, and then derived the finite difference scheme whose solution conserves the given discrete energy.  Neither of which can be applied to our scheme.

Semi-discrete scheme Moreover, we have that, for any There exist such that and that Theorem (Cho)

Remark  It should be noted that we can prove the convergence of the numerical solution for the semi-discrete scheme by using the energy conservation property of the linear wave equation, which does not hold in the full-discrete case.

2-nd order ODE We consider the 2-nd ODE blow-up problem where and the finite difference analogue

Theorem (Cho) Under certain assumption on H, we have where T denotes the blow-up time of denotes the numerical blow-up time. are constants independent of. C. H. Cho, On the convergence of numerical blow-up time for a 2 nd order nonlinear ordinary differential equation, Appl. Math. Lett., 24, 2011,

39 Future work  Stability for finite difference schemes of the linear wave equation with non-uniform time meshes.  A rigorous proof for the convergence of the finite difference solution to the semi-linear wave equation.  Convergence order for the numerical blow-up time.

40

41 Thank you for your attention.

References C.-H. Cho, S. Hamada, and H. Okamoto, On the finite difference approximation for a parabolic blow-up problem, Japan J. Indust. Appl. Math., 24 (2007), pp C.-H. Cho, A finite difference scheme for blow-up problems of nonlinear wave equations, Numerical Mathematics:TMA, 3 (2010), pp C.-H. Cho, On the convergence of numerical blow-up time for a second order nonlinear ordinary differential equation, Appl. Math. Lett., vol.24 no.1 (2011), pp