Probabilistic parameter estimation in a 2-step chemical kinetics model for n-dodecane jet autoignition

Abstract

This paper demonstrates the development of a simple chemical kinetics model designed for autoignition of n-dodecane in air using Bayesian inference with a model-error representation. The model error, i.e. intrinsic discrepancy from a high-fidelity benchmark model, is represented by allowing additional variability in selected parameters. Subsequently, we quantify predictive uncertainties in the results of autoignition simulations of homogeneous reactors at realistic diesel engine conditions. We demonstrate that these predictive error bars capture model error as well. The uncertainty propagation is performed using non-intrusive spectral projection that can also be used in principle with larger scale computations, such as large eddy simulation. While the present calibration is performed to match a skeletal mechanism, it can be done with equal success using experimental data only (e.g. shock-tube measurements). Since our method captures the error associated with structural model simplifications, we believe that the optimised model could then lead to better qualified predictions of autoignition delay time in high-fidelity large eddy simulations than the existing detailed mechanisms. This methodology provides a way to reduce the cost of reaction kinetics in simulations systematically, while quantifying the accuracy of predictions of important target quantities.

KEYWORDS:

• Bayesian inference
• uncertainty quantification
• n-dodecane kinetics
• diesel jet
• autoignition

Additional information

Funding

Support for this research was provided by the US Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies (VT) program [grant number VT0401000]; support was also provided by the US DOE Office of Basic Energy Sciences (BES) Division of Chemical Sciences, Geosciences, and Biosciences; Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the US Department of Energy's National Nuclear Security Administration [contract DE-NA-0003525].