Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88020
Title: Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method
Authors: Lee, Kok Foong
Dosta, Maksym
McGuire, Andrew D.
Mosbach, Sebastian
Wagner, Wolfgang
Heinrich, Stefan
Kraft, Markus
Keywords: Stochastic Weighted Algorithm
Granulation
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
http://hdl.handle.net/10220/44503
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

Google ScholarTM

Check

Altmetric

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.