Numerical simulation of nonlinear fractional integro-differential equations on two-dimensional regular and irregular domains: RBF partition of unity

IF 2.9 2区 数学 Q1 MATHEMATICS, APPLIED Computers & Mathematics with Applications Pub Date : 2025-01-08 DOI:10.1016/j.camwa.2024.12.019
M. Fardi, B. Azarnavid, S. Mohammadi
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Abstract

In this article, we introduce a numerical method that combines local radial basis functions partition of unity with backward differentiation formula to efficiently solve linear and nonlinear fractional integro-differential equations on two-dimensional regular and irregular domains. We derive the time-discretized formulation using the backward difference formula. The meshless radial basis function method, particularly the radial basis function partition of unity method, offers advantages such as flexibility, accuracy, ease of implementation, adaptive refinement, and efficient parallelization. We apply the radial basis function partition of unity method to spatially discretize the problem using the scaled Lagrangian form of polyharmonic splines as approximation bases. Numerical simulations demonstrate the efficacy of our method in solving linear and nonlinear fractional integro-differential equations with complex domains and smooth and nonsmooth initial conditions. Comparative analysis confirms the superior performance of our proposed method.
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二维正则和不规则区域上非线性分数阶积分微分方程的数值模拟:单位的RBF划分
本文介绍了一种将局部径向基函数的单位划分与后向微分公式相结合的数值方法,有效地求解二维正则和不规则域上的线性和非线性分数阶积分微分方程。我们利用后向差分公式推导出时间离散公式。无网格径向基函数法,特别是单元法的径向基函数划分,具有灵活、准确、易于实现、自适应细化和高效并行化等优点。以多谐样条的缩放拉格朗日形式为近似基,采用统一的径向基函数划分方法对问题进行空间离散化。数值模拟证明了该方法在求解具有复杂域、光滑和非光滑初始条件的线性和非线性分数阶积分微分方程方面的有效性。对比分析证实了该方法的优越性。
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来源期刊
Computers & Mathematics with Applications
Computers & Mathematics with Applications 工程技术-计算机:跨学科应用
CiteScore
5.10
自引率
10.30%
发文量
396
审稿时长
9.9 weeks
期刊介绍: Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).
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