Alizadeh, M, Hassanpour, A orcid.org/0000-0002-7756-1506, Pasha, M et al. (2 more authors) (2017) The effect of particle shape on predicted segregation in binary powder mixtures. Powder Technology, 319. pp. 313-322. ISSN 0032-5910
Abstract
Particle shape driven segregation in particulate mixtures has received limited attention in the literature either experimentally or via simulation. This study investigates the shape driven segregation which occurs during the process of heap formation and evaluates the ability of different Discrete Element Method (DEM) simulation approaches to predict the effect. It shows experimentally that the difference in particle shape can drive segregation in a binary mixture and that this segregation can be predicted by DEM models which resolve the particle shape. In this case shape is resolved via a clumped sphere approach. Importantly, the work also demonstrates that simpler models using spherical particles, with rolling friction calibrated to reproduce the experimental angle of repose, tend to underestimate the segregation tendency. The system studied was a binary mixture of irregular shaped particles, a typical spray dried detergent powder and a granulated detergent additive; particle shapes were obtained using X-ray microtomography.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2017 Published by Elsevier B.V. This is an author produced version of a paper published in Powder Technology. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Granular segregation, DEM, Discrete Element Method, clumped spheres, rolling friction, spray dried powder, binary mixture |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Funding Information: | Funder Grant number Innovate UK fka Technology Strategy Board (TSB) 31587-233189 |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Jun 2017 12:35 |
Last Modified: | 01 Jul 2018 00:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.powtec.2017.06.059 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:118401 |