Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies
When designing passive sound-attenuation structures, one of the challenging problems that arise is optimally distributing acoustic porous materials within a design region so as to maximise sound absorption while minimising material usage. To identify efficient optimisation strategies for this multi-...
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Published in | The Journal of the Acoustical Society of America Vol. 153; no. 5; pp. 2945 - 2955 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
01.05.2023
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Online Access | Get full text |
ISSN | 0001-4966 1520-8524 1520-8524 |
DOI | 10.1121/10.0019455 |
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Summary: | When designing passive sound-attenuation structures, one of the challenging problems that arise is optimally distributing acoustic porous materials within a design region so as to maximise sound absorption while minimising material usage. To identify efficient optimisation strategies for this multi-objective problem, several gradient, non-gradient, and hybrid topology optimisation strategies are compared. For gradient approaches, the solid-isotropic-material-with-penalisation method and a gradient-based constructive heuristic are considered. For gradient-free approaches, hill climbing with a weighted-sum scalarisation and a non-dominated sorting genetic algorithm-II are considered. Optimisation trials are conducted on seven benchmark problems involving rectangular design domains in impedance tubes subject to normal-incidence sound loads. The results indicate that while gradient methods can provide quick convergence with high-quality solutions, often gradient-free strategies are able to find improvements in specific regions of the Pareto front. Two hybrid approaches are proposed, combining a gradient method for initiation and a non-gradient method for local improvements. An effective Pareto-slope-based weighted-sum hill climbing is introduced for local improvement. Results reveal that for a given computational budget, the hybrid methods can consistently outperform the parent gradient or non-gradient method. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0001-4966 1520-8524 1520-8524 |
DOI: | 10.1121/10.0019455 |