Evaluation of mean species mass fractions in premixed turbulent flames: A DNS study

International audience; Direct Numerical Simulation (DNS) data obtained by Dave and Chaudhuri (2020) from a lean, complex-chemistry, hydrogen-air flame associated with the thin-reaction-zone regime of premixed turbulent burning are analyzed (by adapting five alternative definitions of combustion progress variable c) in order to examine three different models that (i) are based on the flamelet paradigm and (ii) aim at evaluating mean concentrations of various species in applied CFD research into turbulent combustion. Mean mole fractions of all considered species and mean density are predicted if the laminar-flame profiles of species mole fractions and density, respectively, are directly averaged using a Probability Density Function (PDF) P(c). The best predictions are obtained by extracting P(c) from the DNS data and defining c based on hydrogen mass fraction. These predictions suggest that mean mole fractions of various species in a premixed turbulent flame can be evaluated at a post-processing stage of a CFD study by adopting P(c), obtained at the major stage of the simulations, to average a flamelet library. When applied in such a way, the flamelet paradigm is useful even for lean hydrogen-air flames and even at Karlovitz number as large as 13. If the same PDF is applied to average reaction rates from the same flamelet library, the mean rates of production/consumption of species n are poorly predicted, e.g. for radicals H, O, OH, HO2, and H2O2 if c is defined using hydrogen mass fraction. A hypothesis that conditioned rates 〈Wn|c〉 can be predicted using conditioned mole fractions 〈Xn|c〉, temperature 〈T|c〉, and density 〈ρ|c〉 is not supported either, e.g. for radicals O and OH. These differences between predictive capabilities of the first approach (directly averaging concentration profiles) and two other approaches (averaging reaction rates) are attributed to weakly (highly) non-linear dependencies of the concentrations (rates, respectively) on c.