Improvements to EFIT in Preparation for the Burning Plasma Era

POSTER

Abstract

EFIT was the first and is the most extensively used equilibrium reconstruction code in the world. Although robust, the burning plasma regime will bring new challenges which include adapting to novel operating regimes and incorporating diagnostics that can withstand a harsh, radioactive environment. This regime has motivated the exploration of machine learning techniques to improve the quality of equilibrium reconstructions that can be produced in real-time. To support this development, we are upgrading the core Grad-Shafranov solver. The improvements include clearly separating out the device-specific coding, enhancing code portability, and ensuring thread-safety in preparation for GPU developments. To aid in the development, we have created a test suite for use with continuous integration workflows.

*This material is based upon work supported by the Department of Energy under Award Number(s) DE-SC0021203.

Presenters

  • Torrin A Bechtel

    • ORAU, GA
    • Orau
    • General Atomics / ORAU
    • University of Wisconsin - Madison

Authors

  • Torrin A Bechtel

    • ORAU, GA
    • Orau
    • General Atomics / ORAU
    • University of Wisconsin - Madison
  • Joseph T Mcclenaghan

    • General Atomics
    • General Atomics - San Diego
    • Oak Ridge National Laboratory
  • Cihan Akcay

    • General Atomics
  • Lang L Lao

    • General Atomics - San Diego
    • General Atomics
  • Scott E Kruger

    • Tech-X Corp
    • Tech-X
  • Eric C Howell

    • Tech-X Corp
  • Jarrod Leddy

    • Tech-X Corp
    • Tech-X
  • Matthew Leinhauser

    • LBNL
    • LBNL, UDEL
    • Lawrence Berkeley National Laboratory
  • Samuel W Williams

    • LBNL
    • Lawrence Berkeley National Laboratory