Inverse Design of Energy‐Absorbing Metamaterials by Topology Optimization
Abstract: Compared with the forward design method through the control of geometric parameters and material types, the inverse design method based on the target stress‐strain curve is helpful for the discovery of new structures. This study proposes an optimization strategy for mechanical metamaterials based on a genetic algorithm and establishes a topology optimization method for energy‐absorbing structures with the desired stress‐strain curves. A series of structural mutation algorithms and design‐domain‐independent mesh generation method are developed to improve the efficiency of finite element analysis and optimization iteration. The algorithm realizes the design of ideal energy‐absorbing structures, which are verified by additive manufacturing and experimental characterization. The error between the stress‐strain curve of the designed structure and the target curve is less than 5%, and the densification strain reaches 0.6. Furthermore, special attention is paid to passive pedestrian protection and occupant protection, and a reasonable solution is given through the design of a multiplatform energy‐absorbing structure. The proposed topology optimization framework provides a new solution path for the elastic‐plastic large deformation problem that is unable to be resolved by using classical gradient algorithms or genetic algorithms, and simplifies the design process of energy‐absorbing mechanical metamaterials.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Inverse Design of Energy‐Absorbing Metamaterials by Topology Optimization ; day:11 ; month:12 ; year:2022 ; extent:10
Advanced science ; (11.12.2022) (gesamt 10)
- Urheber
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Zeng, Qingliang
Duan, Shengyu
Zhao, Zeang
Wang, Panding
Lei, Hongshuai
- DOI
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10.1002/advs.202204977
- URN
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urn:nbn:de:101:1-2022121214055390931720
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:25 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Zeng, Qingliang
- Duan, Shengyu
- Zhao, Zeang
- Wang, Panding
- Lei, Hongshuai
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