Publication:
Dense Medium Cyclone: From Fundamental Simulation to Process Application

dc.contributor.advisor Yu, Aibing en_US
dc.contributor.advisor Chu, Kaiwei en_US
dc.contributor.advisor Vince, Andrew en_US
dc.contributor.author Chen, Jiang en_US
dc.date.accessioned 2022-03-21T14:16:34Z
dc.date.available 2022-03-21T14:16:34Z
dc.date.issued 2014 en_US
dc.description.abstract Dense medium cyclone (DMC) is a high-tonnage device that is widely used to upgrade run-of-mine coal in the coal industry. It is known that the complicated multiphase flow in the DMC is technically difficult and expensive to experimentally investigate. In recent years, with the development of computational technology, various mathematical models based on the flow fundamentals such as computational fluid dynamics (CFD) and its combination with discrete element method (DEM) have been shown to be effective in overcoming this difficulty. In practice, the material properties fed in the DMC such as coal particle density and size distribution and their interaction are important variables affecting the DMC performance. Particularly, many problems frequently confronted in the operation of DMCs (e.g., vortex finder/spigot overloading, surging and system instability) are basically related to these variables. Although many studies have been done to help understand the underlying mechanisms, no systematic study has been made to examine the effects of these variables on DMC performance. In this work, the effects of particle density and size distribution and their interaction are systematically studied using a previously developed CFD-DEM model. In particular, Johnson s SB function, which is able to describe a wide range of distribution, is employed to represent the particle density and/or size distribution. The simulation results are analysed in terms of medium and particle flow patterns, particle-fluid, particle-particle and particle-wall interaction forces to elucidate the mechanisms. Based on the newly obtained CFD-DEM results in this thesis, a previously developed PC-based DMC model, which can readily run on a personal computer (PC), to predict the DMC performance as a function of a range of variables in an easy, fast and cost-effective way, is further developed and extended. Finally, the extended PC-based model is used to optimize the DMC designs for coal preparation through representative examples, in comparison with several typical designs in the industry. In addition, some new rules for DMC scale-up are proposed to meet industrial needs. It is shown that the developed PC-based model can indeed offer a cost-effective way to design, operate and optimize DMC process under different conditions. en_US
dc.identifier.uri http://hdl.handle.net/1959.4/53579
dc.language English
dc.language.iso EN en_US
dc.publisher UNSW, Sydney en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/au/ en_US
dc.subject.other Dense medium cyclone (DMC) en_US
dc.subject.other Computational fluid dynamics (CFD) en_US
dc.subject.other Discrete element method (DEM) en_US
dc.subject.other Johnson s SB function en_US
dc.subject.other DMC performance en_US
dc.subject.other Process Application en_US
dc.title Dense Medium Cyclone: From Fundamental Simulation to Process Application en_US
dc.type Thesis en_US
dcterms.accessRights open access
dcterms.rightsHolder Chen, Jiang
dspace.entity.type Publication en_US
unsw.accessRights.uri https://purl.org/coar/access_right/c_abf2
unsw.identifier.doi https://doi.org/10.26190/unsworks/16888
unsw.relation.faculty Science
unsw.relation.originalPublicationAffiliation Chen, Jiang, Materials Science & Engineering, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Yu, Aibing, Materials Science & Engineering, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Chu, Kaiwei, Materials Science & Engineering, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Vince, Andrew, Elsa Consulting Group en_US
unsw.relation.school School of Materials Science & Engineering *
unsw.thesis.degreetype PhD Doctorate en_US
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