A general trend in the experimental programmes of present day Tokamaks, and of JET in particular, is the constant increase in the number of parameters to be controlled in real time, to satisfy the machine protection requirements on the one hand and to improve performance on the other. Since the amount of data collected is also increasing at least at a rate compatible with the Moore law, significant developments are required in the field of real time algorithms particularly for magnetic reconstructions, disruption prediction and image processing. A new real time equilibrium code called EQUINOX, using internal and external measurements of the magnetic fields, has been qualified on JET. It can provide reconstructed accurate equilibria about every 50 ms on a 2 GHz PC. An advanced disruption predictor, based on machine learning tools, has been deployed using inputs selected with a genetic algorithm. Its success rate remains of the order of 94% for up to 170 ms before the occurrence of the disruption. Nonextensive entropies, which are more sensitive to long range correlations, seem to be useful in detecting vibrations in the videos of JET cameras, both visible and infrared.

New signal processing methods and information technologies for the real time control of JET reactor relevant plasmas

A Murari;
2011

Abstract

A general trend in the experimental programmes of present day Tokamaks, and of JET in particular, is the constant increase in the number of parameters to be controlled in real time, to satisfy the machine protection requirements on the one hand and to improve performance on the other. Since the amount of data collected is also increasing at least at a rate compatible with the Moore law, significant developments are required in the field of real time algorithms particularly for magnetic reconstructions, disruption prediction and image processing. A new real time equilibrium code called EQUINOX, using internal and external measurements of the magnetic fields, has been qualified on JET. It can provide reconstructed accurate equilibria about every 50 ms on a 2 GHz PC. An advanced disruption predictor, based on machine learning tools, has been deployed using inputs selected with a genetic algorithm. Its success rate remains of the order of 94% for up to 170 ms before the occurrence of the disruption. Nonextensive entropies, which are more sensitive to long range correlations, seem to be useful in detecting vibrations in the videos of JET cameras, both visible and infrared.
2011
Istituto gas ionizzati - IGI - Sede Padova
Inglese
86
6-8
544
547
4
http://www.sciencedirect.com/science/article/pii/S092037961000606X
Sì, ma tipo non specificato
Real time equilibrium reconstruction
Genetic Algorithms
SVM
Nonextensive entropy
This work, supported by the European Communities under the contract of Association between EURATOM, ENEA, CIEMAT and CEA, was carried out under the framework of the European Fusion Development Agreement. "Funding under Association Contract FU07-CT-2007-00053" / La rivista è pubblicata anche online con ISSN 1873-7196 (Editore: Elsevier Science SA).
1
info:eu-repo/semantics/article
262
A. Murari; J. Vega; D. Mazon; G.A. Rattá; M.Gelfusa; A. Debrie; C. Boulbe; B. Faugeras; JETEFDA Contributors
01 Contributo su Rivista::01.01 Articolo in rivista
none
   EU Fusion for ITER Applications
   EUFORIA
   FP7
   211804
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/41589
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