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    A hierarchical method for Bayesian inference of rate parameters from shock tube data: Application to the study of the reaction of hydroxyl with 2-methylfuran

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    Type
    Article
    Authors
    Kim, Daesang
    El Gharamti, Iman
    Hantouche, Mireille
    Elwardani, Ahmed Elsaid cc
    Farooq, Aamir cc
    Bisetti, Fabrizio cc
    Knio, Omar cc
    KAUST Department
    Applied Mathematics and Computational Science Program
    Center for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ)
    Chemical Kinetics & Laser Sensors Laboratory
    Clean Combustion Research Center
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Mechanical Engineering Program
    Physical Science and Engineering (PSE) Division
    Reactive Flow Modeling Laboratory (RFML)
    Date
    2017-06-22
    Online Publication Date
    2017-06-22
    Print Publication Date
    2017-10
    Permanent link to this record
    http://hdl.handle.net/10754/625629
    
    Metadata
    Show full item record
    Abstract
    We developed a novel two-step hierarchical method for the Bayesian inference of the rate parameters of a target reaction from time-resolved concentration measurements in shock tubes. The method was applied to the calibration of the parameters of the reaction of hydroxyl with 2-methylfuran, which is studied experimentally via absorption measurements of the OH radical's concentration following shock-heating. In the first step of the approach, each shock tube experiment is treated independently to infer the posterior distribution of the rate constant and error hyper-parameter that best explains the OH signal. In the second step, these posterior distributions are sampled to calibrate the parameters appearing in the Arrhenius reaction model for the rate constant. Furthermore, the second step is modified and repeated in order to explore alternative rate constant models and to assess the effect of uncertainties in the reflected shock's temperature. Comparisons of the estimates obtained via the proposed methodology against the common least squares approach are presented. The relative merits of the novel Bayesian framework are highlighted, especially with respect to the opportunity to utilize the posterior distributions of the parameters in future uncertainty quantification studies.
    Citation
    Kim D, El Gharamti I, Hantouche M, Elwardany AE, Farooq A, et al. (2017) A hierarchical method for Bayesian inference of rate parameters from shock tube data: Application to the study of the reaction of hydroxyl with 2-methylfuran. Combustion and Flame 184: 55–67. Available: http://dx.doi.org/10.1016/j.combustflame.2017.06.002.
    Sponsors
    The research reported in this publication was supported by King Abdullah University of Science and Technology (KAUST) and the Center for Uncertainty Quantification in Computational Science and Engineering funded by the Strategic Research Initiative (SRI).
    Publisher
    Elsevier BV
    Journal
    Combustion and Flame
    DOI
    10.1016/j.combustflame.2017.06.002
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S0010218017302110
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.combustflame.2017.06.002
    Scopus Count
    Collections
    Articles; Applied Mathematics and Computational Science Program; 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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