Vivek T. Ramamoorthy
Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies
Ramamoorthy, Vivek T.; Özcan, Ender; Parkes, Andrew J.; Jaouen, Luc; Bécot, François-Xavier
Authors
ENDER OZCAN ender.ozcan@nottingham.ac.uk
Professor of Computer Science and Operational Research
Dr ANDREW PARKES ANDREW.PARKES@NOTTINGHAM.AC.UK
Assistant Professor
Luc Jaouen
François-Xavier Bécot
Abstract
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.
Citation
Ramamoorthy, V. T., Özcan, E., Parkes, A. J., Jaouen, L., & Bécot, F. (2023). Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free, and hybrid strategies. Journal of the Acoustical Society of America, 153(5), Article 2945. https://doi.org/10.1121/10.0019455
Journal Article Type | Article |
---|---|
Acceptance Date | May 2, 2023 |
Online Publication Date | May 19, 2023 |
Publication Date | 2023-05 |
Deposit Date | Jul 26, 2023 |
Publicly Available Date | Jul 26, 2023 |
Journal | Journal of the Acoustical Society of America |
Print ISSN | 0001-4966 |
Electronic ISSN | 1520-8524 |
Publisher | Acoustical Society of America (ASA) |
Peer Reviewed | Peer Reviewed |
Volume | 153 |
Issue | 5 |
Article Number | 2945 |
DOI | https://doi.org/10.1121/10.0019455 |
Keywords | Acoustics, Evolutionary computation, Algorithms and data structure, Materials properties, 2D materials, Porous media, Optimization algorithms, Mathematical optimization, Gradient method, Optimization problems |
Public URL | https://nottingham-repository.worktribe.com/output/21112785 |
Publisher URL | https://pubs.aip.org/asa/jasa/article-abstract/153/5/2945/2891461/Multi-objective-topology-optimisation-for-acoustic?redirectedFrom=fulltext |
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Multiobjective Topology Optimisation Algorithms For Absorption Maximisation
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