U.S. Department of EnergyOffice of Scientific and Technical Information
Deep electric field predictions by drift-reduced Braginskii theory with plasma-neutral interactions based upon experimental images of boundary turbulence
Abstract
We present 2-dimensional turbulent electric field calculations via physics-informed deep learning consistent with (i) drift-reduced Braginskii theory under the framework of an axisymmetric fusion plasma with purely toroidal field and (ii) experimental estimates of the fluctuating electron density and temperature obtained from analysis of gas puff imaging of a discharge on the Alcator C-Mod tokamak. The inclusion of effects from the locally puffed atomic helium on particle and energy sources within the reduced plasma turbulence model are found to strengthen correlations between the electric field and electron pressure. The neutrals are also directly associated with an observed broadening in the distribution of turbulent field amplitudes and increased E×B shearing rates.
- Authors:
- Publication Date:
- DOE Contract Number:
- SC0014264; SC0014251
- Research Org.:
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Plasma Science and Fusion Center
- Sponsoring Org.:
- USDOE Office of Science (SC), Fusion Energy Sciences (FES)
- Subject:
- 70 PLASMA PHYSICS AND FUSION TECHNOLOGY
- OSTI Identifier:
- 1887953
- DOI:
- https://doi.org/10.7910/DVN/EFXCPW
Citation Formats
Mathews, Abhilash, Hughes, Jerry, Terry, James, and Baek, Seung-Gyou. Deep electric field predictions by drift-reduced Braginskii theory with plasma-neutral interactions based upon experimental images of boundary turbulence. United States: N. p., 2022.
Web. doi:10.7910/DVN/EFXCPW.
Mathews, Abhilash, Hughes, Jerry, Terry, James, & Baek, Seung-Gyou. Deep electric field predictions by drift-reduced Braginskii theory with plasma-neutral interactions based upon experimental images of boundary turbulence. United States. doi:https://doi.org/10.7910/DVN/EFXCPW
Mathews, Abhilash, Hughes, Jerry, Terry, James, and Baek, Seung-Gyou. 2022.
"Deep electric field predictions by drift-reduced Braginskii theory with plasma-neutral interactions based upon experimental images of boundary turbulence". United States. doi:https://doi.org/10.7910/DVN/EFXCPW. https://www.osti.gov/servlets/purl/1887953. Pub date:Mon Jun 06 00:00:00 EDT 2022
@article{osti_1887953,
title = {Deep electric field predictions by drift-reduced Braginskii theory with plasma-neutral interactions based upon experimental images of boundary turbulence},
author = {Mathews, Abhilash and Hughes, Jerry and Terry, James and Baek, Seung-Gyou},
abstractNote = {We present 2-dimensional turbulent electric field calculations via physics-informed deep learning consistent with (i) drift-reduced Braginskii theory under the framework of an axisymmetric fusion plasma with purely toroidal field and (ii) experimental estimates of the fluctuating electron density and temperature obtained from analysis of gas puff imaging of a discharge on the Alcator C-Mod tokamak. The inclusion of effects from the locally puffed atomic helium on particle and energy sources within the reduced plasma turbulence model are found to strengthen correlations between the electric field and electron pressure. The neutrals are also directly associated with an observed broadening in the distribution of turbulent field amplitudes and increased E×B shearing rates.},
doi = {10.7910/DVN/EFXCPW},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2022},
month = {6}
}