时间谐波声散射的非均匀有理B样条和拉格朗日近似:精度和吸收边界条件

IF 1.8 4区 数学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
S. M. Dsouza, T. Khajah, X. Antoine, S. Bordas, S. Natarajan
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引用次数: 9

摘要

摘要本文旨在利用高阶局部吸收边界条件,特别是基于卡普和威尔科克斯远场展开,评估基于拉格朗日的有限元方法和非均匀有理B样条等几何分析的性能。通过观察近似多项式的阶数、自由度、波数和吸收边界条件调谐参数的影响,分析了这两种方法的精度和收敛性。结果表明,与传统的基于拉格朗日的有限元方法相比,无论多项式阶数如何,IGA都能提供更高的每自由度精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non Uniform Rational B-Splines and Lagrange approximations for time-harmonic acoustic scattering: accuracy and absorbing boundary conditions
ABSTRACT The paper aims to evaluate the performance of the Lagrange-based finite element method and the non-uniform rational B-splines isogeometric analysis of time-harmonic acoustic exterior scattering problems using high-order local absorbing boundary conditions, in particular based on the Karp’s and Wilcox’s far-field expansions. The analysis of accuracy and convergence of both methods is achieved by observing the effect of the order of the approximating polynomial, the number of degrees of freedom, the wave number, and the absorbing boundary conditions tuning parameters. It is concluded that, regardless of the polynomial order, IGA provides a higher accuracy per degree of freedom compared to the traditional Lagrange-based finite element method.
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来源期刊
CiteScore
3.80
自引率
5.30%
发文量
7
审稿时长
>12 weeks
期刊介绍: Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems. The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application. MCMDS welcomes original articles on a range of topics including: -methods of modelling and simulation- automation of modelling- qualitative and modular modelling- data-based and learning-based modelling- uncertainties and the effects of modelling errors on system performance- application of modelling to complex real-world systems.
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