A new approach to chemistry modelling for large-eddy simulation of turbulent reacting flows is developed. Instead of solving transport equations for all of the numerous species in a typical chemical mechanism and modelling the unclosed chemical source terms, the present study adopts an indirect mapping approach, whereby all of the detailed chemical processes are mapped to a reduced system of tracking scalars. Here, only two such scalars are considered: a mixture fraction variable, which tracks the mixing of fuel and oxidizer, and a progress variable, which tracks the global extent of reaction of the local mixture. The mapping functions, which describe all of the detailed chemical processes with respect to the tracking variables, are determined by solving quasi-steady diffusion-reaction equations with complex chemical kinetics and multicomponent mass diffusion. The performance of the new model is compared to fast-chemistry and steady-flamelet models for predicting velocity, species concentration, and temperature fields in a methane-fuelled coaxial jet combustor for which experimental data are available. The progress-variable approach is able to capture the unsteady, lifted flame dynamics observed in the experiment, and to obtain good agreement with the experimental data, while the fast-chemistry and steady-flamelet models both predict an attached flame.
The dynamic procedure is applied to the problem of modeling the subgrid-scale variance and dissipation rate of a conserved scalar in large eddy simulations of turbulent reacting flows. A simple scaling relation for the subgrid-scale variance is proposed, and the coefficient of the scaling law is obtained using the dynamic procedure. The variance dissipation rate is modeled by assuming equilibrium with the local variance production rate, which is obtained using a dynamic model. Example model predictions are obtained using actual large eddy simulation data, and the subgrid variance predicted by the dynamic model is compared to results obtained using a scale similarity model. Generalization of the approach to multiple scalars and nonconserved scalars is briefly discussed.
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