Coupling of state-resolved rovibrational coarse-grain model for nitrogen to stochastic particle method for simulating internal energy excitation and dissociation

Abstract

We propose to couple a state-resolved rovibrational coarse-grain model to a stochastic particle method for simulating internal energy excitation and dissociation of a molecular gas. An existing coarse-grain model based on the NASA Ames ab initio database for the N2-N system is modified using variably-spaced energy bins. Thermodynamic properties of the new coarse-grained model closely match those of the full set of rovibrational levels over a wide temperature range, using a number of bins much smaller than the complete mechanism. The chemical-kinetic behavior of the original equally -- and new variably -- spaced bin formulations is compared by simulating excitation and dissociation of N2 in an adiabatic, isochoric reactor. The variably-spaced formulation is better suited for reproducing the dynamics of the full database at conditions of interest in Earth reentry. Furthermore, we discuss details of our Direct Simulation Monte Carlo (DSMC) implementation for the coarse-grain model and describe changes to the collision algorithm necessary to accommodate our state-resolved reaction mechanism. The DSMC code is then verified against equivalent master equation (ME) calculations. In these simulations, state-resolved cross sections are used in analytical form. They verify micro-reversibility for the bins and allow for faster execution of the code. In our verification, we obtain very close agreement for the N and N2 concentrations, as well as the translational and rovibrational mode temperatures obtained independently using both methods. In addition to macroscopic moments, we compare internal energy populations predicted at selected time steps via DSMC and ME. We observe good agreement between both methods within the statistical scatter limits imposed by DSMC. In future work, the rovibrational coarse-grain model coupled to the particle method will allow us to study 3D reentry flow configurations.