Meshfree Methods for Partial Differential Equations

  • Michael Griebel
  • Marc Alexander Schweitzer

Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE, volume 26)

Table of contents

  1. Front Matter
    Pages I-IX
  2. Ted Belytschko, Giulio Ventura, Jingxiao Xu
    Pages 37-50
  3. Steinar Børve, Marianne Omang, Jan Trulsen
    Pages 51-62
  4. Jason Frank, Georg Gottwald, Sebastian Reich
    Pages 131-142
  5. Michael Griebel, Marc Alexander Schweitzer
    Pages 161-192
  6. Weimin Han, Xueping Meng
    Pages 193-210
  7. Michael Junk
    Pages 223-238
  8. Hongsheng Lu, Jiun-Shyan Chen
    Pages 251-265
  9. Joseph J. Monaghan
    Pages 281-290

About these proceedings

Introduction

Meshfree methods for the solution of partial differential equations gained much attention in recent years, not only in the engineering but also in the mathematics community. One of the reasons for this development is the fact that meshfree discretizations and particle models ar often better suited to cope with geometric changes of the domain of interest, e.g. free surfaces and large deformations, than classical discretization techniques such as finite differences, finite elements or finite volumes. Another obvious advantage of meshfree discretization is their independence of a mesh so that the costs of mesh generation are eliminated. Also, the treatment of time-dependent PDE from a Lagrangian point of view and the coupling of particle models. The coupling of particle models and continuous models gained enormous interest in recent years from a theoretical as well as from a practial point of view. This volume consists of articles which address the different meshfree methods (SPH, PUM, GFEM, EFGM, RKPM etc.) and their application in applied mathematics, physics and engineering.

Keywords

Regression Simulation differential equation element-free Galerkin methodse engineering applications finite element method finite elements meshfree discretizations modeling partial differential equations partition of united method reproducing kernel particle methods smoothed particle hydrodynamics stability stochastic particle methods

Editors and affiliations

  • Michael Griebel
    • 1
  • Marc Alexander Schweitzer
    • 1
  1. 1.Institut für Angewandte MathematikUniversität BonnBonnGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-56103-0
  • Copyright Information Springer-Verlag Berlin Heidelberg 2003
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-43891-5
  • Online ISBN 978-3-642-56103-0
  • Series Print ISSN 1439-7358
  • About this book