Physics-informed machine learning techniques for edge plasma turbulence
modelling in computational theory and experiment
- URL: http://arxiv.org/abs/2205.07838v1
- Date: Mon, 16 May 2022 17:46:14 GMT
- Title: Physics-informed machine learning techniques for edge plasma turbulence
modelling in computational theory and experiment
- Authors: Abhilash Mathews
- Abstract summary: Edge plasma turbulence is critical to the performance of magnetic confinement fusion devices.
This thesis presents the first 2-dimensional time-dependent experimental measurements of the turbulent electron density, electron temperature, and neutral density in a fusion plasma.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Edge plasma turbulence is critical to the performance of magnetic confinement
fusion devices. Towards better understanding edge turbulence in both theory and
experiment, a custom-built physics-informed deep learning framework constrained
by partial differential equations is developed to accurately learn turbulent
fields consistent with the two-fluid theory from partial observations of
electron pressure. This calculation is not otherwise possible using
conventional equilibrium models. With this technique, the first direct
quantitative comparisons of turbulent fields between electrostatic two-fluid
theory and electromagnetic gyrokinetic modelling are demonstrated with good
overall agreement found in magnetized helical plasmas at low normalized
pressure.
To translate these computational techniques to experimental fusion plasmas, a
novel method to translate brightness measurements of HeI line radiation into
local plasma fluctuations is demonstrated via a newly created deep learning
framework that integrates neutral transport physics and collisional radiative
theory for the $3^3 D - 2^3 P$ transition in atomic helium. Using fast camera
data on the Alcator C-Mod tokamak, this thesis presents the first 2-dimensional
time-dependent experimental measurements of the turbulent electron density,
electron temperature, and neutral density in a fusion plasma using a single
spectral line. With this experimentally inferred data, initial estimates of the
2-dimensional turbulent electric field consistent with drift-reduced Braginskii
theory under the framework of an axisymmetric fusion plasma with purely
toroidal field are calculated. The inclusion of atomic helium effects on
particle and energy sources are found to strengthen correlations between the
electric field and electron pressure while broadening turbulent field
amplitudes which impact ${\bf E \times B}$ flows and shearing rates.
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