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Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Transients in the rate of injection (ROI) with respect to time are ever-present in direct-injection engines, even with common-rail fueling. The shape of the injection ramp-up and ramp-down affects spray penetration and mixing, particularly with multiple-injection schedules currently in practice. Ultimately, the accuracy of CFD model predictions used to optimize the combustion process depends upon the accuracy of the ROI utilized as fuel input boundary conditions. But experimental difficulties in the measurement of ROI, as well as real-world affects that change the ROI from the bench to the engine, add uncertainty that may be mistaken for weaknesses in spray modeling instead of errors in boundary conditions. In this work we use detailed, time-resolved measurements of penetration at the Spray A conditions of the Engine Combustion Network to rigorously guide the necessary ROI shape required to match penetration in jet models that allow variable rate of injection.