Description
Runaway electrons (REs) pose a significant threat to the safe operation and component lifetime of future high-performance tokamaks such as ITER. During plasma disruptions, REs can be generated and multiplied via the avalanche mechanism, potentially causing serious damage to the first wall and in-vessel structures, especially if the REs replace the bulk electrons as the main current carriers. One approach to avoid such current replacement is to deplete the seed REs through stochastic trajectory loss before avalanche multiplication can develop.
In this work, we investigate the stochastic transport of seed REs in ITER disruption mitigation scenarios using guiding-center simulations with conservative high-order magnetic moments [1]. The simulations are performed with PTC [2] and employ 3D fluid magnetic fields generated by JOREK [3]. We focus on several ITER plasmas after Shattered Pellet Injection (SPI) with different injection schemes, which exhibit flux-surface breakup and subsequent healing, and analyze the evolution of RE transport behaviors as magnetic stochasticity develops.
Consistent with previous findings [4], a self-similar radial density profile of seed REs is observed for each plasma scenario. This profile consistent with the eigen-solution of the radial diffusion equation, providing evidence for eigen-mode dominated diffusive transport. By statistically evaluating the diffusion coefficients from particle simulations, we analyze the characteristic loss time of seed REs and show that it is primarily governed by the edge diffusion coefficient. This result indicates that injection schemes capable of producing stronger edge diffusion can deplete REs more efficiently, even when the volume-averaged diffusion coefficient is relatively lower. The Chirikov overlap parameter is found to be a reasonable indicator of whether or not the stochastic RE transport could be well descripted by diffusion-dominated or advection-dominated model. Finally, using a realistic 3D wall, we simulate the deposition pattern of REs on the first wall to estimate the impact of RE deposition.
Understanding the transport and deposition patterns offers valuable insights for optimizing mitigation techniques and protecting plasma-facing components from localized RE impacts.