Quantitative analysis of latent space in airfoil shape generation using variational autoencoders
Research on shape generation using machine learning has been widely conducted, and two-dimensional laminar flow airfoils are treated as a benchmark problem. When learning airfoil shapes using variational autoencoders (VAEs), it is known that the results obtained by ordinary VAE (N-VAE) and hypersphe...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | Japanese |
| Published: |
The Japan Society of Mechanical Engineers
2021-10-01
|
| Series: | Nihon Kikai Gakkai ronbunshu |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/transjsme/87/903/87_21-00212/_pdf/-char/en |