Calculation of Electron Energy Distribution Functions From Electron Swarm Parameters Using Artificial Neural Network in SF6 and Argon
IEEE TRANSACTIONS ON PLASMA SCIENCE, cilt.38, sa.9, ss.2332-2339, 2010 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 38 Sayı: 9
- Basım Tarihi: 2010
- Doi Numarası: 10.1109/tps.2010.2049588
- Dergi Adı: IEEE TRANSACTIONS ON PLASMA SCIENCE
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.2332-2339
- Anahtar Kelimeler: Argon, boltzmann equation, neural networks, SF6, EFFECTIVE IONIZATION COEFFICIENTS, COLLISION CROSS-SECTIONS, MAGNETIC-FIELDS, GAS-MIXTURES, TRANSPORT, DISCHARGES, SIMULATION, PLASMAS
- Gazi Üniversitesi Adresli: Evet
Özet
This paper proposes an artificial neural network (ANN) to obtain the electron energy distribution functions (EEDFs) in SF6 and argon from the following: 1) mean energies; 2) the drift velocities; and 3) other related swarm data. In order to obtain the required swarm data, the electron swarm behavior in SF6 and argon is analyzed over the range of the density-reduced electric field strength E/N from 50 to 800 Td from a Boltzmann equation analysis based on the finite difference method under a steady-state Townsend condition. A comparison between the EEDFs calculated by the Boltzmann equation and by ANN for various values of E/N suggests that the proposed ANN yields good agreement of EEDFs with those of the Boltzmann equation solution results.