Sawtooth crashes are observed during ECCD experiments at the superconducting optimized stellarator Wendelstein 7-X. The study and the characterization are necessary in order to understand under which condition ECCD can be driven without posing a risk to experimental operations. The development of automatic tools is crucial to speed up the analysis of extensive datasets. In this work, we report on the first attempt of using a data-driven approach to automatically characterize the sawtooth crashes. Cluster algorithms are applied to the dataset, confirming the existence of two distinct types of crashes. This approach allows to study the two groups separately and underlines the different plasma parameters that influence the sawtooth crash parameters, for instance crash amplitude and period.
Automated W7-X sawtooth crashes detection and characterization
Aymerich, E.;
2024-01-01
Abstract
Sawtooth crashes are observed during ECCD experiments at the superconducting optimized stellarator Wendelstein 7-X. The study and the characterization are necessary in order to understand under which condition ECCD can be driven without posing a risk to experimental operations. The development of automatic tools is crucial to speed up the analysis of extensive datasets. In this work, we report on the first attempt of using a data-driven approach to automatically characterize the sawtooth crashes. Cluster algorithms are applied to the dataset, confirming the existence of two distinct types of crashes. This approach allows to study the two groups separately and underlines the different plasma parameters that influence the sawtooth crash parameters, for instance crash amplitude and period.File | Dimensione | Formato | |
---|---|---|---|
Zanini_2024_Nucl._Fusion_64_076027.pdf
accesso aperto
Descrizione: articolo online
Tipologia:
versione editoriale (VoR)
Dimensione
4.83 MB
Formato
Adobe PDF
|
4.83 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.