Automatic disruption classification in JET with the ITER-like wall

被引:27
|
作者
Cannas, B. [1 ]
de Vries, P. C. [2 ]
Fanni, A. [1 ]
Murari, A. [3 ]
Pau, A. [1 ]
Sias, G. [1 ]
机构
[1] Univ Cagliari, Elect & Elect Engn Dept, I-09124 Cagliari, Italy
[2] ITER Org, F-13115 St Paul Les Durance, France
[3] Consorzio RFX Assoc EURATOM ENEA Fus, I-35127 Padua, Italy
关键词
disruptions; prediction; classification; machine learning; fusion plasma; real-time control; NEAREST-NEIGHBOR SEARCH; NEURAL-NETWORKS; PREDICTION; LIMIT;
D O I
10.1088/0741-3335/57/12/125003
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
The new full-metal ITER-like wall at JET was found to have a deep impact on the physics of disruptions at JET. In order to develop disruption classification, the 10D operational space of JET with the new ITER-like wall has been explored using the generative topographic mapping method. The 2D map has been exploited to develop an automatic disruption classification of several disruption classes manually identified. In particular, all the non-intentional disruptions have been considered, that occurred in JET from 2011 to 2013 with the new wall. A statistical analysis of the plasma parameters describing the operational spaces of JET with carbon wall and JET ITER-like wall has been performed and some physical considerations have been made on the difference between these two operational spaces and the disruption classes which can be identified. The performance of the JET-ITER-like wall classifier is tested in real-time in conjunction with a disruption predictor presently operating at JET with good results. Moreover, to validate and analyse the results, another reference classifier has been developed, based on the k-nearest neighbour technique. Finally, in order to verify the reliability of the performed classification, a conformal predictor based on non-conformity measures has been developed.
引用
收藏
页数:15
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