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physics.plasm-ph2024
Adaptive Anomaly Detection Disruption Prediction Starting from First Discharge on Tokamak
Xinkun Ai
Plasma disruption presents a significant challenge in tokamak fusion, where it can cause severe damage and economic losses. Current disruption predictors mainly rely on data-driven…
physics.plasm-ph2023
Cross-Tokamak Deployment Study of Plasma Disruption Predictors Based on Convolutional Autoencoder
Xinkun Ai, Wei Zheng, Ming Zhang +12
In the initial stages of operation for future tokamak, facing limited data availability, deploying data-driven disruption predictors requires optimal performance with minimal use o…
physics.plasm-ph2023
Cross-tokamak Disruption Prediction based on Physics-Guided Feature Extraction and domain adaptation
Chengshuo Shen, Wei Zheng, Bihao Guo +11
The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in dis…