Computational Fluid Dynamics and Population Balance Model Enhances the Smart Manufacturing and Performance Optimization of an Innovative Precipitation Reactor

In this study, we propose the study of an innovative precipitation prototype designed by ResourSEAs, guided by a CFD-PBM (Computational Fluid Dynamics and Population Balance Model) approach, aiming to understand the influence of reactant concentration and nozzle orientation on precipitation processes. The first part of the study examines the effect of reactant concentration on supersaturation and the zeroth-order moment ((Formula presented.)) within a controlled flow and turbulence fields. Three different concentrations of (Formula presented.) (0.1, 0.3, and 0.6 M) and (Formula presented.) (0.005, 0.01, and 0.02 M) were tested, resulting in varying supersaturation profiles and (Formula presented.) fields. Our results show that, under equal turbulence conditions, increasing the concentration of reactants beyond a certain point actually slows down mixing, which in turn hinders the generation of supersaturation. As a result, supersaturation profiles become nearly identical to those of lower concentrations, despite having consumed more reactants. The second part of this study focuses on the effect of nozzle orientation and positioning along the prototype axis on reactant mixing and particle formation. The simulations reveal that nozzle orientation has a significant impact on the formation of primary particles, especially when positioned in low-velocity regions, leading to slower mixing and greater particle growth. Conversely, high-velocity regions promote faster mixing and more intense aggregation. These findings highlight the interplay between concentration, nozzle orientation, and flow conditions in determining precipitation efficiency, offering insights for optimizing reactor design in industrial applications.