Computational design of a large dataset of viscoelastic metastructures for inverse design in low-frequency vibration attenuation

Turlin, R, Hirschler, T, Bodaghi, M ORCID: https://orcid.org/0000-0002-0707-944X and Demoly, F, 2025. Computational design of a large dataset of viscoelastic metastructures for inverse design in low-frequency vibration attenuation. In: Active and Passive Smart Structures and Integrated Systems XIX. Proceedings. Proceedings of SPIE (13432). SPIE. ISBN 9781510686502

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Abstract

In the context of acoustic stealth, the attenuation of low-frequency vibrations generated by submarine rotating machinery remains a major challenge. Existing passive and active solutions still have limitations to effectively mitigate vibrations across varying operating conditions. The research work introduces a computational design approach that integrates generative design and finite element analysis to build a comprehensive dataset of viscoelastic meta-structures, characterized by their transmissibility. This dataset will serve as a foundation for future machine learning-enabled inverse design, paving the way for optimized vibration attenuation strategies.

Item Type:	Chapter in book
Creators:	Turlin, R., Hirschler, T., Bodaghi, M. and Demoly, F.
Publisher:	SPIE
Date:	5 May 2025
Number:	13432
ISBN:	9781510686502
Identifiers:	Number Type 10.1117/12.3051444 DOI 2445117 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	24 Sep 2025 15:16
Last Modified:	24 Sep 2025 15:16
URI:	https://irep.ntu.ac.uk/id/eprint/54417

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