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The Improved Element-Free Galerkin Method for Anisotropic Steady-State Heat Conduction Problems

Heng Cheng1, Zebin Xing1, Miaojuan Peng2,*

1 School of Applied Science, Taiyuan University of Science and Technology, Taiyuan, 030024, China
2 Department of Civil Engineering, School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200444, China

* Corresponding Author: Miaojuan Peng. Email: email

(This article belongs to the Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)

Computer Modeling in Engineering & Sciences 2022, 132(3), 945-964. https://doi.org/10.32604/cmes.2022.020755

Abstract

In this paper, we considered the improved element-free Galerkin (IEFG) method for solving 2D anisotropic steady-state heat conduction problems. The improved moving least-squares (IMLS) approximation is used to establish the trial function, and the penalty method is applied to enforce the boundary conditions, thus the final discretized equations of the IEFG method for anisotropic steady-state heat conduction problems can be obtained by combining with the corresponding Galerkin weak form. The influences of node distribution, weight functions, scale parameters and penalty factors on the computational accuracy of the IEFG method are analyzed respectively, and these numerical solutions show that less computational resources are spent when using the IEFG method.

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APA Style
Cheng, H., Xing, Z., Peng, M. (2022). The improved element-free galerkin method for anisotropic steady-state heat conduction problems. Computer Modeling in Engineering & Sciences, 132(3), 945-964. https://doi.org/10.32604/cmes.2022.020755
Vancouver Style
Cheng H, Xing Z, Peng M. The improved element-free galerkin method for anisotropic steady-state heat conduction problems. Comput Model Eng Sci. 2022;132(3):945-964 https://doi.org/10.32604/cmes.2022.020755
IEEE Style
H. Cheng, Z. Xing, and M. Peng "The Improved Element-Free Galerkin Method for Anisotropic Steady-State Heat Conduction Problems," Comput. Model. Eng. Sci., vol. 132, no. 3, pp. 945-964. 2022. https://doi.org/10.32604/cmes.2022.020755



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