Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
A mathematical model for predicting classification performance in wet fine screens
Screening is a well-known classification process in the minerals processing industry. The process involves separation of fine particles from coarse particles based on size and is applicable to both dry and fine screening. Fine screening is normally carried out wet. Until recently, fine wet screening...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Chemical Engineering
2016
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613237390868480 |
|---|---|
| access_status_str | Open Access |
| author | Mwale, Adolph Ntaja |
| author2 | Mainza, Aubrey Njema |
| author_browse | Mainza, Aubrey Njema Mwale, Adolph Ntaja |
| author_facet | Mainza, Aubrey Njema Mwale, Adolph Ntaja |
| author_sort | Mwale, Adolph Ntaja |
| collection | Thesis |
| description | Screening is a well-known classification process in the minerals processing industry. The process involves separation of fine particles from coarse particles based on size and is applicable to both dry and fine screening. Fine screening is normally carried out wet. Until recently, fine wet screening had been limited to relatively low throughput applications. Developments in the recent past have seen the evolution of fine screening to high capacity applications. It has found application in operations such as closed circuits with a mill in place of hydrocyclones. However, even though developments are increasing, there has been a process model developmental lag. A fine wet screen model that can be used for unit simulation purposes to predict screen performance outcomes or integration into other models to simulate and predict process performance is necessary. Most existing screen models are for dry and coarse screening applications. This thesis is aimed at developing a fine wet screen process model for predicting wet screening performance in the 45 - 150 μm range. Pilot plant testwork was conducted using a UG2-Chrome ore blend as feed. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/20122 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:57.328Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| 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:11427/20122 A mathematical model for predicting classification performance in wet fine screens Mwale, Adolph Ntaja Mainza, Aubrey Njema Kallon, Daramy Bepswa, Aaron Paul Chemical Engineering Screening is a well-known classification process in the minerals processing industry. The process involves separation of fine particles from coarse particles based on size and is applicable to both dry and fine screening. Fine screening is normally carried out wet. Until recently, fine wet screening had been limited to relatively low throughput applications. Developments in the recent past have seen the evolution of fine screening to high capacity applications. It has found application in operations such as closed circuits with a mill in place of hydrocyclones. However, even though developments are increasing, there has been a process model developmental lag. A fine wet screen model that can be used for unit simulation purposes to predict screen performance outcomes or integration into other models to simulate and predict process performance is necessary. Most existing screen models are for dry and coarse screening applications. This thesis is aimed at developing a fine wet screen process model for predicting wet screening performance in the 45 - 150 μm range. Pilot plant testwork was conducted using a UG2-Chrome ore blend as feed. 2016-06-24T06:32:00Z 2016-06-24T06:32:00Z 2015 Master Thesis Masters MSc (Eng) http://hdl.handle.net/11427/20122 eng application/pdf Department of Chemical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Chemical Engineering Mwale, Adolph Ntaja A mathematical model for predicting classification performance in wet fine screens |
| thesis_degree_str | Master's |
| title | A mathematical model for predicting classification performance in wet fine screens |
| title_full | A mathematical model for predicting classification performance in wet fine screens |
| title_fullStr | A mathematical model for predicting classification performance in wet fine screens |
| title_full_unstemmed | A mathematical model for predicting classification performance in wet fine screens |
| title_short | A mathematical model for predicting classification performance in wet fine screens |
| title_sort | mathematical model for predicting classification performance in wet fine screens |
| topic | Chemical Engineering |
| url | http://hdl.handle.net/11427/20122 |
| work_keys_str_mv | AT mwaleadolphntaja amathematicalmodelforpredictingclassificationperformanceinwetfinescreens AT mwaleadolphntaja mathematicalmodelforpredictingclassificationperformanceinwetfinescreens |