A compartmental CFD-PBM model of high shear wet granulation


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.

Publication DOI: https://doi.org/10.1002/aic.15401
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Chemical Engineering & Applied Chemistry
College of Engineering & Physical Sciences > Energy and Bioproducts Research Institute (EBRI)
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., & Abrahamsson, P. J. (2017). A compartmental CFD-PBM model of high shear wet granulation. AIChE Journal, 63(2), 438-458, which has been published in final form at http://dx.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.
Uncontrolled Keywords: high shear wet granulation,population balance model,multiple compartments,Monte Carlo,CFD,Chemical Engineering(all),Biotechnology,Environmental Engineering
Publication ISSN: 1547-5905
Last Modified: 15 Apr 2024 07:17
Date Deposited: 28 Jun 2016 11:10
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2017-02
Published Online Date: 2016-07-15
Accepted Date: 2016-06-23
Submitted Date: 2015-10-30
Authors: Yu, Xi (ORCID Profile 0000-0003-3574-6032)
Hounslow, Michael J
Reynolds, Gavin K
Rasmuson, Anders
Niklasson Björn, Ingela
Abrahamsson, Per J



Version: Accepted Version

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