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A. Bruncrona

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Preprint Aug 2026

Machine learning methods for modelling local, linear gyrokinetic simulations of MAST-U pedestal turbulence

Gyrokinetic (GK) stability strongly influences the performance of high-confinement-mode pedestals in spherical tokamak plasmas. High-fidelity gyrokinetic codes such as GENE can model microinstability-driven transport, but the computational cost limits their routine use in integrated pedestal modeling workflows. Instead...

A. Niemelä, D. Jordan, A. Järvinen et al. · 0 citations

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