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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.

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.

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.

Recently a spray model that uses the moments of the droplet size distribution functions to represent the complete hydrodynamics characteristics of spray flow has been shown to be an applicable tool for the analysis of engine sprays. The primary advantage of the model is that it is less computationally intensive compared to models that track droplet parcels. The main purpose of the current study is to evaluate the capability of using the model for the predictions of narrow-angle sprays at fuel injection pressure cases of up to 770 bar and spray cone angles of just 30 from two different sets of experimental data, with the results being characterized by spray tip penetration and sauter mean diameter values. The effects of uncertain input parameters, like the collision constant in the droplet collision model, were assessed before the simulation of the experimental conditions.

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.

Discrete droplet models in which parcels of droplets are tracked in space in a Lagrangian framework have historically dominated the modelling of fuel sprays. These models are computationally expensive, as the chaotic motions of each droplet have to be predicted. A development of a spray model that captures the full polydisperse nature of spray flow without using droplet size classes has been presented in previous publications. In this paper, the model is applied to solid cone diesel sprays. The size information concerning the spray is obtained by calculating three moments of the droplet-size distribution function from transport equations and one moment from a Gamma size distribution function. The predictions from the model are compared with results from experiments, a discrete droplet model, and two moments-based models. These indicate that droplet break-up, collisions, penetration and sizes are successfully modelled.