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Iterative Splitting Methods For Differential Equations

Iterative Splitting Methods For Differential Equations

Iterative Splitting Methods For Differential Equations
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Iterative Splitting Methods For Differential Equations Paperback - 2017

by Geiser, Juergen,

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Details

  • Title Iterative Splitting Methods For Differential Equations
  • Author Geiser, Juergen,
  • Binding Paperback
  • Condition New
  • Pages 320
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date 2017-05-31
  • Illustrated Yes
  • Features Bibliography, Illustrated
  • Bookseller's Inventory # 29503289
  • ISBN 9781138111905 / 1138111902
  • Weight 1.01 lbs (0.46 kg)
  • Dimensions 9.21 x 6.14 x 0.69 in (23.39 x 15.60 x 1.75 cm)
  • Themes
    • Aspects (Academic): Science/Technology Aspects
  • Category Mathematics
  • Dewey Decimal Code 518.26
  • Quantity available 5

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From the publisher

Iterative Splitting Methods for Differential Equations explains how to solve evolution equations via novel iterative-based splitting methods that efficiently use computational and memory resources. It focuses on systems of parabolic and hyperbolic equations, including convection-diffusion-reaction equations, heat equations, and wave equations.

In the theoretical part of the book, the author discusses the main theorems and results of the stability and consistency analysis for ordinary differential equations. He then presents extensions of the iterative splitting methods to partial differential equations and spatial- and time-dependent differential equations.

The practical part of the text applies the methods to benchmark and real-life problems, such as waste disposal, elastics wave propagation, and complex flow phenomena. The book also examines the benefits of equation decomposition. It concludes with a discussion on several useful software packages, including r3t and FIDOS.

Covering a wide range of theoretical and practical issues in multiphysics and multiscale problems, this book explores the benefits of using iterative splitting schemes to solve physical problems. It illustrates how iterative operator splitting methods are excellent decomposition methods for obtaining higher-order accuracy.

About the author

Juergen Geiser is a researcher in the Department of Mathematics at the Humboldt-University of Berlin. His research interests include numerical and computational analysis, partial differential equations, decomposition and discretization methods for hyperbolic and parabolic equations, optimization, scientific computing, and interface analysis.

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