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Metaheuristic optimisation of an elastic metamaterial for robust vibration control

Metaheuristic optimisation of an elastic metamaterial for robust vibration control
Metaheuristic optimisation of an elastic metamaterial for robust vibration control
Parametric uncertainty in a structure can reduce modelling accuracy, leading to a reduction in the efficacy of a vibration suppression system. The suppression of modal vibration with robustness to parametric uncertainty has been demonstrated using multiple tuned-vibration-absorbers (TVAs) with distributed resonance frequencies. In this paper, an Elastic Metamaterial (EMM) unit cell consisting of multiple single-degree-of-freedom resonators is defined for the absorption of vibration in a cantilever beam. A genetic algorithm (GA), hybrid genetic algorithm (HGA) and particle swarm optimisation (PSO) are compared in their ability to optimise the resonance frequencies of the unit cell to minimise the mean kinetic energy gain of the EMM, on a beam with parametric variation. Firstly, all optimisation procedures are able to produce an EMM unit cell with good robustness to parametric uncertainty. When the optimisations are run until convergence, the PSO is shown to achieve the best fitness value, but with an increase in computation time compared to the GA. The HGA achieves a better fitness value than the GA but computation time is inflated by a factor greater than 50. By also running until a time constraint is met, it is shown that the GA and PSO perform similarly for the same time-limit.
1939-800X
Singleton, Lawrence
b7b7fbb9-2469-4774-8572-31a016b7e5ac
Cheer, Jordan
8e452f50-4c7d-4d4e-913a-34015e99b9dc
Daley, Stephen
53cef7f1-77fa-4a4c-9745-b6a0ba4f42e6
Singleton, Lawrence
b7b7fbb9-2469-4774-8572-31a016b7e5ac
Cheer, Jordan
8e452f50-4c7d-4d4e-913a-34015e99b9dc
Daley, Stephen
53cef7f1-77fa-4a4c-9745-b6a0ba4f42e6

Singleton, Lawrence, Cheer, Jordan and Daley, Stephen (2020) Metaheuristic optimisation of an elastic metamaterial for robust vibration control. Proceedings of Meetings on Acoustics, 39 (1), [045008]. (doi:10.1121/2.0001185).

Record type: Article

Abstract

Parametric uncertainty in a structure can reduce modelling accuracy, leading to a reduction in the efficacy of a vibration suppression system. The suppression of modal vibration with robustness to parametric uncertainty has been demonstrated using multiple tuned-vibration-absorbers (TVAs) with distributed resonance frequencies. In this paper, an Elastic Metamaterial (EMM) unit cell consisting of multiple single-degree-of-freedom resonators is defined for the absorption of vibration in a cantilever beam. A genetic algorithm (GA), hybrid genetic algorithm (HGA) and particle swarm optimisation (PSO) are compared in their ability to optimise the resonance frequencies of the unit cell to minimise the mean kinetic energy gain of the EMM, on a beam with parametric variation. Firstly, all optimisation procedures are able to produce an EMM unit cell with good robustness to parametric uncertainty. When the optimisations are run until convergence, the PSO is shown to achieve the best fitness value, but with an increase in computation time compared to the GA. The HGA achieves a better fitness value than the GA but computation time is inflated by a factor greater than 50. By also running until a time constraint is met, it is shown that the GA and PSO perform similarly for the same time-limit.

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More information

Accepted/In Press date: 24 January 2020
e-pub ahead of print date: 5 May 2020
Venue - Dates: 178th Meeting of the Acoustical Society of America, Coronado Island, United States, 2019-12-02 - 2019-12-06

Identifiers

Local EPrints ID: 441086
URI: http://eprints.soton.ac.uk/id/eprint/441086
ISSN: 1939-800X
PURE UUID: 893e21e1-cc94-455f-902f-4eb45c019b88
ORCID for Jordan Cheer: ORCID iD orcid.org/0000-0002-0552-5506

Catalogue record

Date deposited: 29 May 2020 16:31
Last modified: 07 Oct 2020 01:58

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