Validation of the static forward Grad-Shafranov equilibrium solvers in FreeGSNKE and Fiesta using EFIT++ reconstructions from MAST-U
K. Pentland, N.C. Amorisco, O. El-Zobaidi, S. Etches, A. Agnello, G., K. Holt, A. Ross, C. Vincent, J. Buchanan, S. J. P. Pamela, G. McArdle, L., Kogan, G. Cunningham

TL;DR
This paper validates the static forward Grad-Shafranov equilibrium solvers in FreeGSNKE and Fiesta by comparing their results with EFIT++ reconstructions from MAST-U, demonstrating high accuracy and providing open access to the code and data.
Contribution
The paper introduces a validation pipeline for FreeGSNKE and Fiesta against real MAST-U equilibria, ensuring their reliability for MHD equilibrium modeling.
Findings
Both solvers accurately reproduce poloidal flux quantities.
High agreement with EFIT++ reconstructions across multiple shots.
Open source code and data for reproducibility.
Abstract
A key aspect in the modelling of magnetohydrodynamic (MHD) equilibria in tokamak devices is having access to fast, accurate, and stable numerical simulation methods. There is an increasing demand for reliable methods that can be used to develop traditional or machine learning-based shape control feedback systems, optimise scenario designs, and integrate with other plasma edge or transport modelling codes. To handle such applications, these codes need to be flexible and, more importantly, they need to have been validated against both analytically known and real-world tokamak equilibria to ensure they are consistent and credible. In this paper, we are interested in solving the static forward Grad-Shafranov (GS) problem for free-boundary MHD equilibria. Our focus is on the validation of the static forward solver in the Python-based equilibrium code FreeGSNKE by solving equilibria from…
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Taxonomy
TopicsNuclear Physics and Applications · Nuclear reactor physics and engineering · Magnetic confinement fusion research
