| About this Abstract |
| Meeting |
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
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| Symposium
|
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
| Presentation Title |
Smooth 3D Transition Cell Generation based on Latent Space Arithmetic |
| Author(s) |
Xiaochen Yu, Bohan Peng, Ajit Panesar |
| On-Site Speaker (Planned) |
Xiaochen Yu |
| Abstract Scope |
Lattice structures with multiple unit cell types have diversified the property space by offering more design freedom in adjusting geometric parameters at the microscale level. It is essential to ensure connectivity and smooth transition among different cell types to avoid pre-mature failure. In this work, we propose a framework to generate the transition cell with latent space operations. Latent embedding is a low-dimensional representation of the original microstructure and could be retrieved by training a machine learning (ML) model called variational autoencoder (VAE). Different types of triply periodic minimal surface (TPMS) lattice were chosen as the targets to demonstrate the capability of the algorithm in handling complex 3D geometries within a physically restricted transition region. Both visual and quantitative evaluations will be provided to illustrate the connectivity and geometric similarity of the generated transition. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |