Tokamak divertor plasma emulation with machine learning

Tokamak divertor plasma emulation with machine learning

Future tokamak devices that aim to create conditions relevant to power plant operations must consider strategies for mitigating damage to plasma facing components in the divertor. One of the goals of MAST-U tokamak operations is to inform these considerations by researching advanced divertor configu...

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Bibliographic Details
Main Authors: G.K. Holt, A. Keats, S. Pamela, M. Kryjak, A. Agnello, N.C. Amorisco, B.D. Dudson, M. Smyrnakis
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Nuclear Fusion
Subjects:
tokamak divertor
plasma fluid simulation database
MAST-Upgrade
machine learning
neural network
Online Access:https://doi.org/10.1088/1741-4326/ad4f9e

Internet

https://doi.org/10.1088/1741-4326/ad4f9e

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