Deep modelling of plasma and neutral fluctuations from gas puff turbulence imaging

Dataset · Wed May 25 00:00:00 EDT 2022

DOI:https://doi.org/10.7910/DVN/WLBOCQ· OSTI ID:1887947

Mathews, A. ^[1]; Terry, J. L.; Baek, S. G.; Hughes, J. W.; Kuang, A. Q.; LaBombard, B.; Miller, M. A.; Zweben, S. J.; Stotler, D.; Reiter, D.; Zholobenko, W.; Goto, M.

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1. OSTI

The role of turbulence in setting boundary plasma conditions is presently a key uncertainty in projecting to fusion energy reactors. To robustly diagnose edge turbulence, we develop and demonstrate a technique to translate brightness measurements of HeI line radiation into local plasma fluctuations via a novel integrated deep learning framework that combines neutral transport physics and collisional radiative theory for the $3^3 D - 2^3 P$ transition in atomic helium. The tenets for experimental validity are reviewed, illustrating that this turbulence analysis for ionized gases is transferable to both magnetized and unmagnetized environments with arbitrary geometries. Based upon fast camera data on the Alcator C-Mod tokamak, we present the first 2-dimensional time-dependent experimental measurements of the turbulent electron density, electron temperature, and neutral density revealing shadowing effects in a fusion plasma using a single spectral line.

• Research Organization: Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Plasma Science and Fusion Center; Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Fusion Energy Sciences (FES)
• DOE Contract Number: SC0014264; SC0014251; AC02-09CH11466
• OSTI ID: 1887947
• Country of Publication: United States
• Language: English

Related Subjects

70 PLASMA PHYSICS AND FUSION TECHNOLOGY