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

被引:0
|
作者
Cai, Jianqing [1 ,2 ]
Liang, Yunfeng [1 ,2 ]
Chen, Zhongyong [3 ]
Zheng, Wei [3 ]
Hu, Di [4 ]
Xue, Lei [5 ]
Lin, Zhifang [6 ]
Gu, Xiang [1 ,7 ]
机构
[1] Hebei Key Lab Compact Fus, Langfang 065001, Peoples R China
[2] Forschungszentrum Julich, Inst Fus Energy & Nucl Waste Management Plasmaphy, D-52425 Julich, Germany
[3] Huazhong Univ Sci & Technol, Sch Elect & Elect Engn, Int Joint Res Lab Magnet Confinement Fus & Plasma, Wuhan 430074, Peoples R China
[4] Beihang Univ, Sch Phys, 37 Xueyuan Rd, Beijing 100191, Peoples R China
[5] South Western Inst Phys, Chengdu 610225, Peoples R China
[6] Jiangsu Normal Univ, Sch Elect Engn & Automat, Xuzhou 221116, Peoples R China
[7] ENN Sci & Technol Dev Co Ltd, Langfang 065001, Peoples R China
基金
中国国家自然科学基金;
关键词
spherical tokamak; EHL-2; disruption mitigation; disruption prediction; neural network; GAS-JET; NEURAL-NETWORK; IMPURITY; INJECTION; SHUTDOWN; DESIGN;
D O I
10.1088/2058-6272/adb40b
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
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.
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页数:10
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