基于强-弱耦合算法的改进无网格电场计算方法

Hongzhi Du, Tong Wu, Yuan Fang, Shi Long, Youyuan Wang
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引用次数: 0

摘要

传统的静电场数值计算方法有有限元法、有限差分法等。由于网格划分耗时,无网格法逐渐被学者们用于物理场分析。目前,无网格局部Petrov-Galerkin法和无网格弱-强法在各个领域都有报道,具有较好的精度和广泛的适用性。提出了一种改进的基于测试函数的无网格强-弱耦合方法。利用离散节点表示问题域和边界,利用移动最小二乘法构造形状函数。对于局部积分域不与全局导数边界相交的节点,采用无网格强形式法构造基本方程。对于其他节点,采用无网格局部弱公式法。用指数函数作为弱公式表达式的检验函数。通过改变指数函数的系数,控制测试函数的形状,减小影响域大小变化对计算精度的影响。实例分析表明,该方法比传统的无网格方法具有更高的精度和更好的收敛效果。该方法在处理电数值计算时精度高,计算效率高,收敛性强。与传统方法相比,该方法具有更好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved meshless method based on strong-weak coupling algorithm for electric field calculation
The traditional numerical calculation methods of electrostatic field include finite element method, finite difference method and so on. Due to the time-consuming meshing, the meshless method is gradually used by scholars for physical field analysis. At present, the meshless local Petrov-Galerkin method and the meshfree weak-strong method have been reported in various fields with their better accuracy and wide applicability. This paper presents an improved meshless strong-weak coupling method based on test function. The scattered nodes are used to represent the problem domain and boundary, and the shape function is constructed by the moving least square method. For the nodes where the local integration domain does not intersect the global derivative boundary, the meshless strong form method is used to construct the basic equation. For other nodes, the meshless local weak formula method is used. The exponential function is used as a test function for weak formula expressions. By changing the coefficient of the exponential function, the shape of the test function is controlled, and the influence of the change in the size of the influence domain on the calculation accuracy is reduced. The case analysis shows that this method has higher accuracy and better convergence effect than the traditional meshless method. The proposed method has high precision and computational efficiency in processing electrical numerical calculations, and has strong astringency. This method has better application prospects than traditional methods.
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