Publication de 6 numéros par an
ISSN Imprimer: 2152-5080
ISSN En ligne: 2152-5099
Indexed in
DATA-FREE INFERENCE OF UNCERTAIN PARAMETERS IN CHEMICAL MODELS
RÉSUMÉ
We outline the use of a data-free inference procedure for estimation of uncertain model parameters for a chemical model of methane-air ignition. The method involves a nested pair of Markov chains, exploring both the data and parametric spaces, to discover a pooled joint posterior consistent with available information. We describe the highlights of the method, and detail its particular implementation in the system at hand. We examine the performance of the procedure, focusing on the robustness and convergence of the estimated joint parameter posterior with increasing number of data chain samples. We also comment on comparisons of this posterior with the missing reference posterior density.
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Sargsyan K., Najm H. N., Ghanem R., On the Statistical Calibration of Physical Models, International Journal of Chemical Kinetics, 47, 4, 2015. Crossref
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Khalil M., Chowdhary K., Safta C., Sargsyan K., Najm H.N., Inference of reaction rate parameters based on summary statistics from experiments, Proceedings of the Combustion Institute, 36, 1, 2017. Crossref
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Najm Habib, Chowdhary Kenny, Inference Given Summary Statistics, in Handbook of Uncertainty Quantification, 2015. Crossref
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Kim Daesang, El Gharamti Iman, Hantouche Mireille, Elwardany Ahmed E., Farooq Aamir, Bisetti Fabrizio, Knio Omar, 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, 2017. Crossref
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Najm Habib N., Chowdhary Kenny, Inference Given Summary Statistics, in Handbook of Uncertainty Quantification, 2017. Crossref
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Khalil Mohammad, Najm Habib N., Probabilistic inference of reaction rate parameters from summary statistics, Combustion Theory and Modelling, 22, 4, 2018. Crossref
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Casey Tiernan A., Najm Habib N., Estimating the joint distribution of rate parameters across multiple reactions in the absence of experimental data, Proceedings of the Combustion Institute, 37, 1, 2019. Crossref
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Soize Christian, Ghanem Roger, Physics‐constrained non‐Gaussian probabilistic learning on manifolds, International Journal for Numerical Methods in Engineering, 121, 1, 2020. Crossref
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Torres-Herrador Francisco, Coheur Joffrey, Panerai Francesco, Magin Thierry E., Arnst Maarten, Mansour Nagi N., Blondeau Julien, Competitive kinetic model for the pyrolysis of the Phenolic Impregnated Carbon Ablator, Aerospace Science and Technology, 100, 2020. Crossref
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Hantouche Mireille, Sarathy S. Mani, Knio Omar M., Global sensitivity analysis of n-butanol ignition delay times to thermodynamics class and rate rule parameters, Combustion and Flame, 222, 2020. Crossref
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Walker Eric A., Ravisankar Kishore, Savara Aditya, CheKiPEUQ Intro 2: Harnessing Uncertainties from Data Sets, Bayesian Design of Experiments in Chemical Kinetics**, ChemCatChem, 12, 21, 2020. Crossref
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Almohammadi Saja, Hantouche Mireille, Le Maître Olivier P., Knio Omar M., A tangent linear approximation of the ignition delay time. I: Sensitivity to rate parameters, Combustion and Flame, 230, 2021. Crossref
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Casey T.A., Khalil M., Najm H.N., Inference and combination of missing data sets for the determination of H2O2 thermal decomposition rate uncertainty, Combustion and Flame, 232, 2021. Crossref
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Horvatits Caitlin, Lee Jungkuk, Kyriakidou Eleni A., Walker Eric A., Characterizing Adsorption Sites on Ag/SSZ-13 Zeolites: Experimental Observations and Bayesian Inference, The Journal of Physical Chemistry C, 124, 35, 2020. Crossref