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Bayesian calibration of a methane-air global scheme and uncertainty propagation to flame-vortex interactions

机译：Bayesian calibration of a methane-air global scheme and uncertainty propagation to flame-vortex interactions

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摘要

Simplified chemistry models are commonly used in reactive computational fluid dynamics (CFD) simulationsto alleviate the computational cost. Uncertainties associated with the calibration of such simplifiedmodels have been characterized in some works, but to our knowledge, there is a lack of studies analyzingthe subsequent propagation through CFD simulation of combustion processes.This work propagates the uncertainties - arising in the calibration of a global chemistry model - throughdirect numerical simulations (DNS) of flame-vortex interactions. Calibration uncertainties are derived byinferring the parameters of a two-step reaction mechanism for methane, using synthetic observations ofone-dimensional laminar premixed flames based on a detailed mechanism. To assist the inference, independentsurrogate models for estimating flame speed and thermal thickness are built taking advantageof the Principal Component Analysis (PCA) and the Polynomial Chaos (PC) expansion. Using the MarkovChain Monte Carlo (MCMC) sampling method, a discussion on how push-forward posterior densities behavewith 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 twodimensionalflame-vortex interactions using 60 independent samples. Posterior predictive densities forthe time evolution of the heat release and flame surface are consistent, being that the confidence intervalscontain the reference simulation. However, the two-step mechanism fails to reproduce the flameresponse to stretch as it was not considered in the calibration. This study highlights the capabilities andlimitations of propagating chemistry-models uncertainties to CFD applications to fully quantify posterioruncertainties on target quantities.

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