A high-dimensional, stochastic model for twin-screw granulation – part 1: model description
In this work we present a novel four-dimensional, stochastic population balance model for twin-screw granulation. The model uses a compartmental framework to reflect changes in mechanistic rates between different screw element geometries. This allows us to capture the evolution of the material along...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/107589 http://hdl.handle.net/10220/50342 |
| _version_ | 1824454670573109248 |
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| author | McGuire, Andrew D. Mosbach, Sebastian Lee, Kok Foong Reynolds, Gavin Kraft, Markus |
| author2 | School of Chemical and Biomedical Engineering |
| author_facet | School of Chemical and Biomedical Engineering McGuire, Andrew D. Mosbach, Sebastian Lee, Kok Foong Reynolds, Gavin Kraft, Markus |
| author_sort | McGuire, Andrew D. |
| collection | NTU |
| description | In this work we present a novel four-dimensional, stochastic population balance model for twin-screw granulation. The model uses a compartmental framework to reflect changes in mechanistic rates between different screw element geometries. This allows us to capture the evolution of the material along the barrel length. The predictive power of the model is assessed across a range of liquid-solid feed ratios through comparison with experimental particle size distributions. The model results show a qualitative agreement with experimental trends and a number of areas for model improvement are discussed. A sensitivity analysis is carried out to assess the effect of key operating variables and model parameters on the simulated product particle size distribution. The stochastic treatment of the model allows the particle description to be readily extended to track more complex particle properties and their transformations. |
| first_indexed | 2025-02-19T03:26:00Z |
| format | Journal Article |
| id | ntu-10356/107589 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:26:00Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/1075892023-12-29T06:53:40Z A high-dimensional, stochastic model for twin-screw granulation – part 1: model description McGuire, Andrew D. Mosbach, Sebastian Lee, Kok Foong Reynolds, Gavin Kraft, Markus School of Chemical and Biomedical Engineering Granulation Stochastic Engineering::Chemical engineering In this work we present a novel four-dimensional, stochastic population balance model for twin-screw granulation. The model uses a compartmental framework to reflect changes in mechanistic rates between different screw element geometries. This allows us to capture the evolution of the material along the barrel length. The predictive power of the model is assessed across a range of liquid-solid feed ratios through comparison with experimental particle size distributions. The model results show a qualitative agreement with experimental trends and a number of areas for model improvement are discussed. A sensitivity analysis is carried out to assess the effect of key operating variables and model parameters on the simulated product particle size distribution. The stochastic treatment of the model allows the particle description to be readily extended to track more complex particle properties and their transformations. Accepted version 2019-11-06T01:37:43Z 2019-12-06T22:35:02Z 2019-11-06T01:37:43Z 2019-12-06T22:35:02Z 2018 Journal Article McGuire, A. D., Mosbach, S., Lee, K. F., Reynolds, G., & Kraft, M. (2018). A high-dimensional, stochastic model for twin-screw granulation - part 1: model description. Chemical Engineering Science, 188221-237. doi:10.1016/j.ces.2018.04.076 0009-2509 https://hdl.handle.net/10356/107589 http://hdl.handle.net/10220/50342 10.1016/j.ces.2018.04.076 en Chemical Engineering Science © 2018 Elsevier. All rights reserved. This paper was published in Chemical Engineering Science and is made available with permission of Elsevier. 51 p. application/pdf |
| spellingShingle | Granulation Stochastic Engineering::Chemical engineering McGuire, Andrew D. Mosbach, Sebastian Lee, Kok Foong Reynolds, Gavin Kraft, Markus A high-dimensional, stochastic model for twin-screw granulation – part 1: model description |
| title | A high-dimensional, stochastic model for twin-screw granulation – part 1: model description |
| title_full | A high-dimensional, stochastic model for twin-screw granulation – part 1: model description |
| title_fullStr | A high-dimensional, stochastic model for twin-screw granulation – part 1: model description |
| title_full_unstemmed | A high-dimensional, stochastic model for twin-screw granulation – part 1: model description |
| title_short | A high-dimensional, stochastic model for twin-screw granulation – part 1: model description |
| title_sort | high dimensional stochastic model for twin screw granulation part 1 model description |
| topic | Granulation Stochastic Engineering::Chemical engineering |
| url | https://hdl.handle.net/10356/107589 http://hdl.handle.net/10220/50342 |
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