@article{2020-00010, author = {Davide Paredi and Tommaso Lucchini and Gianluca D’Errico and Angelo Onorati and Lyle Pickett and Joshua Lacey}, title ={Validation of a comprehensive computational fluid dynamics methodology to predict the direct injection process of gasoline sprays using Spray G experimental data}, journal = {International Journal of Engine Research}, volume = {21}, number = {1}, pages = {199-216}, year = {2020}, doi = {10.1177/1468087419868020}, URL = {https://doi.org/10.1177/1468087419868020}, eprint = {https://doi.org/10.1177/1468087419868020}, abstract = { A detailed prediction of injection and air–fuel mixing is fundamental in modern direct injection, spark-ignition engines to guarantee a stable and efficient combustion process and to minimize pollutant formation. Within this context, computational fluid dynamics simulations nowadays represent a powerful tool to understand the in-cylinder evolution of spray and air–fuel charge. To guarantee the accuracy of the adopted multidimensional spray sub-models, it is mandatory to validate the computed results against available experimental data under well-defined operating conditions. To this end, in this work, the authors proposed the calibration and validation of a comprehensive set of spray sub-models by means of the simulation of the Spray G experiment, available in the context of the engine combustion network. For a suitable validation of the proposed numerical setup in addition to the baseline condition, gasoline direct injection operating points typical of early injection with homogeneous operation, late injection with high ambient density and flash boiling with enhanced fuel evaporation were also simulated. Numerical computations were validated against a wide set of available experimental data by means of an accurate post-processing analysis taking into account axial liquid and vapor penetrations, gas-phase velocity between spray plumes, droplet size, plume liquid velocity, direction and mass distribution. Satisfactory results were achieved with the proposed setup, which is able to predict gasoline spray evolution under different operating conditions. } }