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dc.contributor.authorLong, Quan
dc.contributor.authorKim, Daesang
dc.contributor.authorTempone, Raul
dc.contributor.authorBisetti, Fabrizio
dc.contributor.authorFarooq, Aamir
dc.contributor.authorKnio, Omar
dc.contributor.authorPrudhomme, Serge
dc.date.accessioned2017-06-01T10:20:42Z
dc.date.available2017-06-01T10:20:42Z
dc.date.issued2014-01-06
dc.identifier.urihttp://hdl.handle.net/10754/623996
dc.description.abstractWe develop a Bayesian framework for the optimal experimental design of the shock tube experiments which are being carried out at the KAUST Clean Combustion Center. The unknown parameters are the pre-exponential parameters and the activation energies in the reaction rate functions. The control parameters are the initial hydrogen concentration and the temperature. First, we build a polynomial based surrogate model for the observable related to the reactions in the shock tube. Second, we use a novel MAP based approach to estimate the expected information gain in the proposed experiments and select the best experimental set-ups corresponding to the optimal expected information gains. Third, we use the synthetic data to carry out virtual validation of our methodology.
dc.subjectRCFD
dc.titleOptimal Design and Model Validation for Combustion Experiments in a Shock Tube
dc.typePoster
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentClean Combustion Research Center
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Division
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentMechanical Engineering Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences & Engineering (CEMSE)
dc.conference.dateJanuary 6-10, 2014
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2014)
dc.conference.locationKAUST
kaust.personLong, Quan
kaust.personKim, Daesang
kaust.personTempone, Raul
kaust.personBisetti, Fabrizio
kaust.personFarooq, Aamir
kaust.personKnio, Omar
kaust.personPrudhomme, Serge
refterms.dateFOA2018-06-14T04:28:53Z


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