Fluid and kinetic studies of tokamak disruptions using Bayesian optimization
arxiv(2024)
摘要
When simulating runaway electron dynamics in tokamak disruptions, fluid
models with lower numerical cost are often preferred to more accurate kinetic
models. The aim of this work is to compare fluid and kinetic simulations of a
large variety of different disruption scenarios in ITER. We consider both
non-activated and activated scenarios; for the latter we derive and implement
kinetic sources for the Compton scattering and tritium beta decay runaway
electron generation mechanisms in our simulation tool DREAM [M. Hoppe et al
2021 Comp. Phys. Commun. 268, 108098]. To achieve a diverse set of disruption
scenarios, Bayesian optimization is utilized to explore a range of massive
material injection densities for deuterium and neon. The cost function is
designed to distinguish between successful and unsuccessful disruption
mitigation based on the runaway current, current quench time and transported
fraction of the heat loss. In the non-activated scenarios, we find that fluid
and kinetic disruption simulations can have significantly different runaway
electron dynamics, due to an overestimation of the hot-tail generation rate by
the fluid model. The primary cause of this is that the fluid hot-tail
generation model neglects superthermal electron transport losses during the
thermal quench. In the activated scenarios the fluid and kinetic models give
similar predictions, which can be explained by the activated sources'
significant influence on the RE dynamics and the seed.
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