  Population balance framework is a useful tool that can be used to describe
size distribution of droplets in a liquid-liquid dispersion. Breakup and
coalescence models provide closures for mathematical formulation of the
population balance equation (PBE) and are crucial for accu- rate predictions of
the mean droplet size in the flow. Number of closures for both breakup and
coalescence can be identified in the literature and most of them need an
estimation of model parameters that can differ even by several orders of
magnitude on a case to case basis. In this paper we review the fundamental
assumptions and derivation of breakup and coalescence ker- nels. Subsequently,
we rigorously apply two-stage optimization over several independent sets of
experiments in order to identify model parameters. Two-stage identification
allows us to estab- lish new parametric dependencies valid for experiments that
vary over large ranges of important non-dimensional groups. This be adopted for
optimization of parameters in breakup and co- alescence models over multiple
cases and we propose a correlation based on non-dimensional numbers that is
applicable to number of different flows over wide range of Reynolds numbers.
