- Title
- Characterisation and modelling of gravity pre-concentration amenability using LST fluidisation in a REFLUXTM classifier
- Creator
- Lowes, Callan; Zhou, James; McGrath, Teresa; Eksteen, Jacques; Galvin, Kevin
- Relation
- Minerals Vol. 10, Issue 6, no. 545
- Publisher Link
- http://dx.doi.org/10.3390/min10060545
- Publisher
- MDPI AG
- Resource Type
- journal article
- Date
- 2020
- Description
- Samples of the feed, underflow and overflow from water-based separations conducted using a continuous REFLUXTM Classifier involving inclined channels with a 3 mm spacing have been fractionated. Another REFLUXTM Classifier operating in a semi-batch configuration using a dense fluidising medium of lithium heteropolytungstates (LST) was used to determine the density distributions of the three streams. The partition surface of the separator was quantified, and the technique was validated against sink/float data for a −300 + 38 µm chromite ore separation. It was found that the LST flow fractionation determined the D50 with remarkable accuracy across the entire size range, with the Ep values also very good above 75 µm. For water-based continuous separations involving a gold ore covering the size range −1.0 + 0.090 mm, the D50 varied with particle size to the power −0.22 and the Ep remained relatively constant at approximately 170 kg/m3 for each of the narrow particle size ranges. These results were consistent with the partition surface validated based on the much finer size range of the higher density chromite ore. The performance of the continuous system was then modelled, with the results shown to agree well with separations conducted on the feed. This approach has been developed as an alternative to using the sink/float test, thus offering a new option with both a lower cost and minimal health and environmental risk. The findings from this study can in turn be used to assess the amenability of a given ore to gravity pre-concentration.
- Subject
- REFLUXTM classifier; dense minerals; gravity separation; pre-concentration; process modelling; characterisation
- Identifier
- http://hdl.handle.net/1959.13/1425313
- Identifier
- uon:38231
- Identifier
- ISSN:2075-163X
- Rights
- © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
- Language
- eng
- Full Text
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