A shape-parameterized RBF-partition of unity technique for PDEs

IF 2.9 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics Letters Pub Date : 2025-01-10 DOI:10.1016/j.aml.2024.109453
Roberto Cavoretto, Alessandra De Rossi, Adeeba Haider
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Abstract

In this paper, we study a direct discretization technique based on a radial basis function partition of unity (RBF-PU) method, which is built to numerically solve partial differential equations (PDEs). Unlike commonly used shape parameter free polyharmonic spline kernels, in this work we focus on local radial kernels depending on the shape parameter associated with the basis functions. The resulting scheme generally leads to more flexibility and accuracy, in particular when a polynomial term is added to the local RBF expansion. To emphasize the benefits deriving from use of the direct approach, we also compare it with the RBF finite difference (RBF-FD) method both in terms of computational efficiency and accuracy. Numerical results show the method performance by solving some elliptic PDE problems.
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pde的形状参数化rbf分割技术
本文研究了一种基于径向基函数单位划分(RBF-PU)方法的直接离散化技术,该方法用于数值求解偏微分方程(PDEs)。与常用的无形状参数的多谐样条核不同,本文主要研究与基函数相关的形状参数的局部径向核。所得到的方案通常会带来更大的灵活性和准确性,特别是当将多项式项添加到局部RBF展开中时。为了强调使用直接方法的好处,我们还将其与RBF有限差分(RBF- fd)方法在计算效率和精度方面进行了比较。通过对椭圆型偏微分方程的求解,验证了该方法的有效性。
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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来源期刊
Applied Mathematics Letters
Applied Mathematics Letters 数学-应用数学
CiteScore
7.70
自引率
5.40%
发文量
347
审稿时长
10 days
期刊介绍: The purpose of Applied Mathematics Letters is to provide a means of rapid publication for important but brief applied mathematical papers. The brief descriptions of any work involving a novel application or utilization of mathematics, or a development in the methodology of applied mathematics is a potential contribution for this journal. This journal''s focus is on applied mathematics topics based on differential equations and linear algebra. Priority will be given to submissions that are likely to appeal to a wide audience.
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