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
ow. Number of closures for both breakup and
coalescence can be identi ed in the literature and most of them need an estimation of model
parameters that can di er 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 identi cation 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 di erent
ows over wide range of Reynolds numbers
