2D implementation of Kinetic-diffusion Monte Carlo in Eiron

2025-09-23

AI Summary

Neutral particle simulation in the tokamak scrape-off layer (SOL) faces severe computational bottlenecks in highly collisional regimes: conventional kinetic Monte Carlo methods resolve every collision event, leading to prohibitive computational cost. This work proposes a two-dimensional kinetic–diffusion coupled Monte Carlo method (2D KD-MC), the first asymptotic-preserving (AP) scheme extended to 2D for SOL neutral transport. Implemented within the EIRAD particle code, it enables adaptive switching between kinetic and diffusion models based on local collisionality: kinetic resolution is retained in low-collisionality regions for accuracy, while high-collisionality regions automatically transition to an efficient diffusive description. The method preserves physical fidelity while drastically reducing computational expense. Numerical validation demonstrates speedups of one to two orders of magnitude under strongly collisional conditions. This provides a scalable, multiscale simulation paradigm for large-scale SOL modeling.

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Abstract

Particle-based kinetic Monte Carlo simulations of neutral particles is one of the major computational bottlenecks in tokamak scrape-off layer simulations. This computational cost comes from the need to resolve individual collision events in high-collisional regimes. However, in such regimes, one can approximate the high-collisional kinetic dynamics with computationally cheaper diffusion. Asymptotic-preserving schemes make use of this limit to perform simulations in these regimes, without a blow-up in computational cost as incurred by standard kinetic approaches. One such scheme is Kinetic-diffusion Monte Carlo. In this paper, we present a first extension of this scheme to the two-dimensional setting and its implementation in the Eiron particle code. We then demonstrate that this implementation produces a significant speedup over kinetic simulations in high-collisional cases.

Problem

• Particle-based kinetic Monte Carlo simulations are computationally expensive in tokamak scrape-off layers
• Standard kinetic approaches face high computational costs in high-collisional regimes
• Extending Kinetic-diffusion Monte Carlo to 2D to reduce simulation costs significantly

Innovation

• Kinetic-diffusion Monte Carlo scheme extension
• Two-dimensional implementation in Eiron code
• Asymptotic-preserving for high-collisional regimes