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Probability based models for the power draw and energy spectra of a tumbling mill
Includes abstract.
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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Department of Chemical Engineering
2014
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| _version_ | 1867614079188729856 |
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| access_status_str | Open Access |
| author | Bbosa, Lawrence Sidney |
| author2 | Mainza, Aubrey |
| author_browse | Bbosa, Lawrence Sidney Mainza, Aubrey |
| author_facet | Mainza, Aubrey Bbosa, Lawrence Sidney |
| author_sort | Bbosa, Lawrence Sidney |
| collection | Thesis |
| description | Includes abstract. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/5347 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:46:20.280Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Department of Chemical Engineering |
| publisherStr | Department of Chemical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/5347 Probability based models for the power draw and energy spectra of a tumbling mill Bbosa, Lawrence Sidney Mainza, Aubrey Chemical Engineering Includes abstract. Includes bibliographical references. Positron Emission Particle Tracking (PEPT) and the Discrete Element Method (DEM) are used to develop probability based models for the power draw and collision energy spectra of a tumbling mill. Experiments are conducted using dry spherical glass bead charge in a laboratory scale tumbling mill, which is mounted with a torque transducer and tachometer to measure mill power. Particle tracking information from PEPT is used to reconstruct the motion of glass beads and infer the overall charge behaviour, while DEM is employed to simulate particle motion and interaction, with collision mechanics calculated using the Hertz-Mindlin contact model. For both sets of data, the product of torque and average angular velocities in discrete cells are accumulated to obtain mill power. This method is found to be within statistical agreement with measured power for all tests. The information from both techniques is then used to develop a model for the power draw as a function of particle size, mill speed and volumetric filling. Predictions of the model match well with measured and calculated values. Based on frequency distributions of collision energies from DEM, a model for the energy spectra of each particle size per steady state mill revolution is developed. This model is found to predict collision frequencies within close agreement with DEM simulation data and follows trends consistent with existing work on tumbling mill modelling. 2014-07-31T11:12:36Z 2014-07-31T11:12:36Z 2013 Doctoral Thesis Doctoral PhD http://hdl.handle.net/11427/5347 eng application/pdf Department of Chemical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Chemical Engineering Bbosa, Lawrence Sidney Probability based models for the power draw and energy spectra of a tumbling mill |
| thesis_degree_str | Doctoral |
| title | Probability based models for the power draw and energy spectra of a tumbling mill |
| title_full | Probability based models for the power draw and energy spectra of a tumbling mill |
| title_fullStr | Probability based models for the power draw and energy spectra of a tumbling mill |
| title_full_unstemmed | Probability based models for the power draw and energy spectra of a tumbling mill |
| title_short | Probability based models for the power draw and energy spectra of a tumbling mill |
| title_sort | probability based models for the power draw and energy spectra of a tumbling mill |
| topic | Chemical Engineering |
| url | http://hdl.handle.net/11427/5347 |
| work_keys_str_mv | AT bbosalawrencesidney probabilitybasedmodelsforthepowerdrawandenergyspectraofatumblingmill |