Due to the inherent uncertainties in combustion kinetic model parameters, especially the rate coefficients of elementary reactions, the uncertainties of model predictions can be quite large. Uncertainty minimization using experimental measurements can reduce the parameter uncertainty space of the rate coefficients of elementary reactions, and further reduce the uncertainties of model predictions. The experiment cost will be significantly reduced if we can conduct the combustion experiments on the conditions which have the most significant constraint effects on the validation of the combustion kinetic model. The sensitivity entropy is a quantitative measure of the degree of dispersion of uncertainty sources for an output target of a kinetic model. The smaller the sensitivity entropy is, the lower degree of dispersion of uncertainty sources will be. The experiment target with low disperse uncertainty sources can provide strong constraint on the rate coefficients of specific reactions. The calculation of sensitivity entropy can be conducted on the condition where the experiment can be conducted. An application of the sensitivity entropy is to find the experiment conditions which have the most significant influences on the constraint of the model input parameter space. Figure 1 shows the experimental conditions (dilution ratio, equivalence ratio etc.) can be selected for further experiments by sensitivity entropy analysis. Further details can be found in "Using sensitivity entropy in experimental design for uncertainty minimization of combustion kinetic models", Proc. Combust. Inst., 36, 709-716 (2017).

Figure 1. Experimental conditions selected based on sensitivity entropy.