TGLF-WINN: data-efficient deep learning surrogate for turbulent transport modeling in fusion
The trapped Gyro-Landau Fluid (TGLF) model provides fast, accurate predictions of turbulent transport in tokamaks, but whole device simulations requiring thousands of evaluations remain computationally expensive. Neural network (NN) surrogates offer accelerated inference with fully differentiable ap...
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| Asıl Yazarlar: | , , , , , , , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
IOP Publishing
2026-01-01
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| Seri Bilgileri: | Nuclear Fusion |
| Konular: | |
| Online Erişim: | https://doi.org/10.1088/1741-4326/ae72a6 |
| Etiketler: |
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