Developing an optimization algorithm for diagnostic modeling of optical emission spectroscopic measurement of non-equilibrium plasmas based on the argon collisional-radiative model

In this work, an optimization algorithm was proposed for plasma diagnostic modeling based on a statistical analysis of reduced population density distribution. The algorithm generates a diagnostic equation, whose input parameters are the radiant flux of the multi-optical emission lines, and output p...

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Bibliographic Details
Published in:Japanese Journal of Applied Physics 2021-04, Vol.60 (4), p.46003
Main Authors: Yamashita, Yuya, Akiba, Takuya, Iwanaga, Toshihide, Yamaoka, Hidehiko, Date, Shuichi, Akatsuka, Hiroshi
Format: Article
Language:English
Subjects:
Algorithms
Argon
Atmospheric models
Density distribution
Diagnostic systems
Dielectric barrier discharge
Distribution functions
Electron density
Electron energy
Electron energy distribution
Error analysis
Inductively coupled plasma
Low pressure
Mathematical models
Microwave discharge
Nonequilibrium plasmas
Optimization
Optimization algorithms
Parameters
Plasma
Population (statistical)
Population density
Radiant flux
Statistical analysis
Surface waves
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Summary:In this work, an optimization algorithm was proposed for plasma diagnostic modeling based on a statistical analysis of reduced population density distribution. The algorithm generates a diagnostic equation, whose input parameters are the radiant flux of the multi-optical emission lines, and output parameters are electron temperature T e , electron density N e , and electron energy distribution function (EEDF), based on the dependence of reduced population density on T e , N e , and EEDF. The argon collisional-radiative model and the generalized EEDF were applied for the analysis of the excitation-kinetics. In this study, the diagnostic error for the low-pressure inductively coupled plasma, the low-pressure microwave discharge surface wave plasma, and the atmospheric dielectric barrier discharge plasma were simulated. The simulated diagnostic errors were smaller than those of the previously reported model.
ISSN:0021-4922
1347-4065
DOI:10.35848/1347-4065/abe642