Coalescence in a droplet cloud is studied in this work by means of direct numerical simulation of the turbulent gas flow, which is coupled with a Lagrangian tracking of the disperse phase. In a first step, a collision detection algorithm is developed and validated, which can account for a polydisperse phase. This algorithm is then implemented into an existing code for direct numerical simulations coupled with a Lagrangian tracking scheme. Second, simulations are performed for the configuration of homogeneous isotropic turbulence of the fluid phase and a disperse phase in local equilibrium with the fluid. The influence of both droplet inertia and turbulence intensity on the coalescence rate of droplets is discussed in a pure permanent coalescence regime. First results are given, if other droplet collision outcomes than permanent coalescence (i.e. stretching and reflexive separation) are considered. These results show a strong dependence on the droplet inertia via the relative velocity of the colliding droplets at the moment of collision. The performed simulations serve also as reference data base for the development and validation of statistical modeling approaches, which can be used for simulations of industrial problems. In particular, the simulation results are compared to predictions from a Lagrangian Monte-Carlo type approach and the Eulerian 'Direct Quadrature Method of Moments' (DQMOM) approach. Different closures are validated for the coalescence terms in these approaches, which are based either on the assumption of molecular-chaos, or based on a formulation, which allows to account for the correlation of droplet velocities before collision by the fluid turbulence. It is shown that the latter predicts much better the coalescence rates in comparison with results obtained by the performed deterministic simulations.
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