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An Introduction to Scientific Computing: Twelve Computational Projects Solved with MATLAB

Autor Ionut Danaila, Pascal Joly, Sidi Mahmoud Kaber, Marie Postel
en Limba Engleză Hardback – 27 noi 2006
Teaching or learning numerical methods in applied mathematics cannot be conceived nowadays without numerical experimentation on computers. There is a vast literature devoted either to theoretical numerical methods or - merical programming of basic algorithms, but there are few texts o?ering a complete discussion of numerical issues involved in the solution of concrete and relatively complex problems. This book is an attempt to ?ll this need. It is our belief that advantages and drawbacks of a numerical method cannot be accounted for without one’s experiencing all the steps of scienti?c comp- ing, from physical and mathematical description of the problem to numerical formulation and programming and, ?nally, to critical discussion of numerical results. The book provides twelve computational projects aimed at numerically solving problems selected to cover a broad spectrum of applications, from ?uid mechanics, chemistry, elasticity, thermal science, computer-aided design, signal and imageprocessing, etc. Even though the main volume of this text concerns the numerical analysis of computational methods and their imp- mentation, we have tried to start, when possible, from realistic problems of practical interest for researchers and engineers. For each project, an introductory record card summarizes the mathem- ical and numerical topics explained and the ?elds of application of the - proach. A level of di?culty, scaling from 1 to 3, is assigned to each project.
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Specificații

ISBN-13: 9780387308890
ISBN-10: 038730889X
Pagini: 294
Ilustrații: XVI, 294 p. 135 illus.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.57 kg
Ediția:2007
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States

Public țintă

Graduate

Cuprins

Numerical Approximation of Model Partial Differential Equations.- Nonlinear Differential Equations: Application to Chemical Kinetics.- Polynomial Approximation.- Solving an Advection-Diffusion Equation by a Finite Element Method.- Solving a Differential Equation by a Spectral Method.- Signal Processing: Multiresolution Analysis.- Elasticity: Elastic Deformation of a Thin Plate.- Domain Decomposition Using a Schwarz Method.- Geometrical Design: Bézier Curves and Surfaces.- Gas Dynamics: The Riemann Problem and Discontinuous Solutions: Application to the Shock Tube Problem.- Thermal Engineering: Optimization of an Industrial Furnace.- Fluid Dynamics: Solving the Two-Dimensional Navier-Stokes Equations.

Recenzii

From the reviews:
"In An Introduction to Scientific Computing, the authors present approaches to the numerical solution of problems drawn from a variety of applications. … This is a graduate-level introduction and the pace is brisk. … This is a strong text on scientific computing for advanced students in applied mathematics. … the book is most appropriate for students with some prior experience in scientific computing … ." (William J. Satzer, MathDL, February, 2007)
"The book is based on material offered by the authors at Universite Pierre et Marie Curie (Paris, France) and different engineering schools. It is intended as a graduate-level text in applied mathematics, but it may also be used by students in engineering or physical sciences. It may also be used as a reference for researchers and practicing engineers. Since different possible levels of each project are suggested, the text can be used to propose assignments at different graduate levels." (I. N. Katz, Zentralblatt MATH, Vol. 1119 (21), 2007)
"An Introduction to Scientific Computing plunges into solving PDEs by numerical approximation. … the book is an attempt to completely discuss numerical issues for reasonably complex problems at the level of a graduate textbook. A project-based approach is used. … Overall, this is a pleasing and useful companion to more complete expositions of the topic. … If you’re preparing advanced students for a workshop, or organizing a numerical analysis club for the semester, then the book is perfect." (Sorin Mitran, SIAM Review, Vol. 50 (1), 2008)

Textul de pe ultima copertă

This book provides twelve computational projects aimed at numerically solving problems from a broad range of applications including Fluid Mechanics, Chemistry, Elasticity, Thermal Science, Computer Aided Design, Signal and Image Processing. For each project the reader is guided through the typical steps of scientific computing from physical and mathematical description of the problem, to numerical formulation and programming and finally to critical discussion of numerical results. Considerable emphasis is placed on practical issues of computational methods. The last section of each project contains the solutions to all proposed exercises and guides the reader in using the MATLAB scripts. The mathematical framework provides a basic foundation in the subject of numerical analysis of partial differential equations and main discretization techniques, such as finite differences, finite elements, spectral methods and wavelets).
The book is primarily intended as a graduate-level text in applied mathematics, but it may also be used by students in engineering or physical sciences. It will also be a useful reference for researchers and practicing engineers.

Caracteristici

MATLAB computer programs for each application-project are made available from the Web site of the Editor Versions using the share-ware language Scilab are provided Complementary bibliography is provided with each project Web page for the book: http://www.ann.jussieu.fr/AI2SC provides an introduction to the book, a chapter content and for each chapter compressed archives containing the MATLAB solutions Chapter summaries, detailed illustrations, and study guides at the end of sections included Exericeses and selected solutions provided Includes supplementary material: sn.pub/extras

Notă biografică

Ionut Danaila is Professor of Applied Mathematics at the University of Rouen Normandy, Laboratoire de mathématiques Raphaël Salem, and former member of Laboratoire  Jacques-Louis Lions, Sorbonne Université. He is co-author of  two textbooks (in French) on scientific computing and one research monograph (on vortex ring models) for researchers and graduate students. His main research interests are in numerical analysis and modern scientific computing. He developed several numerical codes for applications in fluid mechanics, quantum physics and thermal sciences. Over the last decade, he headed two fundamental research projects on the mathematical modelling and high-performance simulation of quantum systems (Bose-Einstein condensates and superfluid helium).
Pascal Joly, now retired, was Research Scientist at Laboratoire  Jacques-Louis Lions, Sorbonne Université and Centre national de la recherche scientifique (CNRS). His main research interests concern efficient algorithms in scientific computing (such as solving large sparse linear systems of equations), coding finite element methods for various industrial applications and exploring the wavelets theory in signal processing. He taught courses on numerical methods in various engineering schools and he is former deputy director of the Master of Sciences and Technology of the Université Pierre et Marie Curie for applied Mathematics.
 
Sidi-Mahmoud Kaber is Associate Professor of Applied Mathematics at Laboratoire  Jacques-Louis Lions, Sorbonne Université. He is co-author of three textbooks in French and one in English on numerical analysis. His main research interests include approximation of singular functions and numerical schemes for parallel computing. He is very engaged in using programming and software in mathematics education.
 
  Marie Postel is Associate Professor of Applied Mathematics at Laboratoire  Jacques-Louis Lions, Sorbonne Université. She is co-author of two textbooks (in French) on numerical methods. Her research interests are currently mathematical modeling of biological systems, along with the numerical simulation and calibration of model using experimental data. She has designed several adaptive methods in scientific computing for PDEs using multiresolution analysis. She is currently the head of a master program in engineering mathematics, and teaches numerical methods for ODEs, PDEs and optimization at undergraduate and graduate level.