Recently, a linear disruption predictor (Vega et al 2020 Nucl. Fusion 60 026001) was installed in the JET real-time network for disruption mitigation purposes. From a mathematical point of view, the predictor is based on computing centroids of disruptive examples and non-disruptive examples in a two-dimensional space. This is the reason for calling it centroid method (CM). It uses a single signal: the mode lock normalized to the plasma current. The predictor is not based on thresholds to trigger alarms but on the differences of amplitudes between consecutive samples. The article analyses its results for the range of discharges 94 152-97 137 (June 2019-March 2020), including discharges of both baseline scenario and hybrid scenario. The article presents a comparison between the CM predictor and several different disruption detection systems operational in the JET real-time event detection platform named PETRA (Plasma Events Triggering for Alarms). The CM predictor outperforms all the other classifiers implemented in PETRA, according to all the main statistical indicators normally used to qualify these tools.

Performance analysis of the centroid method predictor implemented in the JET real time network

Murari A;
2022

Abstract

Recently, a linear disruption predictor (Vega et al 2020 Nucl. Fusion 60 026001) was installed in the JET real-time network for disruption mitigation purposes. From a mathematical point of view, the predictor is based on computing centroids of disruptive examples and non-disruptive examples in a two-dimensional space. This is the reason for calling it centroid method (CM). It uses a single signal: the mode lock normalized to the plasma current. The predictor is not based on thresholds to trigger alarms but on the differences of amplitudes between consecutive samples. The article analyses its results for the range of discharges 94 152-97 137 (June 2019-March 2020), including discharges of both baseline scenario and hybrid scenario. The article presents a comparison between the CM predictor and several different disruption detection systems operational in the JET real-time event detection platform named PETRA (Plasma Events Triggering for Alarms). The CM predictor outperforms all the other classifiers implemented in PETRA, according to all the main statistical indicators normally used to qualify these tools.
2022
Istituto per la Scienza e Tecnologia dei Plasmi - ISTP
Inglese
64
11
114003-1
114003-8
8
https://iopscience.iop.org/article/10.1088/1361-6587/ac963f/meta
Sì, ma tipo non specificato
disruptions
JET
automated detection
Electronic ISSN: 1361-6587 - http://www.scopus.com/inward/record.url?eid=2-s2.0-85140140658&partnerID=q2rCbXpz - This work has been carried out within the framework of the EUROfusion Consortium, funded by the European Union via the Euratom Research and Training Programme (Grant Agreement No. 101052200--EUROfusion). This work was also partially funded by the Spanish Ministry of Economy and Competitiveness under Project Nos. PID2019-108377RB-C31 and PID2019-108377RB-C32.
1
info:eu-repo/semantics/article
262
Gadariya D.; Vega J.; Stuart C.; Ratta G.; Card P.; Murari A.; DormidoCanto S.
01 Contributo su Rivista::01.01 Articolo in rivista
none
   Implementation of activities described in the Roadmap to Fusion during Horizon 2020 through a Joint programme of the members of the EUROfusion consortium
   EUROfusion
   H2020
   633053
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/416771
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