Stochastic and self-consistent 3D modeling of streamer discharge trees with Kinetic Monte Carlo

TL;DR

This paper introduces a novel particle-in-cell model for gas discharges using Ito diffusion and Kinetic Monte Carlo, enabling stable, fluctuation-inclusive simulations of complex streamer discharge trees in air.

Contribution

It presents a new microscopic electron model coupled with photoionization, offering enhanced stability and fluctuation support over traditional fluid models.

Findings

Successfully simulated large streamer discharge trees in air.

Demonstrated stability and non-negativity in discharge simulations.

Integrated kinetic Monte Carlo with particle-mesh methods for gas discharges.

Abstract

This paper contains the foundation for a new Particle-In-Cell model for gas discharges, based on Ito diffusion and Kinetic Monte Carlo (KMC). In the new model the electrons are described with a microscopic drift-diffusion model rather than a macroscopic one. We discuss the connection of the Ito-KMC model to the equations of fluctuating hydrodynamics and the advection-diffusion-reaction equation which is conventionally used for simulating streamer discharges. The new model is coupled to a particle description of photoionization, providing a non-kinetic all-particle method with several attractive properties, such as: 1) Taking the same input as a fluid model, e.g. mobility coefficients, diffusion coefficients, and reaction rates. 2) Guaranteed non-negative densities. 3) Intrinsic support for reactive and diffusive fluctuations. 4) Exceptional stability properties. The model is implemented as a particle-mesh model on cut-cell grids with Cartesian adaptive mesh refinement. Positive streamer discharges in atmospheric air are considered as the primary application example, and we demonstrate that we can self-consistently simulate large discharge trees.