A Posteriori Error Estimation and Adaptive Node Refinement for Fast Moving Least Square Reproducing Kernel (FMLSRK) Method
Chany Lee1, Chang-Hwan Im2, Hyun-Kyo Jung3, Hong-Kyu Kim4, Do Wan Kim5
Seoul National University, Seoul, Korea.
Corresponding author. Dept. Biomedical Eng., Yonsei University, Wonju, Korea.
Seoul National University, Seoul, Korea.
Korea Electrotechnology Research Institute, Changwon,Korea.
Hanyang University, Ansan, Korea.
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.
Lee, C., Im, C., Jung, H., Kim, H., Kim, D. W. (2007). A Posteriori Error Estimation and Adaptive Node Refinement for Fast Moving Least Square Reproducing Kernel (FMLSRK) Method. CMES-Computer Modeling in Engineering & Sciences, 20(1), 35–42. https://doi.org/10.3970/cmes.2007.020.035
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