Assessment of Enthalpy-Based Conditional Moment Closure Models in Predicting Ignition of Lean and Stoichiometric PRF-Air Mixtures with Temperature Inhomogeneity
Accurate prediction of the ignition delay in turbulent flows is important in developing advanced combustion technology for internal combustion engines. Enthalpy-based conditional moment closure (CMC) models are assessed with 2-D direct numerical simulation (DNS) data for ignition of homogeneous PRF-air mixtures with temperature inhomogeneity in homogeneous isotropic turbulence. The sensible-enthalpy-based CMC model is compared with the total-enthalpy-based formulation, with the focus being placed on assessing the capability of the CMC models in predicting ignition processes under different engine conditions. A priori analysis shows that the total-enthalpy-based CMC gives good predictions of the heat release rates in the lean mixtures when the temperature inhomogeneity level is low, but leads to significant overprediction under the stoichiometric condition regardless of the thermal stratification levels. On the other hand, the sensible enthalpy formulation performs well for all conditions considered in this study due to the suppressed conditional temperature fluctuations. A mapping method to model conditional scalar dissipation rates and probability density function of sensible enthalpy is also assessed.