Yu, X., Hounslow, M.J. orcid.org/0000-0003-0439-3641, Reynolds, G.K. et al. (3 more authors) (2017) A compartmental CFD-PBM model of high shear wet granulation. AIChE Journal, 63 (2). pp. 438-458. ISSN 0001-1541
Abstract
The conventional, geometrically lumped description of the physical processes inside a high shear granulator is not reliable for process design and scale-up. In this study, a compartmental Population Balance Model (PBM) with spatial dependence is developed and validated in two lab-scale high shear granulation processes using a 1.9L MiPro granulator and 4L DIOSNA granulator. The compartmental structure is built using a heuristic approach based on computational fluid dynamics (CFD) analysis, which includes the overall flow pattern, velocity and solids concentration. The constant volume Monte Carlo approach is implemented to solve the multi-compartment population balance equations.Different spatial dependent mechanisms are included in the compartmental PBM to describe granule growth. It is concluded that for both cases (low and high liquid content), the adjustment of parameters (e.g. layering, coalescence and breakage rate) can provide a quantitative prediction of the granulation process.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is the peer reviewed version of the following article: Yu, X., Hounslow, M. J., Reynolds, G. K., Rasmuson, A., Niklasson Björn, I. and Abrahamsson, P. J. (2017), A compartmental CFD-PBM model of high shear wet granulation. AIChE J., 63: 438–458, which has been published in final form at https://doi.org/10.1002/aic.15401. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. |
Keywords: | high shear wet granulation; population balance model; multiple compartments; Monte Carlo; CFD |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) |
Funding Information: | Funder Grant number ASTRAZENECA UK LTD NONE |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 26 Apr 2017 10:29 |
Last Modified: | 16 Jan 2020 16:55 |
Published Version: | https://doi.org/10.1002/aic.15401 |
Status: | Published |
Publisher: | Wiley |
Refereed: | Yes |
Identification Number: | 10.1002/aic.15401 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:115535 |