A Posteriori Error Estimation and Adaptive Node Refinement for Fast Moving Least Square Reproducing Kernel (FMLSRK) Method
Chany Lee; Chang-Hwan Im; Hyun-Kyo Jung; Hong-Kyu Kim; and Do Wan Kim

Source CMES: Computer Modeling in Engineering & Sciences, Vol. 20, No. 1, pp. 35-42, 2007
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Keywords Adaptive node refinement, electrostatics, error estimation, fast moving least square reproducing kernel (FMLSRK) method, meshless methods.
Abstract In the present study, a residual-based a posteriori error estimation for a kind of meshless method, called fast moving least square reproducing kernel (FMLSRK) method is proposed. The proposed error estimation technique does not require any integration cells in evaluating error norm but recovers the exact solutions in a virtual area defined by a dilation parameter of FMLSRK and node density. The proposed technique was tested on typical electrostatic problems with gird or random node sets and the simulation results show that the proposed error estimation technique can be applied to adaptive node refinement process for more efficient meshless analysis of electromagnetic field.
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