May 6-8

Abstract Details

files Add files

Abstracts

Author: Joseph R Jepson
Requested Type: Poster
Submitted: 2024-04-11 14:51:29

Co-authors: S. A. Sabbagh, C. C. Hegna, E. D. Held, C. R. Sovinec, A. S. Spencer, E. C. Howell

Contact Info:
Columbia University
100 Stellarator Rd, #213
Princeton, NJ   08540
United States

Abstract Text:
Prediction of the full non-linear dynamics and behavior of many physical processes relevant to the design and operation of future burning plasma devices requires numerical simulation. Some examples of such processes include: disruptions due to Neoclassical Tearing Modes (NTMs) and vertical displacement events (VDEs). Fluid theory provides a relatively simple framework for plasma modeling, however, fluid theory requires closure. In low collisionality regimes, many physical processes become fundamentally kinetic. Incorporating kinetic effects is required to close the fluid system in these regimes. Herein, the numerical stability of a Chapman-Enskog-like (CEL) $delta f$ continuum kinetic closure scheme, implemented in the plasma fluid code NIMROD, is investigated when using multiple Fourier modes in toroidal angle. Previous work has found numerically stable time evolution is possible when running with only one toroidal mode ($n=0$) [1]. The CEL approach specifies that the zeroth order in $delta_i$ distribution function ($delta_i = rho_i / L$, with $rho_i$ the ion gyroradius and $L$ a macroscopic length scale) is a time-evolving Maxwellian. This difference leads to a kinetic equation that analytically enforces that the first order kinetic distortion $f_1$ have zero number density ($n$), flow ($mathbf{u}$), and temperature ($T$) moments. The fluid variables in this method are allowed to deviate far from an initial equilibrium. The fluid equations are closed by incorporating appropriate velocity space moments of $f_1$. Results from this work aim to assess kinetic MHD mode stabilization and NTM entrainment supporting Disruption Event Characterization and Forecasting (DECAF) disruption prediction and avoidance analysis [2].
Supported by DOE Grants DE-SC0021311, DE-FG02-86ER53218, DE-SC0018146, DE-FG02-04ER54746, DE-SC0018001, DE-SC0018313, and DE-FC02-04ER54698.
[1] J. R. Jepson, et al., in review, CPC (2024).
[2] S.A. Sabbagh, et al., Phys. Plasmas 30, 032506 (2023).

Comments: