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The Importance of Relative Reaction Rates in the Optimization of Detailed Kinetic Models



Jeffrey A. Manion, William S. McGivern


Numerous mathematical tools intended to optimize rate constants employed in detailed kinetic models and make them consistent with experimental data have been reported in the literature. A typical methodology 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 in order to optimize 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 is available, the available parameter space changes dramatically due to the correlated uncertainty inherent in such a measurement. Relative rate constants are typically measured with greater relative accuracy than corresponding absolute rate constant measurements. This greater accuracy leads to a smaller 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 delay time and show that constraints in parameter space from relative rate measurements lead to significantly smaller uncertainty in the output ignition delay time. Implications 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.
International Journal of Chemical Kinetics


"Uncertainty Quantification", "Combustion", "Model Optimization", "Detailed Kinetic Models"


Manion, J. and McGivern, W. (2016), The Importance of Relative Reaction Rates in the Optimization of Detailed Kinetic Models, International Journal of Chemical Kinetics, [online], (Accessed April 18, 2024)
Created April 26, 2016, Updated February 19, 2017