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An investigation of radial basis function-finite difference (RBF-FD) method for numerical solution of elliptic partial differential equations

  • Mahidol University
  • Ministry of Education

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

The Radial Basis Function (RBF) method has been considered an important meshfree tool for numerical solutions of Partial Differential Equations (PDEs). For various situations, RBF with infinitely differentiable functions can provide accurate results and more flexibility in the geometry of computation domains than traditional methods such as finite difference and finite element methods. However, RBF does not suit large scale problems, and, therefore, a combination of RBF and the finite difference (RBF-FD) method was proposed because of its own strengths not only on feasibility and computational cost, but also on solution accuracy. In this study, we try the RBF-FD method on elliptic PDEs and study the effect of it on such equations with different shape parameters. Most importantly, we study the solution accuracy after additional ghost node strategy, preconditioning strategy, regularization strategy, and floating point arithmetic strategy. We have found more satisfactory accurate solutions in most situations than those from global RBF, except in the preconditioning and regularization strategies.

Original languageEnglish
Article number54
JournalMathematics
Volume5
Issue number4
DOIs
Publication statusPublished - 23 Oct 2017
Externally publishedYes

Keywords

  • Floating point arithmetic
  • Ghost node
  • Numerical partial differential equations (PDEs)
  • Preconditioning
  • Radial basis function-finite difference (RBF-FD) method
  • Regularization

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