Validation of simulated radiative collapse events in TORAX

POSTER

Abstract

We present simulations of radiative collapse events using the TORAX [1] transport simulator, and the first validation against radiative collapse events on Alcator C-Mod. The SIMulation of Off-Normal events (ONSIMs), e.g. radiative collapses, is a new area of time-dependent plasma simulation that has the potential to explore the disruptive chains-of-events, provide synthetic data for disruption prediction algorithms, and stress-test the Plasma Control System within a simulated environment. The validity of these radiative collapse simulations is investigated by comparing the radiated power, kinetic profile, and impurity concentration evolution predicted by TORAX using real C-Mod equilibrium data (and constrained by impurity profile measurements) to those observed on C-Mod.C-Mod equilibria are provided via the newly introduced helper framework [2].Multiple types of radiative collapses are investigated, including core impurity accumulation (temperature hollowing) and edge collapses, along with non-disruptive injections that can help to identify disruptive limits. Through these validations, disruptive concentrations of impurities can be identified and a library of impurity source time-traces can be collated and used to create realistic off-normal events in the simulation of new, unexplored operating scenarios.

[1] J. Citrin et al, https://arxiv.org/abs/2406.06718

[2] G.L. Trevisan et al, APS-DPP 2025

*Work funded by Commonwealth Fusion Systems.

Presenters

  • Alex R Saperstein

    • Massachusetts Institute of Technology

Authors

  • Alex R Saperstein

    • Massachusetts Institute of Technology
  • Jonathan Citrin

    • Google DeepMind
  • Aaron Ho

    • MIT
    • MIT PSFC
    • Massachusetts Institute of Technology
  • Ryan M Sweeney

    • Commonwealth Fusion Systems
  • Conor J Perks

    • Massachusetts Institute of Technology
  • Dan D Boyer

    • Commonwealth Fusion Systems
  • Federico Felici

    • Google DeepMind
  • Gregorio L Trevisan

    • Massachusetts Institute of Technology
  • Cristina Rea

    • Massachusetts Institute of Technology