DocumentCode :
2114892
Title :
A neural network approach for the detection of the locking position in RFX
Author :
Barana, O. ; Manduchi, G. ; Serri, A. ; Sonato, P.
Author_Institution :
Consorzio RFX, Padova, Italy
fYear :
1999
fDate :
1999
Firstpage :
575
Lastpage :
578
Abstract :
Recently in RFX, where wall locked modes were always present, a new technique has demonstrated the possibility to induce a continuous rotation of the modes with respect to the wall. In this technique the nonlinear coupling of the m=0 and m=1 modes has been used to decouple the modes themselves. In the present experiments the mode rotation is induced with a preprogrammed waveform of a toroidal magnetic field rotating ripple. A feedback system able to create a continuous rotation with variable and increasing speed is now under implementation. A neural network (NN) has been developed to identify the locked mode position. In the paper different NNs are presented, discussed and compared
Keywords :
feedback; fusion reactor design; neural nets; nuclear engineering computing; plasma flow; plasma instability; plasma-wall interactions; reversed field pinch; RFX; Reversed Field Experiment; continuous rotation; feedback system; fusion reactors; locking position detection; neural network approach; nonlinear coupling; preprogrammed waveform; toroidal magnetic field rotating ripple; wall locked modes; Feedback; Intelligent networks; Laser mode locking; Magnetic variables control; Neural networks; Neurofeedback; Plasma properties; Tokamaks; Toroidal magnetic fields; Torque;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fusion Engineering, 1999. 18th Symposium on
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-5829-5
Type :
conf
DOI :
10.1109/FUSION.1999.849905
Filename :
849905
Link To Document :
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