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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.

Computer Modeling in Engineering & Sciences 2007, 20(1), 35-42. https://doi.org/10.3970/cmes.2007.020.035

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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APA Style
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. Computer Modeling in Engineering & Sciences, 20(1), 35-42. https://doi.org/10.3970/cmes.2007.020.035
Vancouver Style
Lee C, Im C, Jung H, Kim H, Kim DW. A posteriori error estimation and adaptive node refinement for fast moving least square reproducing kernel (FMLSRK) method. Comput Model Eng Sci. 2007;20(1):35-42 https://doi.org/10.3970/cmes.2007.020.035
IEEE Style
C. Lee, C. Im, H. Jung, H. Kim, and D.W. Kim, “A Posteriori Error Estimation and Adaptive Node Refinement for Fast Moving Least Square Reproducing Kernel (FMLSRK) Method,” Comput. Model. Eng. Sci., vol. 20, no. 1, pp. 35-42, 2007. https://doi.org/10.3970/cmes.2007.020.035



cc Copyright © 2007 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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