Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • Persone
  • Pubblicazioni
  • Strutture
  • Competenze

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • Persone
  • Pubblicazioni
  • Strutture
  • Competenze
  1. Pubblicazioni

Automatic disruption classification in JET with the ITER-like wall

Articolo
Data di Pubblicazione:
2015
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.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
disruptions; prediction; classification; machine learning; fusion plasma; real-time control
Elenco autori:
Murari, Andrea
Autori di Ateneo:
MURARI ANDREA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/310482
Pubblicato in:
PLASMA PHYSICS AND CONTROLLED FUSION (PRINT)
Journal
  • Dati Generali

Dati Generali

URL

http://iopscience.iop.org/article/10.1088/0741-3335/57/12/125003/meta
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)