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arXiv 2109.09698math.NAcs.NAmath.AP
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基于多元样条的配点法用于偏微分方程数值求解

A Multivariate Spline based Collocation Method for Numerical Solution of Partial Differential Equations

Ming-Jun Lai, Jinsil Lee

AI总结:

本文提出一种基于多元多项式样条的配点法,用于求解泊松方程和非散度形式二阶椭圆型偏微分方程,并通过二维、三维数值实验及与已有方法的比较,证明其高效且精度相当或更优。

摘要:

我们提出一种基于三角剖分或四面体剖分上多元多项式样条的配点法,用于偏微分方程的数值求解。我们首先详细解释该方法在泊松方程中的应用,然后将研究扩展到非散度形式的二阶椭圆型偏微分方程。我们将证明数值解能够很好地逼近精确的偏微分方程解。随后,我们给出大量数值实验结果,以展示该方法在二维和三维情形下的性能。此外,我们与文献\cite{ALW06}和\cite{LW17}中已有的多元样条方法进行了比较,结果表明新方法以更高效的方式产生了相似且有时更精确的近似。

英文摘要:

We propose a collocation method based on multivariate polynomial splines over triangulation or tetrahedralization for the numerical solution of partial differential equations. We start with a detailed explanation of the method for the Poisson equation and then extend the study to the second-order elliptic PDE in non-divergence form. We shall show that the numerical solution can approximate the exact PDE solution very well. Then we present a large amount of numerical experimental results to demonstrate the performance of the method over the 2D and 3D settings. In addition, we present a comparison with the existing multivariate spline methods in \cite{ALW06} and \cite{LW17} to show that the new method produces a similar and sometimes more accurate approximation in a more efficient fashion.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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