Development of a flotation model incorporating liberation characteristics
A liberation/flotation model has been developed to evaluate flotation performance, in which the grade distribution of composite particles is incorporated explicitly. The grade distribution of particles at a given size fraction was calculated using a predictive liberation model developed by the autho...
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curtin-20.500.11937-339082017-09-13T15:06:00Z Development of a flotation model incorporating liberation characteristics Zhang, J. Subasinghe, Nimal A liberation/flotation model has been developed to evaluate flotation performance, in which the grade distribution of composite particles is incorporated explicitly. The grade distribution of particles at a given size fraction was calculated using a predictive liberation model developed by the authors. Flotation behaviour of these particles in narrow size fractions were evaluated using batch flotation tests. The recovery of particles in narrow size/grade classes at various flotation times under a given flotation environment were obtained from SEM images of mounted specimens of feed, concentrate and tailings samples using image analysis techniques. By describing the size, grade and recovery data of particles in narrow size/grade classes by separate matrices, a transformation matrix technique has been developed that can predict the flotation performance of a composite sample of an ore comprising various size classes. It has been shown that the predicted results agree well with the observed results. This liberation/flotation model has wide applications in geometallurgical testing and design, where the downstream flotation performance is to be determined with limited availability of ore samples and their liberation characteristics. It also alleviates the deficiencies involved with flotation models that assumes first order behaviour. 2016 Journal Article http://hdl.handle.net/20.500.11937/33908 10.1016/j.mineng.2016.05.021 Elsevier restricted |
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A liberation/flotation model has been developed to evaluate flotation performance, in which the grade distribution of composite particles is incorporated explicitly. The grade distribution of particles at a given size fraction was calculated using a predictive liberation model developed by the authors. Flotation behaviour of these particles in narrow size fractions were evaluated using batch flotation tests. The recovery of particles in narrow size/grade classes at various flotation times under a given flotation environment were obtained from SEM images of mounted specimens of feed, concentrate and tailings samples using image analysis techniques. By describing the size, grade and recovery data of particles in narrow size/grade classes by separate matrices, a transformation matrix technique has been developed that can predict the flotation performance of a composite sample of an ore comprising various size classes. It has been shown that the predicted results agree well with the observed results. This liberation/flotation model has wide applications in geometallurgical testing and design, where the downstream flotation performance is to be determined with limited availability of ore samples and their liberation characteristics. It also alleviates the deficiencies involved with flotation models that assumes first order behaviour. |
format |
Journal Article |
author |
Zhang, J. Subasinghe, Nimal |
spellingShingle |
Zhang, J. Subasinghe, Nimal Development of a flotation model incorporating liberation characteristics |
author_facet |
Zhang, J. Subasinghe, Nimal |
author_sort |
Zhang, J. |
title |
Development of a flotation model incorporating liberation characteristics |
title_short |
Development of a flotation model incorporating liberation characteristics |
title_full |
Development of a flotation model incorporating liberation characteristics |
title_fullStr |
Development of a flotation model incorporating liberation characteristics |
title_full_unstemmed |
Development of a flotation model incorporating liberation characteristics |
title_sort |
development of a flotation model incorporating liberation characteristics |
publisher |
Elsevier |
publishDate |
2016 |
url |
http://hdl.handle.net/20.500.11937/33908 |
first_indexed |
2018-09-06T22:06:48Z |
last_indexed |
2018-09-06T22:06:48Z |
_version_ |
1610897538656763904 |