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Implementing Spectral Methods for Partial Differential Equations

Algorithms for Scientists and Engineers, Scientific Computation

Erschienen am 20.05.2009, Auflage: 1/2009
149,79 €
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Bibliografische Daten
ISBN/EAN: 9789048122608
Sprache: Englisch
Umfang: xviii, 397 S.
Einband: gebundenes Buch

Beschreibung

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.

Autorenportrait

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.

Inhalt

Part I: Approximating Functions, Derivatives and Integrals. 1. Spectral Approximation. 2. Algorithms For Periodic Functions. 3. Algorithms For Non-Periodic Functions. Part II: Approximating Solutions of PDEs. 4. Survey of Spectral Approximations. 5. Spectral Approximation on the Square.6. Transformation Methods from Square to Non-Square Geometries. 7.Spectral Methods in Non-Square Geometries. 8.Spectral Element Methods. A: Miscellaneous Algorithms. B. Floating Point Arithmetic. C. Basic Linear Algebra Subroutines (BLAS). D. Linear Solvers. E. Data Structures.

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