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Disruption prediction and mitigation strategies in the EHL-2 spherical torus

  • Jianqing Cai*
  • , Yunfeng Liang
  • , Zhongyong Chen
  • , Wei Zheng
  • , Di Hu
  • , Lei Xue
  • , Zhifang Lin
  • , Xiang Gu
  • , the EHL 2. Team
  • *Corresponding author for this work
  • Hebei Key Laboratory of Compact Fusion
  • Jülich Research Centre
  • Huazhong University of Science and Technology
  • Institute of Physics
  • Jiangsu Normal University
  • ENN Group Co., Ltd.

Research output: Contribution to journal › Article › peer-review

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 languageEnglish
Article number024013
JournalPlasma Science and Technology
Volume27
Issue number2
DOIs
StatePublished - 1 Feb 2025

Keywords

  • EHL-2
  • disruption mitigation
  • disruption prediction
  • neural network
  • spherical tokamak

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