半线性抛物线积分微分方程 Serendipity 虚拟元素方法的误差分析

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Yang Xu, Zhenguo Zhou, Jingjun Zhao
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引用次数: 0

摘要

本研究的主要目的是评估偶然性虚拟元素方法在求解具有可变系数的半线性抛物线积分微分方程时的性能。与标准(增强)虚元方法相比,该方法的主要优势在于减少了内动量自由度,从而在使用准插值算子近似非线性项时加快了迭代算法的速度。时间离散化采用后向-欧拉方案。为了与后向-欧拉方案的精度阶数保持一致,积分项使用左矩形正交规则进行近似。在 serendipity 虚拟元素框架内,我们引入了 Ritz-Volterra 投影,并对其逼近特性进行了全面分析。在这一分析的基础上,我们最终为半离散和全离散方案提供了最优的 \(H^1\)-seminorm 和 \(L^2\)-norm 误差估计。最后,我们列举了两个数值实例来说明和验证理论发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Error Analysis of Serendipity Virtual Element Methods for Semilinear Parabolic Integro-Differential Equations

Error Analysis of Serendipity Virtual Element Methods for Semilinear Parabolic Integro-Differential Equations

The main objective of this study is to evaluate the performance of serendipity virtual element methods in solving semilinear parabolic integro-differential equations with variable coefficients. The primary advantage of this method, in comparison to the standard (enhanced) virtual element methods, lies in the reduction of internal-moment degrees of freedom, which can speed up the iterative algorithms when using the quasi-interpolation operators to approximate nonlinear terms. The temporal discretization is obtained with the backward-Euler scheme. To maintain consistency with the accuracy order of the backward-Euler scheme, the integral term is approximated using the left rectangular quadrature rule. Within the serendipity virtual element framework, we introduced a Ritz–Volterra projection and conducted a comprehensive analysis of its approximation properties. Building upon this analysis, we ultimately provided optimal \(H^1\)-seminorm and \(L^2\)-norm error estimates for both the semi-discrete and fully discrete schemes. Finally, two numerical examples that serve to illustrate and validate the theoretical findings are presented.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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