ADAPTIVE RBF-FD METHOD FOR POISSON’S EQUATION

J. Slak, G. Kosec
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引用次数: 3

Abstract

Solutions to many physical problems governed by partial differential equations (PDEs) often vary significantly in magnitude throughout the problem domain. Although in some special cases the areas with high error are known in advance, in general the error distribution is unknown beforehand. Adaptive techniques for solving PDEs are a standard way of dealing with this problem, where problematic regions are iteratively refined. A step further is automatic adaptivity, where problematic regions are chosen automatically using an error indicator and then refined, until a certain error threshold is reached. In this paper, we apply a recently published technique for automatic adaptivity for strong form meshless methods and solve the Poisson equation and its generalisations, using the popular RBF-FD method. Both 2D and 3D cases are considered, comparing uniform and adaptive refinement, illustrating the advantages of fully automatic adaptivity.
泊松方程的自适应rbf-fd方法
许多由偏微分方程(PDEs)控制的物理问题的解在整个问题域的大小通常有很大的变化。虽然在一些特殊情况下,高误差区域是事先已知的,但一般情况下,误差分布是事先未知的。求解偏微分方程的自适应技术是处理该问题的标准方法,其中有问题的区域被迭代地细化。更进一步是自动适应性,其中使用错误指示器自动选择有问题的区域,然后进行细化,直到达到某个错误阈值。在本文中,我们应用了最近发表的一种强形式无网格方法的自动自适应技术,并使用流行的RBF-FD方法求解泊松方程及其推广。同时考虑了二维和三维两种情况,比较了均匀化和自适应细化,说明了全自动自适应的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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