CFD simulations of reacting flows are fundamental investigation tools used to predict combustion behaviour and pollutants formation in modern internal combustion engines. Focusing on spark-ignited units, most of the flamelet-based combustion models adopted in current simulations use the fuel/air/residual laminar flame propagation speed as a background to predict the turbulent flame speed. This, in turn, is a fundamental requirement to model the effective burn rate.
A consolidated approach in engine combustion simulations relies on the adoption of empirical correlations for laminar flame speed, which are derived from fitting of combustion experiments. However, these last are conducted at pressure and temperature ranges largely different from those encountered in engines: for this reason, correlation extrapolation at engine conditions is inevitably accepted. As a consequence, relevant differences between proposed correlations emerge even for the same fuel and conditions. The lack of predictive chemistry-grounded correlations leads to a wide modelling uncertainty, often requiring an extensive model tuning when validating combustion simulations against engine experiments.
In this paper a fitting form based on fifth order logarithmic polynomials is applied to reconstruct correlations for a set of Toluene Reference Fuels (TRFs), namely iso-octane, n-heptane, toluene and for a commercial gasoline fuel surrogate. Experimental data from literature are collected as well as existing computations for laminar flame speed. These last are extended up to full-load engine-relevant conditions, where experiments are not available; they constitute a model-based prediction of flame behaviour at such states. The mentioned literature and calculated data, which are shown to be representative of a wide range of engine-typical operating points, constitute the target values for the fitting polynomials.
The model-based correlations of this study constitute a reference to increase the accuracy of flamelet combustion simulations, and to reduce the modelling approximations when dealing with full-load engine operations.