A multi-scale, mechanistic model of a wet granulation process using a novel bi-directional PBM–DEM coupling algorithm. (17th February 2015)

• Record Type: Journal Article
• Authors: Barrasso, Dana; Eppinger, Thomas; Pereira, Frances E.; Aglave, Ravindra; Debus, Kristian; Bermingham, Sean K.; Ramachandran, Rohit
• Is Part Of: Chemical engineering science. Volume 123(2015)
• Page Start: 500
• Page End: 513
• Publication Date: 2015-02-17
• Subjects: Wet granulation -- Population balance modeling -- Discrete element methods -- Multi-scale modeling -- Quality-by-Design; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2014.11.011
• Languages: English
• ISSNs: 0009-2509

Abstract

Abstract: In this study, a novel mechanistic model for a wet granulation process is presented, combining the techniques of population balance modeling and discrete element methods to predict critical quality attributes of the granule product, such as porosity and size distribution. When applied to a twin screw granulation process, the model shows sensitivities to the screw element type and geometry, as well as material properties (binder viscosity, pore saturation) and process parameters (screw speed, liquid-to-solid ratio). Predicted trends are consistent with experimental observations in the literature. Using this modeling framework, a model-based approach can be used to implement Quality by Design, establishing a design space to transition towards a quantitative mechanistic understanding of wet granulation processes. Abstract : Highlights: A multi-scale, mechanistic model of a wet granulation process is developed. An efficient bi-directional coupling algorithm is implemented to exchange data between models. Particle-scale information from DEM simulations is used to evaluate rate expressions in the PBM. Sensitivities to process parameters, material properties, and equipment geometry are demonstrated.