圆扇形上拉普拉斯特征值问题的等时计量分析:正则特性和分级网格

IF 2.9 2区 数学 Q1 MATHEMATICS, APPLIED Computers & Mathematics with Applications Pub Date : 2024-10-07 DOI:10.1016/j.camwa.2024.09.018
Thomas Apel, Philipp Zilk
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引用次数: 0

摘要

圆形扇形上的拉普拉斯特征值问题具有角奇异性特征函数。标准方法可能会产生次优近似结果。为了解决这个问题,本文提出了一种新的数值算法,通过使用单补丁分级网格细化方案来增强标准等距几何分析。数值测试表明,特征值和特征函数的收敛速度都达到了最佳水平。此外,结果表明,对于拉普拉斯频谱的下半部分,平滑样条曲线与 C0 连续样条曲线相比,具有更优越的近似常数。这是将之前在矩形域上发现的平滑样条曲线的优异频谱逼近特性扩展到圆形扇形域的结果。此外,分级网格在精确逼近有限数量的特征值方面被证明具有特别的优势。最后,介绍了一种分层网格结构,以避免物理域中的各向异性元素,并省略奇点附近的冗余自由度。数值结果验证了分层网格分级在模拟低规则性和高规则性特征函数方面的有效性。
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Isogeometric analysis of the Laplace eigenvalue problem on circular sectors: Regularity properties and graded meshes
The Laplace eigenvalue problem on circular sectors has eigenfunctions with corner singularities. Standard methods may produce suboptimal approximation results. To address this issue, a novel numerical algorithm that enhances standard isogeometric analysis is proposed in this paper by using a single-patch graded mesh refinement scheme. Numerical tests demonstrate optimal convergence rates for both the eigenvalues and eigenfunctions. Furthermore, the results show that smooth splines possess a superior approximation constant compared to their C0-continuous counterparts for the lower part of the Laplace spectrum. This is an extension of previous findings about excellent spectral approximation properties of smooth splines on rectangular domains to circular sectors. In addition, graded meshes prove to be particularly advantageous for an accurate approximation of a limited number of eigenvalues. Finally, a hierarchical mesh structure is presented to avoid anisotropic elements in the physical domain and to omit redundant degrees of freedom in the vicinity of the singularity. Numerical results validate the effectiveness of hierarchical mesh grading for simulating eigenfunctions of low and high regularity.
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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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