Bayesian calibration of a methane-air global scheme and uncertainty propagation to flame-vortex interactions
| Autor: | Olivier Le Maitre, Jan Mateu Armengol, Ronan Vicquelin |
|---|---|
| Přispěvatelé: | Laboratoire d'Énergétique Moléculaire et Macroscopique, Combustion (EM2C), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Uncertainty Quantification in Scientific Computing and Engineering (PLATON), Centre de Mathématiques Appliquées - Ecole Polytechnique (CMAP), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Barcelona Supercomputing Center |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Flame-vortex Interactions
Computational chemistry Computational fluid dynamics 020209 energy General Chemical Engineering Bayesian inference Montecarlo Mètode de General Physics and Astronomy Energy Engineering and Power Technology 02 engineering and technology [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] Physics::Fluid Dynamics Laminar Premixed Flame symbols.namesake 020401 chemical engineering Laminar premixed flame [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST] Methane-air global scheme 0202 electrical engineering electronic engineering information engineering Calibration Physics::Chemical Physics 0204 chemical engineering Uncertainty quantification Methane-air Global Scheme Uncertainty Propagation Propagation of uncertainty [STAT.AP]Statistics [stat]/Applications [stat.AP] Polynomial chaos business.industry [SPI.FLUID]Engineering Sciences [physics]/Reactive fluid environment Markov chain Monte Carlo Bayesian Inference General Chemistry Mechanics Flame speed Monte Carlo method Informàtica::Aplicacions de la informàtica::Aplicacions informàtiques a la física i l‘enginyeria [Àrees temàtiques de la UPC] Fuel Technology 13. Climate action Flame-vortex interactions Uncertainty propagation symbols Uncertainty Quantification business |
| Zdroj: | Combustion and Flame Combustion and Flame, Elsevier, 2021, 234, pp.111642. ⟨10.1016/J.COMBUSTFLAME.2021.111642⟩ Combustion and Flame, 2021, 234, pp.111642. ⟨10.1016/J.COMBUSTFLAME.2021.111642⟩ UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| ISSN: | 0010-2180 |
| Popis: | Simplified chemistry models are commonly used in reactive computational fluid dynamics (CFD) simulations to alleviate the computational cost. Uncertainties associated with the calibration of such simplified models have been characterized in some works, but to our knowledge, there is a lack of studies analyzing the subsequent propagation through CFD simulation of combustion processes. This work propagates the uncertainties - arising in the calibration of a global chemistry model - through direct numerical simulations (DNS) of flame-vortex interactions. Calibration uncertainties are derived by inferring the parameters of a two-step reaction mechanism for methane, using synthetic observations of one-dimensional laminar premixed flames based on a detailed mechanism. To assist the inference, independent surrogate models for estimating flame speed and thermal thickness are built taking advantage of the Principal Component Analysis (PCA) and the Polynomial Chaos (PC) expansion. Using the Markov Chain Monte Carlo (MCMC) sampling method, a discussion on how push-forward posterior densities behave with respect to the detailed mechanism is provided based on three different calibrations relying (i) only on flame speed, (ii) only on thermal thickness, and (iii) on both quantities simultaneously. The model parameter uncertainties characterized in the latter calibration are propagated to two-dimensional flame-vortex interactions using 60 independent samples. Posterior predictive densities for the time evolution of the heat release and flame surface are consistent, being that the confidence intervals contain the reference simulation. However, the two-step mechanism fails to reproduce the flame response to stretch as it was not considered in the calibration. This study highlights the capabilities and limitations of propagating chemistry-models uncertainties to CFD applications to fully quantify posterior uncertainties on target quantities. The authors wish to thank V. Moureau for his help on setting up the YALES2 case. This work has bene ted from the financial support of the LabEx LaSIPS (ANR-10-LABX-0032-LaSIPS) managed by the French National Research Agency under the "Investissements d'avenir" program (ANR-11-IDEX-0003). The study was performed using HPC resources from the Mesocentre computing center of CentraleSupelec and Ecole Normale Superieure Paris-Saclay supported by CNRS and Region Ile-de-France (http://mesocentre.centralesupelec.fr/). |
| Databáze: | OpenAIRE |
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