The objective of the present work is to establish a framework to design simple Arrhenius mechanisms for simulation of Diesel engine combustion. The goal is to predict auto-ignition and flame propagation over a selected range of temperature and equivalence ratio, at a significantly reduced computational cost, and to quantify the accuracy of the optimized mechanisms for a selected set of characteristics. The methodology is demonstrated for n-dodecane oxidation by fitting the auto-ignition delay time predicted by a detailed reference mechanism to a two-step model mechanism. The pre-exponential factor and activation energy of the first reaction are modeled as functions of equivalence ratio and temperature and calibrated using Bayesian inference. This provides both the optimal parameter values and the related uncertainties over a defined envelope of temperatures, pressures, and equivalence ratios. Non-intrusive spectral projection is then used to propagate the uncertainty through homogeneous auto-ignitions. A benefit of the method is that parametric uncertainties can be propagated in the same way through coupled reacting flow calculations using techniques such as Large Eddy Simulation to quantify the impact of the chemical parameter uncertainty on simulation results.

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