Numerical Simulations of High Reactivity Gasoline Fuel Sprays under Vaporizing and Reactive Conditions
Hernandez Perez, Francisco
Roberts, William L.
Im, Hong G.
KAUST DepartmentChemical Engineering Program
Clean Combustion Research Center
Combustion and Pyrolysis Chemistry (CPC) Group
Computational Reacting Flow Laboratory (CRFL)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
high-pressure combustion (HPC) Research Group
Permanent link to this recordhttp://hdl.handle.net/10754/627585
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AbstractGasoline compression ignition (GCI) engines are becoming more popular alternative for conventional spark engines to harvest the advantage of high volatility. Recent experimental study demonstrated that high reactivity gasoline fuel can be operated in a conventional mixing controlled combustion mode producing lower soot emissions than that of diesel fuel under similar efficiency and NOx level . Therefore, there is much interest in using gasoline-like fuels in compression ignition engines. In order to improve the fidelity of simulation-based GCI combustion system development, it is mandatory to enhance the prediction of spray combustion of gasoline-like fuels. The purpose of this study is to model the spray characteristics of high reactivity gasoline fuels and validate the models with experimental results obtained through an optically accessible constant volume vessel under vaporizing  and reactive conditions . For reacting cases, a comparison of PRF and KAUST multi-component surrogate (KMCS) mechanism was done to obtain good agreement with the experimental ignition delay. From this study, some recommendations were proposed for GCI combustion modelling framework using gasoline like fuels.
CitationMohan B, Mubarak Ali MJ, Ahmed A, Hernandez Perez F, Sim J, et al. (2018) Numerical Simulations of High Reactivity Gasoline Fuel Sprays under Vaporizing and Reactive Conditions. SAE Technical Paper Series. Available: http://dx.doi.org/10.4271/2018-01-0292.
SponsorsThis work was sponsored by the Saudi Aramco under the FUELCOM II program and by King Abdullah University of Science and Technology. The computational simulations utilized the clusters at KAUST Supercomputing Laboratory and IT Research Computing. The author thanks Convergent Science Inc. for providing CONVERGE license.
JournalSAE Technical Paper Series
Conference/Event name2018 SAE World Congress Experience, WCX 2018