Efficient simulation of chemical reaction in DSMC

TL;DR

This paper introduces a coupling strategy that combines macroscopic equations with DSMC to significantly accelerate chemical reaction simulations in near continuum flows.

Contribution

A novel asymptotic preserving coupling method that reduces computational cost and noise in DSMC simulations of chemical reactions.

Findings

Achieves several orders of magnitude speedup in DSMC simulations.

Supports accurate simulations with coarse grids and fewer sampling steps.

Reduces major computational bottlenecks in near continuum flow simulations.

Abstract

A macroscopic mesoscopic, deterministic stochastic coupling strategy is proposed to accelerate the direct simulation Monte Carlo (DSMC) method for chemical reaction. First, a macroscopic synthetic equation is formulated by integrating continuum constitutive relations for diffusion, stress, and heat flux, along with higher order constitutive relations that capture nonequilibrium transport effects. Second, higher order constitutive relations and chemical reaction source terms are sampled from DSMC and embedded into the macroscopic synthetic equation. Third, the macroscopic system is solved to the steady state, whose solution is then employed to correct particle distributions in DSMC intermittently. This coupling features asymptotic preserving, fast converging and noise reduction properties, supporting efficient, accurate simulations with coarse spatiotemporal grids and reduced evolution/sampling steps. Accordingly, it mitigates major computational bottlenecks of DSMC for near continuum flows by several orders of magnitude.