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Structural and Multidisciplinary Optimization

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14.02.2017 | RESEARCH PAPER

Design of absorbing material distribution for sound barrier using topology optimization

verfasst von: Wenchang Zhao, Leilei Chen, Changjun Zheng, Cheng Liu, Haibo Chen

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 2/2017

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Abstract

A topology optimization approach based on the boundary element method (BEM) and the optimality criteria (OC) method is proposed for the optimal design of sound absorbing material distribution within sound barrier structures. The acoustical effect of the absorbing material is simplified as the acoustical impedance boundary condition. Based on the solid isotropic material with penalization (SIMP) method, a topology optimization model is established by selecting the densities of absorbing material elements as design variables, volumes of absorbing material as constraints, and the minimization of sound pressure at reference surface as design objective. A smoothed Heaviside-like function is proposed to help the SIMP method to obtain a clear 0–1 distribution. The BEM is applied for acoustic analysis and the sensitivities with respect to design variables are obtained by the direct differentiation method. The Burton–Miller formulation is used to overcome the fictitious eigen-frequency problem for exterior boundary-value problems. A relaxed form of OC is used for solving the optimization problem to find the optimal absorbing material distribution. Numerical tests are provided to illustrate the application of the optimization procedure for 2D sound barriers. Results show that the optimal distribution of the sound absorbing material is strongly frequency dependent, and performing an optimization in a frequency band is generally needed.

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Titel: Design of absorbing material distribution for sound barrier using topology optimization
verfasst von: Wenchang Zhao
Leilei Chen
Changjun Zheng
Cheng Liu
Haibo Chen
Publikationsdatum: 14.02.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Structural and Multidisciplinary Optimization / Ausgabe 2/2017
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI: https://doi.org/10.1007/s00158-017-1666-8

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