Numerical Analysis of Partial Differential Equations (eBook)

S. H. Lui, PhD, is Associate Professor of Mathematics in the Department of Mathematics at the University of Manitoba, Canada.

Preface.

Acknowledgments.

1. Finite Difference.

1.1 Second-Order Approximation for Delta.

1.2 Fourth-Order Approximation for Delta.

1.3 Neumann Boundary Condition.

1.4 Polar Coordinates.

1.5 Curved Boundary.

1.6 Difference Approximation for Delta².

1.7 A Convection-Diffusion Equation.

1.8 Appendix: Analysis of Discrete Operators.

1.9 Summary and Exercises.

2. Mathematical Theory of Elliptic PDEs.

2.1 Function Spaces.

2.2 Derivatives.

2.3 Sobolev Spaces.

2.4 Sobolev Embedding Theory.

2.5 Traces.

2.6 Negative Sobolev Spaces.

2.7 Some Inequalities and Identities.

2.8 Weak Solutions.

2.9 Linear Elliptic PDEs.

2.10 Appendix: Some Definitions and Theorems.

2.11 Summary and Exercises.

3. Finite Elements.

3.1 Approximate Methods of Solution.

3.2 Finite Elements in 1D.

3.3 Finite Elements in 2D.

3.4 Inverse Estimate.

3.5 L² and Negative-Norm Estimates.

3.6 A Posteriori Estimate.

3.7 Higher-Order Elements.

3.8 Quadrilateral Elements.

3.9 Numerical Integration.

3.10 Stokes Problem.

3.11 Linear Elasticity.

3.12 Summary and Exercises.

4. Numerical Linear Algebra.

4.1 Condition Numbers.

4.2 Classical Iterative Methods.

4.3 Krylov Subspace Methods.

4.4 Preconditioning.

4.5 Direct Methods.

4.6 Appendix: Chebyshev Polynomials.

4.7 Summary and Exercises.

5. Spectral Methods.

5.1 Trigonometric Polynomials.

5.2 Fourier Spectral Method.

5.3 Orthogonal Polynomials.

5.4 Spectral Gakerkin and Spectral Tau Methods.

5.5 Spectral Collocation.

5.6 Polar Coordinates.

5.7 Neumann Problems

5.8 Fourth-Order PDEs.

5.9 Summary and Exercises.

6. Evolutionary PDEs.

6.1 Finite Difference Schemes for Heat Equation.

6.2 Other Time Discretization Schemes.

6.3 Convection-Dominated equations.

6.4 Finite Element Scheme for Heat Equation.

6.5 Spectral Collocation for Heat Equation.

6.6 Finite Different Scheme for Wave Equation.

6.7 Dispersion.

6.8 Summary and Exercises.

7. Multigrid.

7.1 Introduction.

7.2 Two-Grid Method.

7.3 Practical Multigrid Algorithms.

7.4 Finite Element Multigrid.

7.5 Summary and Exercises.

8. Domain Decomposition.

8.1 Overlapping Schwarz Methods.

8.2 Projections.

8.3 Non-overlapping Schwarz Method.

8.4 Substructuring Methods.

8.5 Optimal Substructuring Methods.

8.6 Summary and Exercises.

9. Infinite Domains.

9.1 Absorbing Boundary Conditions.

9.2 Dirichlet-Neumann Map.

9.3 Perfectly Matched Layer.

9.4 Boundary Integral Methods.

9.5 Fast Multiple Method.

9.6 Summary and Exercises.

10. Nonlinear Problems.

10.1 Newton's Method.

10.2 Other Methods.

10.3 Some Nonlinear Problems.

10.4 Software.

10.5 Program Verification.

10.6 Summary and Exercises.

Answers to Selected Exercises.

References.

Index.

"Requiring only a preliminary understanding of analysis,
Numerical Analysis of Partial Differential Equations is suitable
for courses on numerical PDEs at the upper-undergraduate and
graduate levels. The book is also appropriate for students majoring
in the mathematical sciences and engineering."
(Zentralblatt MATH, 1 December 2012)

"Recommended. Upper-division undergraduates,
graduate students, and researchers/faculty."
(Choice, 1 May 2012)