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Numerical Methods for Singularly Perturbed Differential Equations

Convection-Diffusion and Flow Problems

  • Book
  • © 1996

Overview

Part of the book series: Springer Series in Computational Mathematics (SSCM, volume 24)

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Table of contents (4 chapters)

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About this book

The analysis of singular perturbed differential equations began early in this century, when approximate solutions were constructed from asymptotic ex­ pansions. (Preliminary attempts appear in the nineteenth century [vD94].) This technique has flourished since the mid-1960s. Its principal ideas and methods are described in several textbooks. Nevertheless, asymptotic ex­ pansions may be impossible to construct or may fail to simplify the given problem; then numerical approximations are often the only option. The systematic study of numerical methods for singular perturbation problems started somewhat later - in the 1970s. While the research frontier has been steadily pushed back, the exposition of new developments in the analysis of numerical methods has been neglected. Perhaps the only example of a textbook that concentrates on this analysis is [DMS80], which collects various results for ordinary differential equations, but many methods and techniques that are relevant today (especially for partial differential equa­ tions) were developed after 1980.Thus contemporary researchers must comb the literature to acquaint themselves with earlier work. Our purposes in writing this introductory book are twofold. First, we aim to present a structured account of recent ideas in the numerical analysis of singularly perturbed differential equations. Second, this important area has many open problems and we hope that our book will stimulate further investigations.Our choice of topics is inevitably personal and reflects our own main interests.

Authors and Affiliations

  • Institut für Numerische Mathematik, Technische Universität Dresden, Dresden, Germany

    Hans-Görg Roos

  • Department of Mathematics, University College Cork, Cork, Ireland

    Martin Stynes

  • Institut für Analysis und Numerik, Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany

    Lutz Tobiska

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