Optimal Design and Model Validation for Combustion Experiments in a Shock Tube

Handle URI:
http://hdl.handle.net/10754/623996
Title:
Optimal Design and Model Validation for Combustion Experiments in a Shock Tube
Authors:
Long, Quan ( 0000-0002-0329-9437 ) ; Kim, Daesang; Tempone, Raul ( 0000-0003-1967-4446 ) ; Bisetti, Fabrizio ( 0000-0001-5162-7805 ) ; Farooq, Aamir ( 0000-0001-5296-2197 ) ; Knio, Omar; Prudhomme, Serge
Abstract:
We 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Clean Combustion Research Center; Physical Sciences and Engineering (PSE) Division; Applied Mathematics and Computational Science Program; Mechanical Engineering Program; Computer, Electrical and Mathematical Sciences & Engineering (CEMSE)
Conference/Event name:
Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2014)
Issue Date:
6-Jan-2014
Type:
Poster
Appears in Collections:
Posters; Applied Mathematics and Computational Science Program; Physical Sciences and Engineering (PSE) Division; Mechanical Engineering Program; Clean Combustion Research Center; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Conference on Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2014)

Full metadata record

DC FieldValue Language
dc.contributor.authorLong, Quanen
dc.contributor.authorKim, Daesangen
dc.contributor.authorTempone, Raulen
dc.contributor.authorBisetti, Fabrizioen
dc.contributor.authorFarooq, Aamiren
dc.contributor.authorKnio, Omaren
dc.contributor.authorPrudhomme, Sergeen
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.en
dc.subjectRCFDen
dc.titleOptimal Design and Model Validation for Combustion Experiments in a Shock Tubeen
dc.typePosteren
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentClean Combustion Research Centeren
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.contributor.departmentApplied Mathematics and Computational Science Programen
dc.contributor.departmentMechanical Engineering Programen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences & Engineering (CEMSE)en
dc.conference.dateJanuary 6-10, 2014en
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2014)en
dc.conference.locationKAUSTen
kaust.authorLong, Quanen
kaust.authorKim, Daesangen
kaust.authorTempone, Raulen
kaust.authorBisetti, Fabrizioen
kaust.authorFarooq, Aamiren
kaust.authorKnio, Omaren
kaust.authorPrudhomme, Sergeen
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