A turbulence reduced order model based on non-interpolated convolutional autoencoder
Reduced-order modeling stands as a pivotal method in curbing the computational expenses linked with expansive fluid dynamics quandaries by employing proxy numerical simulations. Within this realm, downscaling and reconstruction methods serve as fundamental constituents of reduced-order modeling. The...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
EDP Sciences
2025-02-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/full_html/2025/01/jnwpu2025431p149/jnwpu2025431p149.html |
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