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|Title:||Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method||Authors:||Lee, Kok Foong
McGuire, Andrew D.
|Keywords:||Stochastic Weighted Algorithm
|Issue Date:||2017||Source:||Lee, K. F., Dosta, M., McGuire, A. D., Mosbach, S., Wagner, W., Heinrich, S., et al. (2017). Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method. Computers & Chemical Engineering, 99, 171-184.||Series/Report no.:||Computers and Chemical Engineering||Abstract:||This paper presents a multi-compartment population balance model for wet granulation coupled with DEM (discrete element method) simulations. Methodologies are developed to extract relevant data from the DEM simulations to inform the population balance model. First, compartmental residence times are calculated for the population balance model from DEM. Then, a suitable collision kernel is chosen for the population balance model based on particle–particle collision frequencies extracted from DEM. It is found that the population balance model is able to predict the trends exhibited by the experimental size and porosity distributions by utilising the information provided by the DEM simulations.||URI:||https://hdl.handle.net/10356/88020
|ISSN:||0098-1354||DOI:||http://dx.doi.org/10.1016/j.compchemeng.2017.01.022||Rights:||© 2017 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Computers and Chemical Engineering, Elsevier Ltd. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.compchemeng.2017.01.022].||metadata.item.grantfulltext:||open||metadata.item.fulltext:||With Fulltext|
|Appears in Collections:||SCBE Journal Articles|
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