Abstract
This chapter analyzes the deterministic approach of direct numerical simulation (DNS) and the probabilistic approach of probability density function (PDF) modeling. These approaches are implemented for the prediction of droplet dispersion and polydispersity in liquid–fuel combustors. These modeling approaches are used for predicting two-phase turbulent flows. The DNS is focused on generating information useful in designing the experiment on the backward-facing step with countercurrent flow, which closely represents the dump combustor flow situation. DNS allows the quantification and visualization of various effects arising because of the different inlet flow conditions, Stokes number of the dispersed phase, and strength of the countercurrent flow. The DNS data are valuable in the development and assessment of predictive models. The chapter discusses the development of PDF model for a general situation of turbulent flow laden with evaporating droplets. This model is in the form of a closed equation, which governs the transport of the probability density of droplet position, velocity, temperature, and diameter.
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