Probabilistic Approach to Predict Abnormal Combustion in Spark Ignition Engines
KAUST DepartmentClean Combustion Research Center
Computational Reacting Flow Laboratory (CRFL)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/631296
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AbstractThis study presents a computational framework to predict the outcome of combustion process based on a given RANS initial condition by performing statistical analysis of Sankaran number, Sa, and ignition regime theory proposed by Im et al. . A criterion to predict strong auto-ignition/detonation a priori is used in this study, which is based on Sankaran-Zeldovich criterion. In the context of detonation, Sa is normalized by a sound speed, and is spatially calculated for the bulk mixture with temperature and equivalence ratio stratifications. The initial conditions from previous pre-ignition simulations were used to compute the spatial Sa distribution followed by the statistics of Sa including the mean Sa, the probability density function (PDF) of Sa, and the detonation probability, P. Sa is found to be decreased and detonation probability increased significantly with increase of temperature. The statistic mean Sa calculated for the entire computational domain and the predicted Sa from the theory were found to be nearly identical. The predictions based on the adapted Sankaran-Zel'dovich criterion and detonation probability agree well with the results of the previous high fidelity pre-ignition simulations.
CitationMubarak Ali MJ, Luong MB, Sow A, Hernandez Perez F, Im H (2018) Probabilistic Approach to Predict Abnormal Combustion in Spark Ignition Engines. SAE Technical Paper Series. Available: http://dx.doi.org/10.4271/2018-01-1722.
SponsorsThis work was funded by King Abdullah University of Science and Technology (KAUST) and the computations utilized the KAUST supercomputing facility. The authors thank convergent science for providing the licenses for the code.
JournalSAE Technical Paper Series
Conference/Event nameSAE 2018 International Powertrains, Fuels and Lubricants Meeting, FFL 2018