Physics-guided attention-aware convolutional neural networks for identification of magnetic islands in the tearing mode on EAST tokamak

Physics-guided attention-aware convolutional neural networks for identification of magnetic islands in the tearing mode on EAST tokamak

The tearing mode (TM), a large-scale magnetohydrodynamic instability in tokamak, typically disrupts the equilibrium magnetic surfaces, leads to the formation of magnetic islands, reduces core electron temperature and density, thus resulting in significant energy losses and may even cause discharge t...

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Main Authors: Feifei Long, Yian Zhao, Yunjiao Zhang, Chenguang Wan, Yinan Zhou, Ziwei Qiang, Kangning Yang, Jiuying Li, Tonghui Shi, Bihao Guo, Yang Zhang, Hailing Zhao, Ang Ti, Adi Liu, Chu Zhou, Jinlin Xie, Zixi Liu, Ge Zhuang, the EAST Team
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Nuclear Fusion
Subjects:
tearing mode
magnetic island
neural networks
MCF
tokamak
Online Access:https://doi.org/10.1088/1741-4326/adc9c2
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https://doi.org/10.1088/1741-4326/adc9c2

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