Machine learning-enabled forward prediction and inverse design of 4D-printed active plates

Machine learning-enabled forward prediction and inverse design of 4D-printed active plates

Shape transformations of active composites (ACs) depend on the spatial distribution of constituent materials. Voxel-level complex material distributions can be encoded by 3D printing, offering enormous freedom for possible shape-change 4D-printed ACs. However, efficiently designing the material dist...

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Bibliographic Details
Main Authors: Sun, Xiaohao, Yue, Liang, Yu, Luxia, Forte, Connor T., Armstrong, Connor D., Zhou, Kun, Demoly, Frédéric, Zhao, Renee Ruike, Qi, Jerry Hang
Other Authors: School of Mechanical and Aerospace Engineering
Format: Journal Article
Language:English
Published: 2024
Subjects:
Engineering
Machine learning
Evolutionary algorithm
Online Access:https://hdl.handle.net/10356/181246

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