摘要
A gas puff imaging(GPI) diagnostic has been developed and applied to measure edge plasma turbulence on the HL-2A tokamak.The principle and experimental setup of GPI are described.GPI is applied to investigate blobs in the edge and scrape-off layer.Statistical characterizations of GPI line emission intensity are calculated, including the probability density functions(PDFs),skewness, and kurtosis of the intensity, which are found to be consistent with measurements by Langmuir probes.Besides, the track of blob motions is recorded by time sequence of individual frames.The characteristics of the original images and the relatively high-frequency(>10 kHz)/low-frequency(1–10 kHz) component images are illustrated.The observation of the blob’s structures and high-speed motions proves the success and high performance of the GPI diagnostic.
A gas puff imaging(GPI) diagnostic has been developed and applied to measure edge plasma turbulence on the HL-2A tokamak.The principle and experimental setup of GPI are described.GPI is applied to investigate blobs in the edge and scrape-off layer.Statistical characterizations of GPI line emission intensity are calculated, including the probability density functions(PDFs),skewness, and kurtosis of the intensity, which are found to be consistent with measurements by Langmuir probes.Besides, the track of blob motions is recorded by time sequence of individual frames.The characteristics of the original images and the relatively high-frequency(>10 kHz)/low-frequency(1–10 kHz) component images are illustrated.The observation of the blob’s structures and high-speed motions proves the success and high performance of the GPI diagnostic.
基金
supported by the National Key Research and Development Program of China (No.2017YFE0300405)
National Natural Science Foundation of China (Nos.11575055, 11705052, 11875124, 11475058, and 11475056)
the National Key Research and Development Program of China (Nos.2017YFE0301201, 2018YFE0303102, 2018YFE0309103)
the Chinese National Fusion Project for ITER (No.2015GB104000)
