2000
DOI: 10.1007/s004660000203
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Meshless local Petrov-Galerkin (MLPG) method in combination with finite element and boundary element approaches

Abstract: The meshless local Petrov±Galerkin (MLPG) method is an effective truly meshless method for solving partial differential equations using moving least squares (MLS) interpolants. It is, however, computationally expensive for some problems. A coupled MLPG/®nite element (FE) method and a coupled MLPG/boundary element (BE) method are proposed in this paper to improve the solution ef®ciency. A procedure is developed for the coupled MLPG/FE method and the coupled MLPG/BE method so that the continuity and compatibilit… Show more

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Cited by 97 publications
(39 citation statements)
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“…The unknown variable u in this LSWF is approximated by the nodal shape functions (10). To obtain the discrete equations from the LSWF (22), the RBF interpolation (9) is adopted to approximate the trial function u.…”
Section: Discretization and Numerical Implementationmentioning
confidence: 99%
“…The unknown variable u in this LSWF is approximated by the nodal shape functions (10). To obtain the discrete equations from the LSWF (22), the RBF interpolation (9) is adopted to approximate the trial function u.…”
Section: Discretization and Numerical Implementationmentioning
confidence: 99%
“…The MLPG method has been successfully used in analyses of solids Zhu, 1998, 2000;Atluri et al, 1999;Gu and Liu, 2001b, c). In addition, the MLPG method has also been combined with FEM and BEM (Liu and Gu, 2000b).…”
Section: Introductionmentioning
confidence: 99%
“…Hegen [21] developed another coupled EFG/FEM technique based on the modified variational principle. Gu and Liu developed a group of coupled methods including EFG/BEM and MLPG/FEM/BEM [17][18][19]27,28] based on the FE interface element technique or the modified variational principle. In these coupled methods, the MM is used in a sub-domain where the MM is required to obtain high accuracy, and FEM or BEM is employed in other sub-domains where FEM or BEM is required to improve the computational efficiency.…”
Section: Introductionmentioning
confidence: 99%