KAUST DepartmentClean Combustion Research Center
Computational Reacting Flow Laboratory (CRFL)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
KAUST Grant NumberOSR-2017-CRG6-3409.03
Permanent link to this recordhttp://hdl.handle.net/10754/669295
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AbstractAdvancements in internal combustion technology, such as efficiency improvements and the usage of new complex fuels, are often coupled with developments of suitable numerical tools for predicting the complex dynamic behavior of sprays. Therefore, this work presents a Eulerian multi-fluid model specialized for the dynamic behavior of dense evaporating liquid fuel sprays. The introduced model was implemented within the open-source OpenFOAM library, which is constantly gaining popularity in both industrial and academic settings. Therefore, it represents an ideal framework for such development. The presented model employs the classes method and advanced interfacial momentum transfer models. The droplet breakup is considered using the enhanced WAVE breakup model, where the mass taken from the parent droplets is distributed among child classes using a triangular distribution. Furthermore, the complex thermal behavior within the moving droplets is considered using a parabolic temperature profile and an effective thermal conductivity approach. This work includes an uncertainty estimation analysis (for both spatial and temporal resolutions) for the developed solver. Furthermore, the solver was validated against two ECN Spray A conditions (evaporating and non-evaporating). Overall, the presented results show the capability of the implemented model to successfully predict the complex dynamic behavior of dense liquid sprays for the selected operating conditions.
CitationKeser, R., Battistoni, M., Im, H. G., & Jasak, H. (2021). A Eulerian Multi-Fluid Model for High-Speed Evaporating Sprays. Processes, 9(6), 941. doi:10.3390/pr9060941
SponsorsThis work was supported by the King Abdullah University of Science and Technology within the OSR-2017-CRG6-3409.03 research grant, and the Croatian Science Foundation (project number DOK-01-2018).
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