Abstract

Modern Diesel engines are attractive for fuel economy and performances but they are suffering from increasingly strict emission standards. Therefore the investigation of the injection and combustion processes are mandatory. This paper focuses on the development of a multi-component fuel based methodology for the simulation of non-reacting and reacting high injection pressure Diesel sprays.In multi-dimensional modeling fuels are represented predominantly by single components, such as n-Dodecane for Diesel, and this is a limitation in their ability to represent real fuels which are blends of hundreds components. This study outlines a method by which the fuel composition is represented by means of a Discrete Multi-Component (DMC) model approach in order to improve the prediction of the vaporization behavior of high injection pressure Diesel sprays.A testing blend of 6 hydrocarbons is taken into account and a reduced one is developed in order to reduce the computational cost of the CFD simulations while maintaining the advantages due to a multi-component description of the mixture. The CFD methodology is developed within Star-CD commercial code while particular care is also dedicated to the prediction of the atomization and secondary breakup processes. At the nozzle exit the atomized droplets are predicted by a primary breakup approach which is able to take into account the cavitation phenomena and the turbulent effects. The atomization model is based on a simplified approach that is able to evaluate the effects of the nozzle geometry.The preliminary investigations are performed in a constant volume vessel, validating the numerical parameters against experimental data in order to correctly reproduce spray vaporization behavior. Then, to illustrate the important differences between the vaporization characteristics of a multi-component mixture compared to a mono-component one, the CFD methodology is tested investigating the in-cylinder combustion process of a 4 cylinders, Common Rail Diesel engine of current production.

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