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
Type
ArticleAuthors
Kim, DaesangEl Gharamti, Iman
Hantouche, Mireille

Elwardani, Ahmed Elsaid

Farooq, Aamir

Bisetti, Fabrizio

Knio, Omar

KAUST Department
Applied Mathematics and Computational Science ProgramCenter 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
2017-06-22Online Publication Date
2017-06-22Print Publication Date
2017-10Permanent link to this record
http://hdl.handle.net/10754/625629
Metadata
Show full item recordAbstract
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 BVJournal
Combustion and FlameAdditional Links
http://www.sciencedirect.com/science/article/pii/S0010218017302110ae974a485f413a2113503eed53cd6c53
10.1016/j.combustflame.2017.06.002