4.5 Article

A Dimension-Splitting Variational Multiscale Element-Free Galerkin Method for Three-Dimensional Singularly Perturbed Convection-Diffusion Problems

Journal

CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
Volume 135, Issue 1, Pages 341-356

Publisher

TECH SCIENCE PRESS
DOI: 10.32604/cmes.2022.023140

Keywords

Dimension-splitting multiscale interpolating element-free Galerkin (DS-VMIEFG) method; interpolating variational multiscale element-free Galerkin (VMIEFG) method; dimension splitting method; singularly perturbed convection-diffusion problems

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In this paper, a new method combining dimensional splitting and multiscale interpolating element-free Galerkin is proposed for solving three-dimensional singular perturbed convection-diffusion problems. By decomposing the problem into a series of 2D problems and constructing discrete equations using least squares method, the method effectively solves the 3D problem with high computational stability.
By introducing the dimensional splitting (DS) method into the multiscale interpolating element-free Galerkin (VMIEFG) method, a dimension-splitting multiscale interpolating element-free Galerkin (DS-VMIEFG) method is proposed for three-dimensional (3D) singular perturbed convection-diffusion (SPCD) problems. In the DSVMIEFG method, the 3D problem is decomposed into a series of 2D problems by the DS method, and the discrete equations on the 2D splitting surface are obtained by the VMIEFG method. The improved interpolation-type moving least squares (IIMLS) method is used to construct shape functions in the weak form and to combine 2D discrete equations into a global system of discrete equations for the three-dimensional SPCD problems. The solved numerical example verifies the effectiveness of the method in this paper for the 3D SPCD problems. The numerical solution will gradually converge to the analytical solution with the increase in the number of nodes. For extremely small singular diffusion coefficients, the numerical solution will avoid numerical oscillation and has high computational stability.

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