Topology optimization of multi-material underwater broadband sound absorption metamaterial based on genetic algorithm

Combining multiple sound energy dissipation mechanisms is essential for improving the sound absorption performance of underwater acoustic metamaterials. The calculation of absorption coefficients of the acoustic structures uses the finite element method, and the hexagonal unit is approximated to a two-dimensional axial symmetry unit. Genetic algorithms and topology optimization methods are combined to design the microstructure of acoustic metamaterials. The rubber, air, and scatterer are taken as optimized materials for microstructure to find the optimal material distribution within the metamaterial. A data filtering method is proposed to eliminate the checkerboard phenomenon. The sound absorption mechanism of the topology structure is analyzed. The advantages of the three-phase material topology structure are revealed by comparing it with two-phase material topology structures. The influences of material parameters, structural parameters, and incident angles on sound absorption performance are studied. The results showed that the average sound absorption coefficient of the optimal topology structure is 0.9574 in the frequency range of 500-10 000 Hz. The material parameters of rubber have no obvious effect on sound absorption performance, which is convenient for selecting matrix materials. The research method provides some ideas for designing low-frequency broadband underwater acoustic metamaterials with multiphase materials.

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Publication Details

Journal
The Journal of the Acoustical Society of America
Published
2025-05-01
DOI
https://doi.org/10.1121/10.0036637
Citations
4
Primary Topic
Acoustic Wave Phenomena Research
Type
article
Field-Weighted Citation Impact
2.70

Funders

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article

Topology optimization of multi-material underwater broadband sound absorption metamaterial based on genetic algorithm

Chuan He, Ying Tong, Feifei Feng, Meng Tao et al.
4 citations
The Journal of the Acoustical Society of America
Acoustic Wave Phenomena Research
2.70
article

Topology optimization of multi-material underwater broadband sound absorption metamaterial based on genetic algorithm

Chuan He, Ying Tong, Feifei Feng, Meng Tao, Jingyong Cai, Zixian Cui
article en
4 citations

Abstract

Combining multiple sound energy dissipation mechanisms is essential for improving the sound absorption performance of underwater acoustic metamaterials. The calculation of absorption coefficients of the acoustic structures uses the finite element method, and the hexagonal unit is approximated to a two-dimensional axial symmetry unit. Genetic algorithms and topology optimization methods are combined to design the microstructure of acoustic metamaterials. The rubber, air, and scatterer are taken as optimized materials for microstructure to find the optimal material distribution within the metamaterial. A data filtering method is proposed to eliminate the checkerboard phenomenon. The sound absorption mechanism of the topology structure is analyzed. The advantages of the three-phase material topology structure are revealed by comparing it with two-phase material topology structures. The influences of material parameters, structural parameters, and incident angles on sound absorption performance are studied. The results showed that the average sound absorption coefficient of the optimal topology structure is 0.9574 in the frequency range of 500-10 000 Hz. The material parameters of rubber have no obvious effect on sound absorption performance, which is convenient for selecting matrix materials. The research method provides some ideas for designing low-frequency broadband underwater acoustic metamaterials with multiphase materials.

The Journal of the Acoustical Society of AmericaVol. 157(5)
Guizhou University (CN), Systems Engineering Society of China (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Acoustic Wave Phenomena Research
2.70
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Topology optimization of multi-material underwater broadband sound absorption metamaterial based on genetic algorithm — Chuan He, Ying Tong, et al. · The Journal of the Acoustical Society of America (2025) | TGRS Research Map | TGRS