Machine learning-aided line intensity ratio technique applied to deuterium plasmas

Nishijima, D.; Baldwin, M. J.; Chang, F.; Tynan, G. R.

doi:10.1063/5.0147463

Machine learning-aided line intensity ratio technique applied to deuterium plasmas

Journal Article · Tue May 02 00:00:00 EDT 2023 · AIP Advances

DOI:https://doi.org/10.1063/5.0147463· OSTI ID:1972220

^[1]; ^[2]; ^[2]; Tynan, G. R. ^[2]

Univ. of California San Diego, La Jolla, CA (United States); University of California San Diego
Univ. of California San Diego, La Jolla, CA (United States)

It has been demonstrated that the electron density, n_e, and temperature, T_e, are successfully evaluated from He I line intensity ratios coupled with machine learning (ML). In this paper, the ML-aided line intensity ratio technique is applied to deuterium (D) plasmas with 0.031 < n_e (10¹⁸ m^–3) < 0.67 and 2.3 < T_e (eV) < 5.1 in the PISCES-A linear plasma device. Two line intensity ratios, D_α/D_γ and D_α/D_β, are used to develop a predictive model for n_e and T_e separately. Reasonable agreement of both ne and Te with those from single Langmuir probe measurements is obtained at n_e > 0.1 × 10¹⁸ m^–3. Addition of the D₂/D_α intensity ratio, where the D₂ band emission intensity is integrated in a wavelength range of λ ~ 557.4–643.0 nm, is found to improve the prediction of, in particular, n_e, and T_e. It is also confirmed that the technique works for D plasmas with 0.067 < n_e (10¹⁸ m^–3) < 6.1 and 0.8 < T_e (eV) < 15 in another linear plasma device, PISCES-RF. The two training datasets from PISCES-A and PISCES-RF are combined, and unified predictive models for n_e and T_e give reasonable agreement with probe measurements in both devices.

View Accepted Manuscript (DOE)

Research Organization:: Univ. of California San Diego, La Jolla, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Fusion Energy Sciences (FES)

Grant/Contract Number:: FG02-07ER54912; SC0022528

OSTI ID:: 1972220

Journal Information:: AIP Advances, Journal Name: AIP Advances Journal Issue: 5 Vol. 13; ISSN 2158-3226

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

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