Predictive modeling of NSTX discharges with the updated multi-mode anomalous transport module
Name
24ja046_full.pdf
Size
1.02 MB
Format
Adobe PDF
Checksum (MD5)
eb93a17147bef3f29fb218cf9d96ed8c
Author(s)
Rafiq, Tariq
Wilson, Christopher
Clauser, Cesar F.
Schuster, Eugenio
Weiland, Jan
Anderson, Johan
Kaye, Stanley M.
Pankin, Alexei
LeBlanc, Benoit P.
Bell, Ronald E.
Date Issued
January 2024
Journal
Nuclear Fusion
Publisher
IOP
Abstract
The objective of this study is twofold: firstly, to demonstrate the consistency between the anomalous transport results produced by updated Multi-Mode Model (MMM) version 9.04 and those obtained through gyrokinetic simulations; and secondly, to showcase MMM's ability to predict electron and ion temperature profiles in low aspect ratio, high beta NSTX discharges. MMM encompasses a range of transport mechanisms driven by electron and ion temperature gradients, trapped electrons, kinetic ballooning, peeling, microtearing, and drift resistive inertial ballooning modes. These modes within MMM are being verified through corresponding gyrokinetic results. The modes that potentially contribute to ion thermal transport are stable in MMM, aligning with both experimental data and findings from linear CGYRO simulations. The isotope effects on these modes are also studied and higher mass is found to be stabilizing, consistent with the experimental trend. The electron thermal power across the flux surface is computed within MMM and compared to experimental measurements and nonlinear CGYRO simulation results. Specifically, the electron temperature gradient modes (ETGM) within MMM account for 2.0 MW of thermal power, consistent with experimental findings. It is noteworthy that the ETGM model requires approximately 5.0 ms of computation time on a standard desktop, while nonlinear CGYRO simulations necessitate 8.0 hours on 8 K cores. MMM proves to be highly computationally efficient, a crucial attribute for various applications, including real-time control, tokamak scenario optimization, and uncertainty quantification of experimental data.
Description
Submitted for publication in Nuclear Fusion
MIT Department
Massachusetts Institute of Technology. Plasma Science and Fusion Center
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1088/1741-4326/ad4d01
