(428e) Predictive Modeling for Particle Dissolution in Mixing Tanks

Particle dissolution is an important process for a variety of applications in the food, pharmaceutics and the process industry. Accurate prediction of the dissolution time is essential to optimize process parameter like subsequent ingredient additions, RPM, and mixing vessel geometry such as baffles. In this study, an Eulerian-Lagrangian model was developed in STAR-CCM+ to simulate particle dissolution in mixing applications: benchtop beakers and pilot scale mix tanks. The continuous liquid phase and the Lagrangian particle phase was two-way coupled, therefore each particle dissolved based on its own local mass transfer coefficient and concentration gradient with continuous phase, thus capturing the spatio-temporal variation in the dissolution process. The model was validated against experiments for two different powders by comparing the dissolution time. The model showed excellent agreement in terms of predicting when the last particle would be dissolved to within seconds. Based on the simulation results, an analytical expression is suggested for the dissolution time to aid in design estimation.