in Wiley InterScience (www.interscience.wiley.com).A new hybrid approach to model powder mixing based on the use of discrete element method (DEM) and compartment modeling is presented. The main motivation behind the proposed approach is to reduce the computational expense of modeling powder mixing by partitioning the mixing system into high shear areas that are modeled using detailed DEM simulations, whereas the remaining process is simulated using stochastic models. The approach can, thus, be used to model complex geometries, as well as a large number of particles that is typically unfeasible with the existing approaches. The results of a horizontal convective mixing vessel are used to illustrate the applicability and efficiency of the proposed approach.
In this paper, the development of a compartment model to simulate mixing within a continuous blender is reported. The main benefit of the method is that it can generate extensive modeling predictions in very short computational time. The model can also be used to explore the effect of sampling parameters on estimated mixing performance, a topic that has been central to pharmaceutical manufacturing for the past 15 years and that remains a central issue in the PAT initiative. However, this method requires more input than conventional particle dynamics methods. Thus, we investigate the effects of modeling parameters on mixing performance to develop general guidance needed to adapt this modeling framework to any continuous process. An experimental technique based on longitudinal sampling is used to examine the content uniformity of the blend along the continuous mixer. The model compares favorably with continuous mixing experiments, capture the effects of feeding rate variability, active product ingredient concentration, and blender processing angle, while effectively capturing and making explicit the effect of sampling parameters such as number of samples and sample size. The modeling approach provides a convenient tool for process design.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.