Speaker
Description
Runaway Electrons (REs) generated during disruption events pose a critical challenge for the operation of next-generation fusion devices such as DEMO. The thermal quench causes intense heat and particle loads on plasma-facing components (PFCs), while the current quench can induce a strong toroidal electric field that accelerates electrons to relativistic energies. A detailed understanding of how REs deposit their energy on PFCs is therefore crucial to proper design the reactor plasma-facing components.
This work presents a systematic predictive modelling approach based on the FLUKA Monte Carlo code [1] to quantify RE energy deposition under DEMO-relevant conditions. A comprehensive look-up table is built by performing a parametric scan over four key variables: electron kinetic energy, pitch angle, magnetic field intensity, and magnetic incidence angle on the solid surface. The explored energy range was identified through RE distribution function calculations on DEMO disruption simulations, considering intrinsic argon impurities.
The study first considers a reference configuration consisting of a flat tungsten monoblock, where both the total deposited energy and the depth at which 90% of the energy is absorbed are evaluated. RE impact on the surface is analysed systematically to identify the influence of each parameter on the deposited energy. The methodology is then extended to a shaped limiter geometry. This allows assessment of the role of geometrical effects, by performing a detailed comparison with the reference case.
The results suggest that the pitch angle may have a notable influence on the interaction between REs and PFCs. For identical electron energies and magnetic field parameters, small pitch angles lead to significantly higher loads. Under the worst-case conditions, more than 90% of the RE incident energy is deposited in the W target, and electrons can deliver a considerable amount of energy up to a depth of 25 mm. These insights provide a solid basis for predicting RE-induced loads and for optimising the PFC design and mitigation strategies.
References:
[1] A. Ferrari, P.R. Sala, A. Fassò, and J. Ranft (2005). FLUKA: A Multi-Particle Transport Code. CERN-2005-010, INFN/TC_05/11, SLAC-R-773.