Fusion Science and Technology / Volume 62 / Number 3 / November 2012 / Pages 403-408
Selected Paper from Seventh Fusion Data Validation Workshop 2012 (Part 2)
New automated analysis methods allow the analysis of large amounts of data without human interaction. Tokamak machines, such as JET, are perfect candidates to apply data mining techniques in order to obtain results with high statistical relevance. In this paper, an automated technique to analyze the pedestal edge gradient is introduced. This technique does not require human intervention and therefore can be applied to many pulses. The pedestal edge gradient is the temperature gradient corresponding to the edge transport barrier at the edge of high-confinement-mode plasmas. This gradient is quantified using the temperature profiles obtained from the electron cyclotron emission diagnostic. An automated technique to locate events in plasma pulses is applied in order to locate edge-localized modes (ELMs), and then the evolution of the edge pedestal gradient is analyzed during the ELMs. The degradation of the edge pedestal gradient during an ELM is quantified using the edge pedestal gradient 2 ms before the ELM as a reference of the amplitude of the gradient. This technique has been applied to a JET database containing >700 pulses and >46 000 ELMs.