Self-consistent modelling and qualitative comparison of mildly relativistic runaway electron dynamics with a closed flux surface formation model during tokamak startup

TL;DR

This paper introduces a self-consistent model for mildly relativistic runaway electrons integrated into a plasma initiation code, improving predictions of runaway electron behavior during tokamak startup.

Contribution

The novel DYON-RE model accounts for relativistic effects and flux surface formation, enhancing the accuracy of runaway electron predictions during tokamak startup.

Findings

DYON-RE accurately predicts plasma current, density, and temperature.

The model aligns with observed radiative temperature behaviors.

It offers a framework for designing runaway-free startup scenarios.

Abstract

A model for mildly relativistic Runaway Electrons (REs) is developed in a reduced-kinetic form and qualitatively compared with radiation characteristics observed in KSTAR ohmic startup. The mildly relativistic correction not only alleviates runaway current overestimation but also accounts for the partial parallel confinement of the initial runaway seed under an open-field configuration during early burn-through. The model is self-consistently integrated in the state-of-the-art predictive plasma initiation code DYON (Hyun-Tae Kim et al 2022 Nucl. Fusion 62 126012), hereafter referred to as DYON-RE. DYON-RE provides an improved RE confinement model during the transition from an open to a closed magnetic configuration by employing a model-based description of closed flux surface formation validated in multi machines. We show prediction capability of DYON-RE in two representative discharges among KSTAR ohmic startups. DYON-RE reliably predicts key plasma parameters such as plasma current, density, and temperature and also implies the characteristic behavior of the radiative temperature measured by electron cyclotron emission diagnostics in agreement with experimental results. The proposed model offers a framework for designing runaway-free ohmic startup scenarios in CPD and ITER. Future experimental validation will further refine its predictive capabilities and broaden its practical application.