Numerical modeling of laminar flame speed and autoignition delay using general fuel-independent function

•Procedure for generation of laminar flame speed and autoignition data bases.•Laminar flame speed features lognormal distribution in equivalence ratio direction.•Validation of results from chemical reactors against available experimental data.•Predictions of autoignition timing is verified against detailed chemical mechanism.•Developed procedure applied to an e-fuel (OME-3) combustion process. The impact of the transport sector on climate change and carbon dioxide emissions into the atmosphere can be decreased by the utilization of biofuels and e-fuels. The chemical kinetics for calculating the combustion process of new biofuels and e-fuels is often excessively computationally demanding for numerical simulations, leading to the development and employment of combustion models, such as flamelet models. Such models require precalculated data of laminar flame speed and autoignition timing. The developed procedure in this work scrutinizes available reaction mechanisms of several fuels with the validation against existing experimental data of autoignition and laminar flame velocities, aiming for the generation of lookup databases. The autoignition of fuel/air mixtures for different conditions is pre-tabulated from nondimensional calculations of constant pressure reactor. Simultaneously, the laminar flame speed is pre-tabulated from premixed freely propagating reactors, for which calculation chemical kinetics software are applied. The ignition delay of cold flame and primary ignition was calculated using inflection point criteria implemented in the proposed method. The developed imputations method is based on the lognormal distribution for laminar flame speed in equivalence ratio direction and exponential functions for pressure, temperature, and exhaust gas recirculation directions. The laminar flame speed and autoignition databases generation procedure was demonstrated on prospective e-fuel three-oxyethylene dimethyl ether (OME-3) fuel by validating the available mechanism against the experimental data. Finally, the generated databases are implemented into the computational fluid dynamics software and verified with the detailed chemical mechanism of OME-3 fuel.