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Machine learning assisted intelligent design of meta structures: a review
dc.contributor.author | He, Liangshu | |
dc.contributor.author | Li, Yan | |
dc.contributor.author | Torrent, Daniel | |
dc.contributor.author | Zhuang, Xiaoying | |
dc.contributor.author | Rabczuk, Timon | |
dc.contributor.author | Jin, Yabin | |
dc.date.accessioned | 2024-02-26T11:59:38Z | |
dc.date.available | 2024-02-26T11:59:38Z | |
dc.date.issued | 2023-10 | |
dc.identifier.citation | He L, Li Y, Torrent D, Zhuang X, Rabczuk T, Jin Y. Machine learning assisted intelligent design of meta structures: a review. Microstructures 2023;3:2023034. https://dx.doi.org/10.20517/microstructures.2023.29 | ca_CA |
dc.identifier.uri | http://hdl.handle.net/10234/206009 | |
dc.description.abstract | In recent years, the rapid development of machine learning (ML) based on data-driven or environment interaction has injected new vitality into the field of meta-structure design. As a supplement to the traditional analysis methods based on physical formulas and rules, the involvement of ML has greatly accelerated the pace of performance exploration and optimization for meta-structures. In this review, we focus on the latest progress of ML in acoustic, elastic, and mechanical meta-structures from the aspects of band structures, wave propagation characteristics, and static characteristics. We finally summarize and envisage some potential research directions of ML in the field of meta-structures. | ca_CA |
dc.format.extent | 24 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | OAE Publishing | ca_CA |
dc.relation.isPartOf | Microstructures 2023; 3. | ca_CA |
dc.rights | © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License | ca_CA |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | ca_CA |
dc.subject | Meta-structure | ca_CA |
dc.subject | inverse design | ca_CA |
dc.subject | machine learning | ca_CA |
dc.subject | continuous fiber reinforced composite metastructure | ca_CA |
dc.subject | additive manufacture | ca_CA |
dc.title | Machine learning assisted intelligent design of meta structures: a review | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.20517/microstructures.2023.29 | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://www.oaepublish.com/articles/microstructures.2023.29 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
project.funder.name | National Key Research and Development Program of China | ca_CA |
project.funder.name | National Natural Science Foundation of China | ca_CA |
project.funder.name | The Young Elite Scientists Sponsorship Program | ca_CA |
project.funder.name | Shanghai Science and Technology Committee | ca_CA |
project.funder.name | Fundamental Research Funds for the Central Universities | ca_CA |
project.funder.name | Agencia Estatal de Investigación | ca_CA |
oaire.awardNumber | 2022YFB4602000 | ca_CA |
oaire.awardNumber | 12272267 | ca_CA |
oaire.awardNumber | 52278411 | ca_CA |
oaire.awardNumber | 2021QNRC001 | ca_CA |
oaire.awardNumber | 22JC1404100 | ca_CA |
oaire.awardNumber | 21JC1405600 | ca_CA |
oaire.awardNumber | PID2021-124814NB-C22 | ca_CA |
oaire.awardNumber | MCIN/AEI/10.13039/501100011033 | ca_CA |
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