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A runaway electron avalanche surrogate for partially ionized plasmas
A physics-constrained deep learning surrogate that predicts the exponential ‘avalanche’ growth rate of runaway electrons (REs) for a plasma containing partially ionized impurities is developed. Specifically, a physics-informed neural network (PINN) that learns the adjoint of the relativistic Fokker–...
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| Autors principals: | , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
IOP Publishing
2025-01-01
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| Col·lecció: | Nuclear Fusion |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1088/1741-4326/ae00db |
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