Abstract
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.
Highlights
The plasma disruptions in devices for the controlled thermonuclear fusion are associated to a sudden loss of magnetic confinement which causes the magnetic and thermal energy stored in the plasma to be released to surrounding structures
In order to validate and analyse the results obtained with generative topographic mapping (GTM), another reference classifier has been developed based on k nearest neighbour (k-neural networks (NNs)), which uses as kernel the Mahalanobis distance (Mahalanobis 1936)
The statistical analysis showed the variation of the JET-ILW operational space with respect to that with JET operations with the carbon wall (JET-C)
Summary
The plasma disruptions in devices for the controlled thermonuclear fusion are associated to a sudden loss of magnetic confinement which causes the magnetic and thermal energy stored in the plasma to be released to surrounding structures. In (Cannas et al 2013b) and (Murari 2013) both the proposed automatic disruption classifiers were based on the manual classification proposed in (de Vries 2011) for the discharges occurring during the JET operations with the carbon wall (JET-C) from 2000 to 2010. The analysis showed the necessity to develop a specialized GTM map of the 10D JET-ILW plasma parameter space for disruption classification purposes. Even if the presented analysis is not explicitly aimed at providing any particular further physical understanding, the proposed classifier is able to give a deeper knowledge of the characteristics of different disruption classes supplying an image of the parameter space where each region is associated to one or more disruptive behaviours. In order to verify the reliability of the classification, a conformal predictor has been developed which provides information on the level of confidence of the proposed classification
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