Challenges arise when operating in a larger scale or an industrial-scale process where engineering design is limited. Mixing process often occurs in a production-scale mixer with more than 10-fold increase in overall capacity which renders difficulty in predicting mixing performance and thus achieving the degree of homogeneity. Insufficient mixing could lead to poor product efficacy. Computational fluid dynamic (CFD) is an increasingly important computational tool used for in silico prediction of hydrodynamics and understanding of the complex flow behavior of the reactors, based on the solution of appropriate conservation equations of mass, momentum, and energy. In our studies, we use the numerical method to predict many critical scale-up parameters, i.e., strain rate, power dissipation, mass transfer coefficient, mixing time, etc. As a result, CFD is a promising model to provide in-depth insight into mixing phenomenon. It could be considered to maximize efficiency and reduce costs associated with scaling up/down processes, technology transfers, and validating bioprocesses.
