Overview
- First book to cover multidomain spectral methods for the numerical solution of time-dependent 1D and 2D partial differential equations
- Presented without too much abstract mathematics and minutae
- Contains a set of basic examples as building blocks for solving complex PDEs in realistic geometries
- With exercises and questions at the end of each chapter
- Both an introduction for graduate students and a reference for computational scientists working on numerical solutions of PDEs
- Includes supplementary material: sn.pub/extras
Part of the book series: Scientific Computation (SCIENTCOMP)
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About this book
This book offers a systematic and self-contained approach to solve partial differential equations numerically using single and multidomain spectral methods. It contains detailed algorithms in pseudocode for the application of spectral approximations to both one and two dimensional PDEs of mathematical physics describing potentials, transport, and wave propagation. David Kopriva, a well-known researcher in the field with extensive practical experience, shows how only a few fundamental algorithms form the building blocks of any spectral code, even for problems with complex geometries. The book addresses computational and applications scientists, as it emphasizes the practical derivation and implementation of spectral methods over abstract mathematics. It is divided into two parts: First comes a primer on spectral approximation and the basic algorithms, including FFT algorithms, Gauss quadrature algorithms, and how to approximate derivatives. The second part shows how to use those algorithms to solve steady and time dependent PDEs in one and two space dimensions. Exercises and questions at the end of each chapter encourage the reader to experiment with the algorithms.
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Keywords
- Approximation of Derivatives
- FFT Algorithm
- Implementation of Spectral Methods
- Multidomain Spectral Methods
- Numerical Algorithms
- PDE
- PDEs in Realistic Geometries
- PDEs with Complex Geometries
- Partial Differential Equations
- Scientific Computing
- Solving Complex PDEs
- Spectral Approximations of PDEs
- Spectral Method
- algorithms
- partial differential equation
Table of contents (9 chapters)
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Front Matter
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Approximating Functions, Derivatives and Integrals
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Front Matter
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Approximating Solutions of PDEs
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Front Matter
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Erratum
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Back Matter
Reviews
From the reviews:
“This book focuses on the implementation aspects of spectral methods. … serve as a textbook for graduate students and applied mathematics researchers who seek a practical way to implement spectral algorithms. The presentation is pedagogical, moving from algorithms that are easy to understand to ones that are more complex and involved. … It is a very recommendable book for a graduate course on spectral methods, and covers more practical subjects that are not usually treated in detail in other monographs on spectral methods.” (Javier de Frutos, Mathematical Reviews, Issue 2010 j)About the author
David Kopriva is Professor of Mathematics at the Florida State University, where he has taught since 1985. He is an expert in the development, implementation and application of high order spectral multi-domain methods for time dependent problems. In 1986 he developed the first multi-domain spectral method for hyperbolic systems, which was applied to the Euler equations of gas dynamics.
Bibliographic Information
Book Title: Implementing Spectral Methods for Partial Differential Equations
Book Subtitle: Algorithms for Scientists and Engineers
Authors: David A. Kopriva
Series Title: Scientific Computation
DOI: https://doi.org/10.1007/978-90-481-2261-5
Publisher: Springer Dordrecht
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media B.V. 2009
Hardcover ISBN: 978-90-481-2260-8Published: 20 May 2009
Softcover ISBN: 978-90-481-8484-2Published: 19 October 2010
eBook ISBN: 978-90-481-2261-5Published: 27 May 2009
Series ISSN: 1434-8322
Series E-ISSN: 2198-2589
Edition Number: 1
Number of Pages: XVIII, 397
Topics: Partial Differential Equations, Analysis, Applications of Mathematics, Numerical and Computational Physics, Simulation, Numeric Computing, Theoretical, Mathematical and Computational Physics