Reproducing Kernel Particle Method for Solving Partial Differential Equations

  • Jiun Shyan Chen
  • , Wing Kam Liu
  • , Yanping Lian
  • , Miguel A. Bessa
  • , Michael C. Hillman
  • , Sheng Wei Chi

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

13 Citations (Scopus)

Abstract

This chapter gives a state of the art review of the weak-form- and strong-form-based reproducing kernel particle method (RKPM). The construction of the continuous and discrete reproducing kernel (RK) approximations and their approximation properties are first presented. Recent developments and their connection to other meshfree methods, as well as an overview of the inherent multiresolution capabilities of the RKPM, are then given. The Galerkin-based method is discussed in detail, along with several recent advances in quadrature and stability. A review of strong form collocation with RK approximation as well as implicit gradient enhancement is presented. Formulations for large deformation and contact problems for which the RKPM is particularly well suited are also discussed.

Original languageEnglish
Title of host publicationEncyclopedia of Computational Mechanics
Publisherwiley
Pages1-44
Number of pages44
ISBN (Electronic)9781119176817
ISBN (Print)9781119003793
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes

Keywords

  • collocation method
  • meshfree methods
  • multiresolution analysis
  • peridynamics
  • quadrature rules
  • rank stability
  • reproducing kernel approximation
  • reproducing kernel particle method
  • variational consistency

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