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    Probabilistic Approach to Predict Abnormal Combustion in Spark Ignition Engines

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    2018-01-1722_Manuscript_added_authors_citation_inf.pdf
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    Type
    Conference Paper
    Authors
    Jaasim, Mohammed
    Luong, Minh Bau cc
    Sow, Aliou
    Hernandez Perez, Francisco
    Im, Hong G. cc
    KAUST Department
    Clean 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
    Date
    2018-09-10
    Permanent link to this record
    http://hdl.handle.net/10754/631296
    
    Metadata
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    Abstract
    This 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. [1]. 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.
    Citation
    Mubarak 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.
    Sponsors
    This 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.
    Publisher
    SAE International
    Journal
    SAE Technical Paper Series
    Conference/Event name
    SAE 2018 International Powertrains, Fuels and Lubricants Meeting, FFL 2018
    DOI
    10.4271/2018-01-1722
    Additional Links
    https://saemobilus.sae.org/content/2018-01-1722
    ae974a485f413a2113503eed53cd6c53
    10.4271/2018-01-1722
    Scopus Count
    Collections
    Conference Papers; Physical Science and Engineering (PSE) Division; Mechanical Engineering Program; Clean Combustion Research Center; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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