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Mohsen Esmaeilbeigi

Mohsen Esmaeilbeigi

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Mathematical Sciences and Statistics
Address: Malayer University
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Research

Title
A shift-adaptive meshfree method for solving a class of initial-boundary value problems with moving boundaries in one-dimensional domain
Type
JournalPaper
Keywords
meshless method;moving boundaries;multiquadric;partial differential equation;radial basis function collocation;shifted node adaptive;stability analysis
Year
2016
Journal NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS
DOI
Researchers Mohsen Esmaeilbeigi

Abstract

A new shift-adaptive meshfree method for solving a class of time-dependent partial differential equations (PDEs) in a bounded domain (one-dimensional domain) with moving boundaries and nonhomogeneous boundary conditions is introduced. The radial basis function (RBF) collocation method is combined with the finite difference scheme, because, unlike with Kansa's method, nonlinear PDEs can be converted to a system of linear equations. The grid-free property of the RBF method is exploited, and a new adaptive algorithm is used to choose the location of the collocation points in the first time step only. In fact, instead of applying the adaptive algorithm on the entire domain of the problem (like with other existing adaptive algorithms), the new adaptive algorithm can be applied only on time steps. Furthermore, because of the radial property of the RBFs, the new adaptive strategy is applied only on the first time step; in the other time steps, the adaptive nodes (obtained in the first time step) are shifted. Thus, only one small system of linear equations must be solved (by LU decomposition method) rather than a large linear or nonlinear system of equations as in Kansa's method (adaptive strategy applied to entire domain), or a large number of small linear systems of equations in the adaptive strategy on each time step. This saves a lot in time and memory usage. Also, Stability analysis is obtained for our scheme, using Von Neumann stability analysis method. Results show that the new method is capable of reducing the number of nodes in the grid without compromising the accuracy of the solution, and the adaptive grading scheme is effective in localizing oscillations due to sharp gradients or discontinuities in the solution. The efficiency and effectiveness of the proposed procedure is examined by adaptively solving two difficult benchmark problems, including a regularized long-wave equation and a Korteweg-de Vries problem.