DNS-driven analysis of the Flamelet/Progress Variable model assumptions on soot inception, growth, and oxidation in turbulent flames

Abstract Modeling suites for Large-Eddy Simulations of soot evolution in turbulent flames include a number of submodels describing the chemistry of soot precursors, particle dynamics, heterogeneous soot chemistry, turbulent mixing, and combustion. To understand the reasons for model failure and to enhance the overall model performance, it is necessary to identify and subsequently improve model components with a leading order effect on the overall error. In this work, errors in soot predictions associated with flamelet-based combustion models are isolated and quantified in a combined a-priori and partial a-posteriori analysis using large-scale Direct Numerical Simulation (DNS) data of a sooting turbulent jet diffusion flame. Gas-phase quantities entering the calculation of the soot source terms and hence coupling the combustion model to the soot model are analyzed in the DNS first. The performance of a Flamelet/Progress Variable model with respect to these quantities is then analyzed a-priori for two DNS cases employing a mixture-averaged transport model and unity Lewis numbers. Then, the soot evolution along Lagrangian trajectories extracted from the DNS is re-computed using rate coefficients directly taken from the DNS and from the flamelet table. In the context of this partial a-posteriori analysis, flamelet-induced errors are also compared to errors induced by the chemical soot model. The soot surface growth and oxidation rate coefficients are reasonably well predicted by the flamelet library. Considerably larger errors in the model-predicted soot mass originate from the tabulated quantities entering the calculation of PAH-based soot growth rates. However, these errors can be reduced to a few percent if the rate is appropriately scaled with the mass fraction of polycyclic aromatic hydrocarbons (PAH). However, this requires the solution of a transport equation for the PAH mass fraction, and modeling the source term in this equation is shown to be challenging. Overall, the largest uncertainties can be attributed to the chemical mechanism for PAH formation and the model for the PAH source term.