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Lookup NU author(s): Dr Colin HareORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2022 The Society of Powder Technology JapanMany granular materials change their volume as they absorb fluids. This phenomenon is called swelling and can be observed in a variety of solids, such as soils, wood, absorbent hygiene products (AHPs) and pharmaceutical excipients. Therefore, an in-depth understanding of grain swelling is of great importance. Since experimental investigations can often provide only limited information, while great insight could be gained from numerical modelling, rigorous numerical models for predicting particle swelling are required. Hence, the objective of this research is to develop and validate a Discrete Element Method (DEM) for swelling of particles. A first order kinetic model was employed to predict the volume expansion of a single grain and subsequently implemented in DEM. The validation of the model was accomplished by comparing the expansion with time of a packed bed made of super absorbent polymer (SAP) particles obtained numerically and experimentally. It was shown that the DEM model can accurately predict the bed expansion. The model was then employed to simulate the swelling of three different materials: superabsorbent polymer (SAP), rice and microcrystalline cellulose (MCC Avicel PH102). As expected, it is demonstrated that the material properties play a significant role on the swelling; the fastest to reach its maximum expansion is the granular bed made of MCC PH102, followed by SAP and rice. However, the highest swelling capacity is achieved with SAP. Moreover, a preliminary DEM analysis of the segregation in a swelling binary mixture is presented in this work. Results suggest that systems which contain a small number of particles, and thus are looser, are more prone to segregation. Future study could advance the developed model to analyse consequences of swelling phenomena in granular materials, such as segregation and heat generation.
Author(s): Braile D, Hare C, Wu C-Y
Publication type: Article
Publication status: Published
Journal: Advanced Powder Technology
Year: 2022
Volume: 33
Issue: 11
Print publication date: 01/11/2022
Online publication date: 29/09/2022
Acceptance date: 17/09/2022
Date deposited: 17/10/2022
ISSN (print): 0921-8831
ISSN (electronic): 1568-5527
Publisher: Elsevier B.V.
URL: https://doi.org/10.1016/j.apt.2022.103806
DOI: 10.1016/j.apt.2022.103806
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