Spray-based turbulent reacting flows are an important class of engineering systems that have widespread use in the chemical processing industry. In such flows, a liquid jet is atomized and introduced into a gas-phase carrier. This atomized spray then evaporates and reacts with the carrier-phase. In aircraft engines and gas turbines, the resulting combustion reactions are highly exothermic and extremely sensitive to the local turbulent mixing process. Typically, combustion systems are classified as premixed or non-premixed flows based on the nature of mixing between fuel and oxidizer at the inlet. Based on this classification, models specific to the combustion regime (i.e., premixed or nor-premixed) are developed. Spray systems provide a unique challenge in that both non-premixed and premixed regimes can coexist in the same flow. The nature of flame propagation is determined by, among other factors, the spray dispersion in the gas-phase and the rate of mixing prior to reaction. This leads to a rich variety of flame structures and compounds the modeling process. While much of the work on spray combustion has focused on understanding spray dispersion, a comprehensive model for the combustion process is yet to be formulated.

In this work, we propose a novel large-eddy simulation/filtered-density function (LES/FDF) approach to modeling the spray combustion process. The filtered-density function, similar (but not identical) to a probability-density function, is used to characterize the sub-filter distribution of the gas-phase scalars. Here, unlike other methods, the chemical source appears closed. This unique property allows different combustion regimes to be represented using a single model. However, the sub-filter mixing term needs to be modeled. The transport equation for the FDF is high dimensional and cannot be solved using conventional Eulerian methods. The gas-phase velocity and turbulence information is obtained from the LES solver. A Monte-Carlo based stochastic method is used along with novel algorithms to ensure temporal accuracy and theoretical consistency of the coupled LES/FDF approach. The liquid spray droplets are simulated using a Lagrangian particle tracking scheme. Canonical flow configurations are used to demonstrate the feasibility of this new approach. Further, experiments from the University of Sydney are used to understand the impact of sub-filter models on predictive accuracy of the method. In particular, single-phase models for the sub-filter mixing term will be evaluated. A novel dynamic approach for determing the mixing time-scale used in these models will be presented.