Sensitivity of predictions to chemical kinetics models in a temporally evolving turbulent non-premixed flame

To investigate the sensitivity of predictions to chemical kinetics models, two different kinetics models, GRI-Mech 3.0 and an 11-species syngas model, are compared by performing 3D finite-rate kinetics-based direct numerical simulations (DNS) of a temporally evolving turbulent non-premixed syngas flame. Dynamic adaptive chemistry and correlated transport techniques are applied to enable computationally efficient simulation with the detailed GRI-Mech 3.0. Both chemical kinetics models, providing comparable qualitative trends, capture local extinction and re-ignition events. However, significant quantitative discrepancies (86–100 K difference in the temperature field) indicate high sensitivity to the chemical kinetics model. The 11-species model predicts a lower radicals-to-products conversion rate, causing statistically more local extinction and less re-ignition. This sensitivity to the chemical kinetics model is magnified relative to a 1D steady laminar simulation by the effects of unsteadiness and turbulence (up to 7 times for temperature, up to 12 times for CO, up to 13 times for H2, up to 7 times for O2, up to 5 times for CO2, and up to 13 times for H2O), with the deviations in species concentrations, temperature, and reaction rates forming a nonlinear positive feedback loop under reacting flow conditions. The differences between the results from the two models are primarily due to: (a) the larger number of species and related kinetic pathways in GRI-Mech 3.0; and (b) the differences in reaction rate coefficients for the same reactions in the two models. Both (a) and (b) are sensitive to unsteadiness and other turbulence effects, but (b) is dominant and is more sensitive to unsteadiness and other turbulence effects. At local extinction, the major differences between the results from the two chemical kinetics models are in the peak values and the volume occupied by the peak values, which is dominated by unsteady effects; at re-ignition, the differences are mainly observed in the spatial distribution of the reacting flow field, which is primarily dominated by the complex turbulence–chemistry interaction.