In this work, steady-state droplet size distributions in a DN300 stirred batch vessel with a Rushton turbine impeller are investigated using an insertion probe based on the telecentric transmitted light principle. High-resolution droplet size distributions are extracted from the images using a convolutional neural network for image-analysis in order to investigate the influence of impeller speed and phase fraction (up to 50 vol.-%). In addition, Sauter mean diameters were calculated and correlated with two semi-empirical approaches, while the standard approach only accomplished 5.7% accuracy, and the correlation of Laso et al. provided a relative mean error of 4.0%. In addition, the correlated exponent in the Weber number was fitted to the experimental data of this work yielding a slightly different value than the theoretical (−0.6), which allows a better representation of the low coalescence tendency of the system, which is usually neglected in standard procedures.

The fluid dynamic (flow rates) and hydrodynamic behavior (local droplet size distributions and local holdup) of a continuous DN300 pump-mixer were investigated using water as the continuous phase and paraffin oil as the dispersed phase. The influence of the impeller speed ($N$= 375 to 425 rpm), the feed phase ratio (${\phi }_F$ = 10 to 30 vol.-%), and the flow rate (${\dot{V}}_{tot}$ ≈ 0.5 to 2.3 L/min) were investigated by measuring the pumping height, local holdup of the disperse phase, and the droplet size distribution (DSD). The latter one was measured at three different vessel positions using an image-based telecentric shadowgraphic technique. The droplet diameters were extracted from the acquired images using a neural network. The Sauter mean diameters were calculated from the DSD and correlated with an extended model based on Doulah (1975), considering the impeller speed, the feed phase ratio, and additionally the flow rate. The new correlation can describe an extensive database containing 155 experiments of the fluid and hydrodynamic within a 15% error range.