Studies of MHD Stability Using Data Mining Technique in Helical Plasmas

Satoshi YAMAMOTO, David PRETTY, Boyd BLACKWELL, Kazunobu NAGASAKI, Hiroyuki OKADA, Fumimichi SANO, Tohru MIZUUCHI, Shinji KOBAYASHI, Katsumi KONDO, Ruben JIMÉNEZ-GÓMEZ, Enrique ASCASÍBAR, Kazuo TOI (+1 others)
2010 Plasma and Fusion Research  
Data mining techniques, which automatically extract useful knowledge from large datasets, are applied to multichannel magnetic probe signals of several helical plasmas in order to identify and classify MHD instabilities in helical plasmas. This method is useful to find new MHD instabilities as well as previously identified ones. Moreover, registering the results obtained from data mining in a database allows us to investigate the characteristics of MHD instabilities with parameter studies. We
more » ... troduce the data mining technique consisted of pre-processing, clustering and visualizations using results from helical plasmas in H-1 and Heliotron J. We were successfully able to classify the MHD instabilities using the criterion of phase differences of each magnetic probe and identify them as energetic-ion-driven MHD instabilities using parameter study in Heliotron J plasmas.
doi:10.1585/pfr.5.034 fatcat:yfkxgyyekvh7pcxd3sgru2h4qq