Analysing the effect of screw configuration using a stochastic twin-screw granulation model

In this work, a framework for modelling twin-screw granulation processes with variable screw configurations using a high-dimensional stochastic population balance method is presented. A modular compartmental approach is presented and a method for estimating residence times for model compartments bas...

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Main Authors: McGuire, Andrew D., Mosbach, Sebastian, Reynolds, Gavin K., Patterson, Robert I. A., Bringley, Eric, Eaves, Nick, Dreyer, Jochen A. H., Kraft, Markus
Other Authors: School of Chemical and Biomedical Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/143459
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1434592023-12-29T06:53:55Z Analysing the effect of screw configuration using a stochastic twin-screw granulation model McGuire, Andrew D. Mosbach, Sebastian Reynolds, Gavin K. Patterson, Robert I. A. Bringley, Eric Eaves, Nick Dreyer, Jochen A. H. Kraft, Markus School of Chemical and Biomedical Engineering Engineering::Chemical engineering Granulation Twin-screw In this work, a framework for modelling twin-screw granulation processes with variable screw configurations using a high-dimensional stochastic population balance method is presented. A modular compartmental approach is presented and a method for estimating residence times for model compartments based on screw element geometry is introduced. The model includes particle mechanisms for nucleation, primary particle layering, coalescence, breakage, and consolidation. A new twin-screw breakage model is introduced, which takes into account the differing breakage dynamics between two types of screw element. Additionally, a new sub-model for the layering of primary particles onto larger agglomerates is presented. The resulting model is used to simulate a twin-screw system with a number of different screw configurations and the predictive power of the model is assessed through comparison with an existing experimental data set in the literature. For most of the screw configurations simulated, the model predicts the product particle size distribution at large particle sizes with a reasonable degree of accuracy. However, the model has a tendency to over-predict the amount of fines in the final product. Nevertheless, the model qualitatively captures the reduction in fines associated with an increase in the number of kneading elements, as observed experimentally. Based on model results, a number of key areas for future model development are identified and discussed. National Research Foundation (NRF) Accepted version ADM acknowledge funding from EPSRC Grant 1486478 and AstraZeneca. ADM would also like to thank C.T. Lao for useful conversations regarding the implementation of the nucleation process. RP acknowledges support from the Deutsche Forschungsgemeinschaft (DFG) through grant CRC 1114 ‘‘Scaling Cascades in Complex Systems”, Project C08. This project was partly funded by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. 2020-09-02T08:34:44Z 2020-09-02T08:34:44Z 2019 Journal Article McGuire, A. D., Mosbach, S., Reynolds, G. K., Patterson, R. I. A., Bringley, E., Eaves, N., ... Kraft, M. (2019). Analysing the effect of screw configuration using a stochastic twin-screw granulation model. Chemical Engineering Science, 203, 358-379. doi:10.1016/j.ces.2019.03.078 0009-2509 https://hdl.handle.net/10356/143459 10.1016/j.ces.2019.03.078 2-s2.0-85064086144 203 358 379 en Chemical Engineering Science © 2019 Elsevier Ltd. All rights reserved. This paper was published in Chemical Engineering Science and is made available with permission of Elsevier Ltd. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Chemical engineering
Granulation
Twin-screw
spellingShingle Engineering::Chemical engineering
Granulation
Twin-screw
McGuire, Andrew D.
Mosbach, Sebastian
Reynolds, Gavin K.
Patterson, Robert I. A.
Bringley, Eric
Eaves, Nick
Dreyer, Jochen A. H.
Kraft, Markus
Analysing the effect of screw configuration using a stochastic twin-screw granulation model
description In this work, a framework for modelling twin-screw granulation processes with variable screw configurations using a high-dimensional stochastic population balance method is presented. A modular compartmental approach is presented and a method for estimating residence times for model compartments based on screw element geometry is introduced. The model includes particle mechanisms for nucleation, primary particle layering, coalescence, breakage, and consolidation. A new twin-screw breakage model is introduced, which takes into account the differing breakage dynamics between two types of screw element. Additionally, a new sub-model for the layering of primary particles onto larger agglomerates is presented. The resulting model is used to simulate a twin-screw system with a number of different screw configurations and the predictive power of the model is assessed through comparison with an existing experimental data set in the literature. For most of the screw configurations simulated, the model predicts the product particle size distribution at large particle sizes with a reasonable degree of accuracy. However, the model has a tendency to over-predict the amount of fines in the final product. Nevertheless, the model qualitatively captures the reduction in fines associated with an increase in the number of kneading elements, as observed experimentally. Based on model results, a number of key areas for future model development are identified and discussed.
author2 School of Chemical and Biomedical Engineering
author_facet School of Chemical and Biomedical Engineering
McGuire, Andrew D.
Mosbach, Sebastian
Reynolds, Gavin K.
Patterson, Robert I. A.
Bringley, Eric
Eaves, Nick
Dreyer, Jochen A. H.
Kraft, Markus
format Article
author McGuire, Andrew D.
Mosbach, Sebastian
Reynolds, Gavin K.
Patterson, Robert I. A.
Bringley, Eric
Eaves, Nick
Dreyer, Jochen A. H.
Kraft, Markus
author_sort McGuire, Andrew D.
title Analysing the effect of screw configuration using a stochastic twin-screw granulation model
title_short Analysing the effect of screw configuration using a stochastic twin-screw granulation model
title_full Analysing the effect of screw configuration using a stochastic twin-screw granulation model
title_fullStr Analysing the effect of screw configuration using a stochastic twin-screw granulation model
title_full_unstemmed Analysing the effect of screw configuration using a stochastic twin-screw granulation model
title_sort analysing the effect of screw configuration using a stochastic twin-screw granulation model
publishDate 2020
url https://hdl.handle.net/10356/143459
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