Machine learning-based mechanical performance prediction and design of lattice structures

•A data-driven framework enables elastic modulus prediction and inverse design of lattice cells.•The designed neural network model achieves superior prediction accuracy.•The proposed C-VAE captures intrinsic correlations between lattice topology and mechanical properties.•An inverse strategy with im...

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Veröffentlicht in:	International journal of mechanical sciences Jg. 294; S. 110230
Hauptverfasser:	Liu, Yifan, Huang, Wei, Wang, Zhiyong, Zhang, Jie, Liu, Jiayi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.05.2025
Schlagworte:	3D-printed architected materials Conditional variational autoencoder Elastic modulus Inverse design Lattice unit cell Machine learning Conditional variational autoencoder Elastic modulus 3D-printed architected materials Inverse design Lattice unit cell Machine learning
ISSN:	0020-7403
Online-Zugang:	Volltext
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