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dc.contributor.authorKim, Daesang
dc.contributor.authorEl Gharamti, Iman
dc.contributor.authorHantouche, Mireille
dc.contributor.authorElwardani, Ahmed Elsaid
dc.contributor.authorFarooq, Aamir
dc.contributor.authorBisetti, Fabrizio
dc.contributor.authorKnio, Omar
dc.date.accessioned2017-10-03T12:49:30Z
dc.date.available2017-10-03T12:49:30Z
dc.date.issued2017-06-22
dc.identifier.citationKim 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.
dc.identifier.issn0010-2180
dc.identifier.doi10.1016/j.combustflame.2017.06.002
dc.identifier.urihttp://hdl.handle.net/10754/625629
dc.description.abstractWe 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.
dc.description.sponsorshipThe 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).
dc.publisherElsevier BV
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S0010218017302110
dc.subjectBayesian inference
dc.subjectChemical kinetics
dc.subjectRate parameters
dc.subjectShock tube
dc.subjectSurrogate model
dc.subjectUncertainty quantification
dc.titleA hierarchical method for Bayesian inference of rate parameters from shock tube data: Application to the study of the reaction of hydroxyl with 2-methylfuran
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentCenter for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ)
dc.contributor.departmentChemical Kinetics & Laser Sensors Laboratory
dc.contributor.departmentClean Combustion Research Center
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentMechanical Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.contributor.departmentReactive Flow Modeling Laboratory (RFML)
dc.identifier.journalCombustion and Flame
dc.contributor.institutionDepartment of Applied Mechanics, Aalto University, Aalto, , Finland
dc.contributor.institutionMechanical Engineering Department, Faculty of Engineering, Alexandria University, Alexandria, 21544, , Egypt
dc.contributor.institutionDepartment of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, 78712-1085, , United States
dc.contributor.institutionDepartment of Mechanical Engineering and Materials Science, Duke University, Durham, NC, 27708, , United States
kaust.personKim, Daesang
kaust.personEl Gharamti, Iman
kaust.personHantouche, Mireille
kaust.personElwardani, Ahmed Elsaid
kaust.personFarooq, Aamir
kaust.personBisetti, Fabrizio
kaust.personBisetti, Fabrizio
kaust.personKnio, Omar
dc.date.published-online2017-06-22
dc.date.published-print2017-10


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