时间分数型PIDEs的非均匀\(\alpha \) -鲁棒IMEX-L1混合有限元分析

IF 2.1 3区 数学 Q2 MATHEMATICS, APPLIED
Lok Pati Tripathi, Aditi Tomar, Amiya K. Pani
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引用次数: 0

摘要

研究了一类具有时空相关系数和非自伴随椭圆部分的时间分数阶偏积分微分方程的非一致隐显L1混合有限元法。该方法将时间变量上的梯度网格IMEX-L1方法与空间变量上的混合有限元方法相结合。研究的重点是分析稳定性结果,并建立最优误差估计,高达一个对数因子,为解决方案和通量在\(L^2\) -范数当初始数据\(u_0\in H_0^1(\Omega )\cap H^2(\Omega )\)。此外,对二维问题导出了\(L^\infty \) -范数的误差估计。本文导出的所有估计和界为\(\alpha \rightarrow 1^{-}\),其中\(\alpha \)为卡普托分数阶导数的阶数。最后,本文最后进行的几个数值实验结果证实了我们的理论发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On a non-uniform \(\alpha \)-robust IMEX-L1 mixed FEM for time-fractional PIDEs

A non-uniform implicit-explicit L1 mixed finite element method (IMEX-L1-MFEM) is investigated for a class of time-fractional partial integro-differential equations (PIDEs) with space-time-dependent coefficients and non-self-adjoint elliptic part. The proposed fully discrete method combines an IMEX-L1 method on a graded mesh in the temporal variable with a mixed finite element method in spatial variables. The focus of the study is to analyze stability results and to establish optimal error estimates, up to a logarithmic factor, for both the solution and the flux in \(L^2\)-norm when the initial data \(u_0\in H_0^1(\Omega )\cap H^2(\Omega )\). Additionally, an error estimate in \(L^\infty \)-norm is derived for 2D problems. All the derived estimates and bounds in this article remain valid as \(\alpha \rightarrow 1^{-}\), where \(\alpha \) is the order of the Caputo fractional derivative. Finally, the results of several numerical experiments conducted at the end of this paper are confirming our theoretical findings.

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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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