用广义 nth 阶扰动边界元方法量化三维声学形状敏感性的不确定性

IF 6.9 1区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Leilei Chen , Ruijin Huo , Haojie Lian , Bo Yu , Mengxi Zhang , Sundararajan Natarajan , Stéphane P.A. Bordas
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引用次数: 0

摘要

本文提出了一种基于扰动的新方法,用于声场及其形状敏感性的不确定性量化。在这项工作中,冲击声波的频率被视为随机变量。通过对声学边界积分方程进行泰勒级数展开,得到声学状态函数相对于频率的 n 次导数。通过直接微分声学边界积分方程中的形状设计变量来获得声学形状灵敏度,然后利用泰勒级数展开求得形状灵敏度相对于随机频率的 n 次导数。基于 nth 阶扰动理论,可以评估声学状态函数的统计特性及其形状敏感性。通过数值示例证明了所提算法的有效性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uncertainty quantification of 3D acoustic shape sensitivities with generalized nth-order perturbation boundary element methods
This paper presents a novel perburbation-based method for uncertainty quantification of acoustic fields and their shape sensitivities. In this work, the frequencies of impinging acoustic waves are regarded as random variables. Taylor’s series expansions of acoustic boundary integral equations are derived to obtain nth-order derivatives of acoustic state functions with respect to frequencies. Acoustic shape sensitivity is obtained by directly differentiating acoustic boundary integral equation with respect to shape design variables, and then the nth-order derivatives of shape sensitivity with respect to random frequencies are formulated with Taylor’s series expansions. Based on the nth-order perturbation theory, the statistical characteristics of acoustic state functions and their shape sensitivities can be evaluated. Numerical examples are presented to demonstrate the validity and effectiveness of the proposed algorithm.
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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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