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

• 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: Article
• Language: English
• Published: 2024
• Subjects: Engineering; Machine learning; Evolutionary algorithm
• Online Access: https://hdl.handle.net/10356/181246
• Institution: Nanyang Technological University

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...