%0 Journal Article
%A Wei, Yanling
%A Liu, Liang
%A Yu, Deliang
%A von Hellermann, Manfred
%A Chen, Wenjin
%A Wang, Jie
%A Ma, Qian
%A He, Xiaoxue
%A He, Xiaofei
%T Analysis of HL-2A charge exchange spectra using parallel genetic algorithm
%J Fusion engineering and design
%V 168
%@ 0920-3796
%C New York, NY [u.a.]
%I Elsevier
%M FZJ-2021-05657
%P 112680 -
%D 2021
%Z kein Zugriff auf Postprint
%X In this work, we present a new method based on parallel genetic algorithm (GA) for in-between shot data analysis of the Charge-Exchange (CX) spectra on the HL-2A tokamak. The neutral beam induced active CX spectra is a powerful ion diagnostic technique to provide spatially resolved ion temperature and rotation velocity measurements on fusion devices. Currently CX spectra obtained in HL-2A experiments are mainly analyzed by the CXSFIT code [A. D. Whiteford, et.al, 2007]. While the analysis itself is fast, its accuracy relies on proper setup of the initial values for the spectral fitting parameters. Time-consuming manual interventions are needed. In the new parallel GA code, a two-loop GA analysis is used to gradually update the fitting parameter search ranges, which enables automatic analysis. A parallel algorithm based on the Linux Message Passing Interface (MPI) cluster is adapted to speed up the process. In a test run, for a set of 1600 data slices, the total time elapsed with 8 CPU nodes is about 310 s (0.2 s per data slice), which is efficient for in-between shot analysis on HL-2A. The uncertainty calculations using virtual CX signals with a noise level up to 5% show that the accuracies for ion temperature and rotation velocity are better than 10.14% and 2.14%, respectively. The ion temperature and rotation velocity obtained by applying the new parallel genetic algorithm on experimental CX data show good agreement with the conventional CXSFIT results.
%F PUB:(DE-HGF)16
%9 Journal Article
%U <Go to ISI:>//WOS:000670075800010
%R 10.1016/j.fusengdes.2021.112680
%U https://juser.fz-juelich.de/record/904087