Liquid–liquid
mixings in stirred tanks are commonly found
in many industries. In this study, we performed computational fluid
dynamics (CFD) modeling and simulation to investigate the liquid–liquid
mixing behavior. Furthermore, the population balance model (PBM) was
used to characterize the droplet size distribution. The PBM model
parameters were calibrated using the experimental data of droplet
sizes at different agitation speeds. Additionally, we employed the
steady-state Sauter mean droplet size to validate the developed CFD–PBM
coupled model at different dispersion phase holdups. Then, the validated
CFD–PBM coupled model was employed to evaluate the role of
impeller structural parameters on the liquid–liquid mixing
efficiency based on a user-defined mixing index. It was found that
the position of impellers significantly affects the mixing efficiency,
and an increase in stirring speed and the number of impellers improved
the mixing efficiency.