声波问题等几何离散化的重叠Schwarz预条件

IF 7.3 1区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Elena Zampieri , Simone Scacchi , Luca F. Pavarino
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引用次数: 0

摘要

本文的目的是构造和分析具有吸收边界条件的声波方程等几何离散化的两级重叠加性Schwarz (OAS)预条件。空间离散采用配点法和伽辽金等几何方法,时间推进采用Newmark隐式格式。在每个时间步解的线性系统是病态的,特别是在高度正则样条的情况下,因此它们的解需要使用有效的预调节器。两级OAS求解方法包括将域划分为重叠的子域,求解每个子域上的独立局部问题和与子域网格相关的附加粗问题。几个二维数值结果验证了我们的理论估计,显示了所提出算法的可扩展性和准最优性。我们还研究了OAS预条件对样条多项式度、样条正则性和重叠参数的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overlapping Schwarz preconditioners for isogeometric discretizations of acoustic wave problems
The aim of this work is to construct and analyze two-level overlapping additive Schwarz (OAS) preconditioners for isogeometric discretizations of the acoustic wave equation with absorbing boundary conditions. Both Collocation and Galerkin isogeometric methods are employed for space discretization, while time advancing is performed by means of a Newmark implicit scheme. The linear systems to be solved at each time step are ill conditioned, especially in case of highly regular splines, thus their solution requires the use of effective preconditioners. Two-level OAS solvers consist of partitioning the domain into overlapping subdomains, solving independent local problems on each subdomain and an additional coarse problem associated with the subdomain mesh. Several two-dimensional numerical results validate our theoretical estimates, showing the scalability and quasi-optimality of the algorithms proposed. We also investigate numerically the robustness of the OAS preconditioners with respect to the spline polynomial degree, the spline regularity and the overlap parameter.
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来源期刊
CiteScore
12.70
自引率
15.30%
发文量
719
审稿时长
44 days
期刊介绍: Computer Methods in Applied Mechanics and Engineering stands as a cornerstone in the realm of computational science and engineering. With a history spanning over five decades, the journal has been a key platform for disseminating papers on advanced mathematical modeling and numerical solutions. Interdisciplinary in nature, these contributions encompass mechanics, mathematics, computer science, and various scientific disciplines. The journal welcomes a broad range of computational methods addressing the simulation, analysis, and design of complex physical problems, making it a vital resource for researchers in the field.
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