Convergent evolving finite element approximations of boundary evolution under shape gradient flow

IF 2.3 2区 数学 Q1 MATHEMATICS, APPLIED IMA Journal of Numerical Analysis Pub Date : 2023-10-30 DOI:10.1093/imanum/drad080
Wei Gong, Buyang Li, Qiqi Rao
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引用次数: 1

Abstract

As a specific type of shape gradient descent algorithm, shape gradient flow is widely used for shape optimization problems constrained by partial differential equations. In this approach, the constraint partial differential equations could be solved by finite element methods on a domain with a solution-driven evolving boundary. Rigorous analysis for the stability and convergence of such finite element approximations is still missing from the literature due to the complex nonlinear dependence of the boundary evolution on the solution. In this article, rigorous analysis of numerical approximations to the evolution of the boundary in a prototypical shape gradient flow is addressed. First-order convergence in time and $k$th order convergence in space for finite elements of degree $k\geqslant 2$ are proved for a linearly semi-implicit evolving finite element algorithm up to a given time. The theoretical analysis is consistent with the numerical experiments, which also illustrate the effectiveness of the proposed method in simulating two- and three-dimensional boundary evolution under shape gradient flow. The extension of the formulation, algorithm and analysis to more general shape density functions and constraint partial differential equations is also discussed.
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形状梯度流下边界演化的收敛演化有限元逼近
形状梯度流作为一种特殊的形状梯度下降算法,被广泛应用于偏微分方程约束的形状优化问题。在这种方法中,约束偏微分方程可以通过有限元方法在具有解驱动进化边界的域上求解。由于边界演化对解的复杂非线性依赖性,文献中仍然缺少对这种有限元近似的稳定性和收敛性的严格分析。在本文中,对原型形状梯度流中边界演变的数值近似进行了严格的分析。对于给定时间的线性半隐式演化有限元算法,证明了阶为$k\geqslant 2$的有限元在时间上的一阶收敛性和在空间上的$k$th阶收敛性。理论分析与数值实验相一致,也说明了该方法在形状梯度流下模拟二维和三维边界演化的有效性。还讨论了公式、算法和分析对更一般的形状密度函数和约束偏微分方程的扩展。
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
IMA Journal of Numerical Analysis
IMA Journal of Numerical Analysis 数学-应用数学
CiteScore
5.30
自引率
4.80%
发文量
79
审稿时长
6-12 weeks
期刊介绍: The IMA Journal of Numerical Analysis (IMAJNA) publishes original contributions to all fields of numerical analysis; articles will be accepted which treat the theory, development or use of practical algorithms and interactions between these aspects. Occasional survey articles are also published.
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