A neural network model relating extraction current characteristics with optical emission spectra for digital twin of miniaturized ion thrusters-Reference-Cited by-同舟云学术

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A neural network model relating extraction current characteristics with optical emission spectra for digital twin of miniaturized ion thrusters

Published:2023-06-19 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 10th International Workshop on Metrology for AeroSpace (MetroAeroSpace)
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Author:

Jia Jun-Wei¹,Zou Ren-Qiu²,Luo Qi³,Zhu Xi-Ming⁴,Wang Yan-Fei⁴,Wu Yu-Jing¹,Lang Hao¹,Zhang Wen-Jie⁵,Dong Xue-Jiang¹

Affiliation:

1. Beijing Orient Institute of Measurement and Test,Beijing,China

2. Beijing Institute of Space Long March Vehicle,Beijing,China

3. Ningbo Civil Construction Design and Research Institute Co.,Zhejiang,China

4. Harbin Institute of Technology,Harbin,China

5. Beijing Institute of Technology,Beijing,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10189920/10189924/10190002.pdf?arnumber=10190002

Reference21 articles.

1. Plasma optical emission spectroscopy based on feedforward neural network

2. A xenon collisional-radiative model applicable to electric propulsion devices: II. Kinetics of the 6s, 6p, and 5d states of atoms and ions in Hall thrusters

3. A xenon collisional-radiative model applicable to electric propulsion devices: I. Calculations of electron-impact cross sections for xenon ions by the Dirac B-spline R-matrix method

4. Water and xenon ECR ion thruster—comparison in global model and experiment

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