Large-eddy spray simulation under direct-injection spark-ignition engine-like conditions with an integrated atomization/breakup model
Rutland, Christopher J
Hernández Pérez, Francisco E
Im, Hong G.
KAUST DepartmentClean Combustion Research Center
Computational Reacting Flow Laboratory (CRFL)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
Online Publication Date2020-01-30
Print Publication Date2021-03
AbstractIn this work, a hybrid breakup model tailored for direct-injection spark-ignition engine sprays is developed and implemented in the OpenFOAM CFD code. The model uses the Lagrangian–Eulerian approach whereby parcels of liquid fuel are injected into the computational domain. Atomization and breakup of the liquid parcels are described by two sub-models based on the breakup mechanisms reported in the literature. Evaluation of the model has been carried out by comparing large-eddy simulation results with experimental measurements under multiple direct-injection spark-ignition engine-like conditions. Spray characteristics including liquid and vapor penetration curves, droplet velocities, and Sauter mean diameter distributions are examined in detail. The model has been found to perform well for the spray conditions considered in this work. Results also show that after the end of injection, most of the residual droplets that are still in the breakup process are driven by the bag and bag–stamen breakup mechanisms. Finally, an effort to unify the breakup length parameter is made, and the given value is tested under various ambient density and temperature conditions. The predicted trends follow the measured data closely for the penetration rates, even though the model is not specifically tuned for individual cases.
CitationLi, H., Rutland, C. J., Hernández Pérez, F. E., & Im, H. G. (2020). Large-eddy spray simulation under direct-injection spark-ignition engine-like conditions with an integrated atomization/breakup model. International Journal of Engine Research, 146808741988186. doi:10.1177/1468087419881867
AcknowledgementsThe authors thank the UW–Madison High Throughput Computing for providing computer resources used to obtain the results presented in this publication.
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Wisconsin Engine Research Consultants, LLC, and by the FUELCOM II collaborative project between King Abdullah University of Science and Technology and Saudi Aramco Oil Co.