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Nowadays, detailed kinetics is necessary for a proper estimation of both flame structure and pollutant formation in compression ignition engines. However, large mechanisms and the need to include turbulence/chemistry interaction introduce significant computational overheads. For this reason, tabulated kinetics is employed as a possible solution to reduce the CPU time even if table discretization is generally limited by memory occupation. In this work the authors applied tabulated homogeneous reactors (HR) in combination with different turbulent-chemistry interaction approaches to model non-premixed turbulent combustion. The proposed methodologies represent good compromises between accuracy, required memory and computational time. The experimental validation was carried out by considering both constant-volume vessel and Diesel engine experiments.

Detailed chemistry represents a fundamental pre-requisite for a realistic simulation of combustion process in Diesel engines to properly reproduce ignition delay and flame structure (lift-off and soot precursors) in a wide range of operating conditions. In this work, the authors developed reduced mechanisms for n-dodecane starting from the comprehensive kinetic mechanism developed at Politecnico di Milano, well validated and tested in a wide range of operating conditions [1]. An algorithm combining Sensitivity and Flux Analysis was employed for the present skeletal reduction. The size of the mechanisms can be limited to less than 100 species and incorporates the most important details of low-temperature kinetics for a proper prediction of the ignition delay. Furthermore, the high-temperature chemistry is also properly described both in terms of reactivity and species formation, including unsaturated compounds such as acetylene, whose concentration controls soot formation.

In the rapidly changing scenario of the energy transition, data-driven tools for kinetic mechanism development and testing can greatly support the evaluation of the combustion properties of new potential e-fuels. Despite the effectiveness of kinetic mechanism generation and optimization procedures and the increased availability of experimental data, integrated methodologies combining data analysis, kinetic simulations, chemical lumping, and kinetic mechanism optimization are still lacking. This paper presents an integrated workflow that combines recently developed automated tools for kinetic mechanism development and testing, from data collection to kinetic model reduction and optimization. The proposed methodology is applied to build a consistent, efficient, and well-performing kinetic mechanism for the combustion of oxymethylene ethers (OMEs), which are promising synthetic e-fuels for transportation.