Foley, E. L. (ORCID:0009000317528397)

DOE OSTI2025

Reversed magnetic shear scenario development in NSTX-U using TRANSP

Abstract Understanding and control of electron thermal transport is a critical point of research in magnetic fusion experiments. Previous experiments have shown that operation with reversed magnetic shear (RMS) can suppress electron thermal transport, resulting in the generation of internal transport barriers (ITBs), with the location of the ITB correlated with the location of minimum magnetic shear. The recent upgrades to NSTX—increased magnetic field up to 1 T, increased plasma current up to 2 MA, 2nd neutral beam—present an increased operating space in which to explore electron thermal transport in RMS plasmas. Utilizing TRANSP, we have developed operating scenarios by which to generate RMS in NSTX-U. The results suggest that RMS in NSTX-U can be generated through fast current ramp and early beam injection into a large plasma volume. This is very similar to the procedure that was followed in both TFTR and NSTX to generate RMS. Sustainment of RMS, disregarding non-( q min = 1) MHD events, requires maintaining a large plasma volume, and increasing the core T e , either via increased plasma current and/or adding heating power. Using this procedure, RMS was sustained for ∼1 s, with q min > 1 for that period.

Galante, M. E. (ORCID:0009000098149425)↗

DOE OSTI2024

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

Uzun-Kaymak, I. U. (ORCID:0000000276251493)↗