A Study on Mixing Time and Vortex Formation in Biopharmaceutical Mixing Processes

In biopharmaceutical mixing processes, robust and optimum mixing parameters, namely impeller's speed and mixing time, should be determined to provide sufficient mixing while avoiding undesirable conditions that may affect product quality. An undesirable condition for protein drug substances is air entrainment, which happens when a strong vortex is formed. Computational fluid dynamics (CFD) methods can inform about mixing time and vortex formation, and there are currently several commercially available CFD methods that can be used. However, it is quite important to establish specific CFD methods for each of these parameters to reduce the computational time and at the same time obtain physically acceptable results. The aim of this work was to determine efficient CFD methods to simulate the time of mixing and vortex depth, and validate them against experiments. To this end, experiments and numerical simulations were conducted. Simulations were validated against the experimental results and were used along with the experiments to determine the optimum mixing parameters. It was found that for the vortex depth predictions, steady state simulations with Reynolds stress model, and for mixing time predictions, transient simulations with sliding mesh and k-omega model are the most efficient among the tested CFD methods.