Description
This presentation addresses recent work at the TCV tokamak aimed at a better characterization and understanding of the dynamics of the burn-through phase leveraging on both experiments and simulations. In particular, the conditions giving rise to a significant amount of fast electrons during the startup phase has come under scrutiny [1]. After developing a robust startup scenario with strong fast-electron signals, scans in pre-breakdown gas pressure as well as post-breakdown gas fuelling amplitude and timing have been performed. This study benefits from a rich gamut of fast-electron diagnostics including low-field side and vertical ECE as well as multiple X-ray diagnostics both inside and outside the vessel.
It is observed that prefill pressure changes can have a significant effect on the early burn-through plasma and fast-electron signals but do not lead to significant changes in the flat-top fast-electron population. Gas fueling scans revealed that the plasma density has a direct impact on the onset of fast electron signals and can thus be used as an active control knob to avoid startup fast electrons. However, both the amount and timing of the application of external fuelling are important.
These experimental scans are modelled by the 0D burn-through code STREAM [2]. This code solves for energy and particle balance fluid equations in 0D including a basic circuit equation and impurities. STREAM includes a state-of-the-art model for the generation and loss of runaway electrons consistent with the presence of partially ionized impurities during the burn-through phase. New observables such as Langmuir probe data to quantify the open-closed field line transition, early ion temperature measurements, and fast-camera measurements of the early plasma volume allow to constrain simulation input parameters and better validate the modeling results. Simulations are underway to determine whether the experimental scans can be reproduced in the simulations by varying exclusively the prefill and/or fueling trajectories. These efforts pave the way towards using burn-through simulations predictively [3].
[1] de Vries P. et al., Nucl. Fus. Vol 63, Issue 8 (2023)
[2] Hoppe M. et al., J. Plasma Phys. Vol 88, Isue 3 (2022)
[3] Kim H.-T. et al., Nucl. Fus., Vol 62, Issue 12 (2022)
** See authors list of B. P. Duval et al., 2024, Nucl. Fusion 64 112023