Impedance Sensitivity Analysis Based on Discontinuous Isogeometric Boundary Element Method in Automotive Acoustics

IF 2.6 3区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computing and Information Science in Engineering Pub Date : 2023-05-16 DOI:10.1115/1.4062544
Yi Sun, Liping Xie, Chihua Lu, Zhien Liu, Wan Chen, Xiaolong Li
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Abstract

Acoustic sensitivity analysis is an essential technique to determine the direction of structural-acoustic optimization by evaluating the gradient of the objective functions with respect to the design variables. However, acoustic sensitivity analysis with respect to acoustic impedance, which is an important parameter representing the interior absorbent material in automotive acoustics, is lacking in the study. Moreover, acoustic sensitivity analysis implemented with conventional numerical methods is time and effort-consuming in automotive acoustics, due to the large-scale mesh generation. In this work, the impedance sensitivity analysis for automotive acoustics based on the discontinuous isogeometric boundary element method is presented. The regularized boundary integral equation with impedance boundary conditions is established, then the sensitivity is derived by differentiating the boundary integral equation. The efficiency of the proposed method is improved by employing the parallel technique and generalized minimal residual solver. A long duct example with an analytical solution validates the accuracy of the proposed method, and an automotive passenger compartment subjecting to impedance boundary conditions illustrates that the computing time of the proposed method is one order of magnitude less than the conventional method. This work presents an easily implementable and efficient tool to investigate acoustic sensitivity with respect to impedance, showing great potential in the application of automotive acoustics.
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基于不连续等几何边界元法的汽车声学阻抗灵敏度分析
声灵敏度分析是通过评价目标函数相对于设计变量的梯度来确定结构声优化方向的一项重要技术。然而,作为汽车声学中代表车内吸声材料的重要参数,声阻抗的声灵敏度分析在研究中缺乏。此外,在汽车声学中,由于需要进行大规模网格生成,采用传统数值方法进行声灵敏度分析费时费力。本文提出了基于不连续等几何边界元法的汽车声学阻抗灵敏度分析方法。建立了带阻抗边界条件的正则化边界积分方程,通过对边界积分方程求导得到了灵敏度。采用并行技术和广义最小残差求解器,提高了算法的效率。长风道算例的解析解验证了所提方法的准确性,一个具有阻抗边界条件的汽车客舱实例表明,所提方法的计算时间比传统方法少一个数量级。这项工作提供了一种易于实现和有效的工具来研究相对于阻抗的声灵敏度,在汽车声学的应用中显示出巨大的潜力。
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来源期刊
CiteScore
6.30
自引率
12.90%
发文量
100
审稿时长
6 months
期刊介绍: The ASME Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to Algorithms, Computational Methods, Computing Infrastructure, Computer-Interpretable Representations, Human-Computer Interfaces, Information Science, and/or System Architectures that aim to improve some aspect of product and system lifecycle (e.g., design, manufacturing, operation, maintenance, disposal, recycling etc.). Applications considered in JCISE manuscripts should be relevant to the mechanical engineering discipline. Papers can be focused on fundamental research leading to new methods, or adaptation of existing methods for new applications. Scope: Advanced Computing Infrastructure; Artificial Intelligence; Big Data and Analytics; Collaborative Design; Computer Aided Design; Computer Aided Engineering; Computer Aided Manufacturing; Computational Foundations for Additive Manufacturing; Computational Foundations for Engineering Optimization; Computational Geometry; Computational Metrology; Computational Synthesis; Conceptual Design; Cybermanufacturing; Cyber Physical Security for Factories; Cyber Physical System Design and Operation; Data-Driven Engineering Applications; Engineering Informatics; Geometric Reasoning; GPU Computing for Design and Manufacturing; Human Computer Interfaces/Interactions; Industrial Internet of Things; Knowledge Engineering; Information Management; Inverse Methods for Engineering Applications; Machine Learning for Engineering Applications; Manufacturing Planning; Manufacturing Automation; Model-based Systems Engineering; Multiphysics Modeling and Simulation; Multiscale Modeling and Simulation; Multidisciplinary Optimization; Physics-Based Simulations; Process Modeling for Engineering Applications; Qualification, Verification and Validation of Computational Models; Symbolic Computing for Engineering Applications; Tolerance Modeling; Topology and Shape Optimization; Virtual and Augmented Reality Environments; Virtual Prototyping
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