Deep electric field predictions by drift-reduced Braginskii theory with plasma-neutral interactions based upon experimental images of boundary turbulence

• URL: http://arxiv.org/abs/2204.11689v1
• Date: Mon, 25 Apr 2022 14:25:55 GMT
• Title: Deep electric field predictions by drift-reduced Braginskii theory with plasma-neutral interactions based upon experimental images of boundary turbulence
• Authors: Abhilash Mathews and Jerry Hughes and James Terry and Seung-Gyou Baek
• Abstract summary: We present 2-dimensional turbulent electric field calculations via physics-informed deep learning. The inclusion of effects from the locally atomic helium on particle and energy sources are found to strengthen correlations between the electric field and electron pressure.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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 ${\bf E \times B}$ shearing rates.

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