Abstract

ABSTRACTNumerous mathematical tools intended to adjust rate constants employed in complex detailed kinetic models to make them consistent with multiple sets of experimental data have been reported in the literature. Application of such model optimization methods typically begins with the assignment of uncertainties in the absolute rate constants in a starting model, followed by variation of the rate constants within these uncertainty bounds to tune rate parameters to match model outputs to experimental observations. The present work examines the impact of including information on relative reaction rates in the optimization strategy, which is not typically done in current implementations. It is shown that where such rate constant data are available, the available parameter space changes dramatically due to the correlations inherent in such measurements. Relative rate constants are typically measured with greater relative accuracy than corresponding absolute rate constant measurements. This greater accuracy further reduces the available parameter space, which significantly affects the uncertainty in the model outcomes as a result of kinetic parameter uncertainties. We demonstrate this effect by considering a simple example case emulating an ignition event and show that use of relative rate measurements leads to a significantly smaller uncertainty in the output ignition delay time in comparison with results based on absolute measurements. This is true even though the same range of absolute rate constants is sampled in each case. Implications of the results with respect to the maintenance of physically realistic kinetics in optimized models are discussed, and suggestions are made for the path forward in the refinement of detailed kinetic models.

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