Abstract
Integrated modelling of electron runaway requires computationally expensive kinetic models that are self-consistently coupled to the evolution of the background plasma parameters. The computational expense can be reduced by using parameterized runaway generation rates rather than solving the full kinetic problem. However, currently available generation rates neglect several important effects; in particular, they are not valid in the presence of partially ionized impurities. In this work, we construct a multilayer neural network for the Dreicer runaway generation rate which is trained on data obtained from kinetic simulations performed for a wide range of plasma parameters and impurities. The neural network accurately reproduces the Dreicer runaway generation rate obtained by the kinetic solver. By implementing it in a fluid runaway-electron modelling tool, we show that the improved generation rates lead to significant differences in the self-consistent runaway dynamics as compared to the results using the previously available formulas for the runaway generation rate.
Highlights
If the electric field exceeds a critical field in plasmas, the accelerating force on fast electrons overcomes the collisional friction
To demonstrate the impact of the modified Dreicer generation rates, we use the neural network in a self-consistent simulation of the electric field and current profile evolution performed by the GO numerical tool (Smith et al 2006)
Runaway acceleration of particles occurring in plasmas with strong electric fields has been studied for more than a century, but only recently has it become possible to perform kinetic simulations in complex scenarios
Summary
If the electric field exceeds a critical field in plasmas, the accelerating force on fast electrons overcomes the collisional friction. Until simulations of the full plasma evolution during a disruption can be realized, as an intermediate step, transport codes and equilibrium solvers could be coupled with analytical formulas for runaway generation rates This means that instead of evolving the full runaway-electron distribution, only key quantities such as the runaway number density would be considered and computed from the instantaneous electric field and background plasma parameters. In such fluid models, the runaway-electron density evolves by analytical generation rates describing Dreicer, hot-tail and avalanche generation, as well as tritium decay and Compton scattering of γ -rays (which can be emitted by the activated wall in the nuclear phase of tokamak operation). We discuss the applications of the model as well as possible improvements (§ 5)
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