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The results of the numerical characterization of the hydrodynamics of Soybean Oil Methyl Ester (SME) fuel spray using a spray model based on the moments of the droplet size distribution function are presented. A heat and mass transfer model based on the droplet surface-areaaveraged temperature is implemented in the spray model and the effects on the SME fuel spray tip penetration and droplet sizes at different ambient gas temperature (300 K to 450 K) and fuel temperature (300 K to 360 K) values are evaluated. The results indicate that the SME fuel spray tip penetration values are insensitive to variations to the fuel temperature values but increase with increasing ambient gas temperature values. The droplet size values increase with increasing SME fuel temperature. The fuel vapor mass fraction is predicted to be highest at the spray core, with the axial velocity values of the droplets increasing with increases in the SME fuel spray temperature.

Creating small sized droplets is the primary reason for using sprays. In high-pressure diesel engine sprays, smaller sized droplets aid the combustion process, thus reducing emissions. Therefore, the adequate representation of the droplet breakup process in diesel engine spray models is essential. Two droplet breakup models have been applied in this study. These models have been developed based on whether the results of the droplet breakup processes have been derived from approximations, using an assumed size distribution function, or based on empirical data, using a gamma size distribution function. The effects of assumptions in the models, such as the number of sibling droplets produced during the breakup process, are also presented.

The need to evaluate other fuel types for use in internal combustion engines has increased with the concerns related to the limited availability of fossil fuels and the need to reduce emissions. In this assessment, two alternative-to-diesel fuels, dimethyl ether and biodiesel, are characterized by their spray tip penetration at different axial distances from the nozzle tip and at different ambient pressure values. The sauter mean diameter values at various axial distances from the injector tip are also evaluated. A novel diesel spray model that presents the hydrodynamics features of sprays from the moments derived from a Gamma size distribution and the droplet-size distribution function, rather than from droplet-size classes, is used for the numerical predictions. The results indicate that the spray tip penetration for both fuels increases rapidly initially but the rate of increase slows at the later stages of the fuel injection.

Fuel spray and atomization processes affect the combustion and emissions characteristics of fuels in internal combustion engines. Biodiesel and synthetic fuels such as oxymethylene dimethyl ethers (OME) show great promise as alternative fuels and are complementary in terms of reproducing the fluid properties of conventional diesel fuels through blending, for instance. Averaged experimental results, empirical correlations and Computational Fluid Dynamics (CFD) have typically been used to evaluate and predict fuel spray liquid and vapor penetration values so as to better design internal combustion engines. Lately, Machine Learning (ML) is being applied to these investigations. Typically, ML spray studies use averaged experimental data and then over-trained neural networks on the limited available data.