Abstract
EHL-2 is a compact, high-field spherical tokamak designed to explore the potential of an advanced p-11B nuclear fusion reactor. Due to its high plasma current and thermal energy, it is crucial to mitigate the impact associated with disruptions to ensure the safe operation of EHL-2. This paper evaluates the performance requirements of the disruption prediction system on EHL-2, with a particular focus on applying generalizable knowledge transfer from existing devices to future ones. Furthermore, the key characteristics of disruption mitigation strategies are analyzed, and their overall mitigation performance on EHL-2 is assessed. This insight provides valuable guidance for optimizing the engineering design of EHL-2 and identifying its optimal operational regime.
| Original language | English |
|---|---|
| Article number | 024013 |
| Journal | Plasma Science and Technology |
| Volume | 27 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1 Feb 2025 |
Keywords
- EHL-2
- disruption mitigation
- disruption prediction
- neural network
- spherical tokamak
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