A Novel Approach to Evaluating Gravity Pre-concentration Amenability Utilising the Hydrodynamics of Dense Liquids in Inclined Channels

Lowes, Zhou, McGrath, Eksteen, Galvin

Presented at the Preconcentration Digital Conference November 2020

ABSTRACT

Pre-concentration of low grade ores can improve the economic and environmental sustainability of an operation significantly, with opportunities for implementation ranging from run-of-mine to mill discharge depending on ore specific characteristics. For a gravity separation, where the performance is fundamentally constrained by mineral liberation, these feeds often represent a very difficult separation given the dominance of the relatively coarse gangue and fine liberation sizes. Thus, building knowledge of the feed through characterisation of the density distribution is critical to assessing amenability before progressing towards lab/pilot-scale test work and full-scale operation.

The traditional approach to determining the density distribution typically involved sink/float testing, however, recent developments in hydrodynamic fractionation using inclined channels now offers a more cost-effective alternative with minimal health and environmental risk. A non-hazardous dense liquid, namely an aqueous solution of lithium heteropolytungstates (LST), is supplied as fluidisation to a REFLUXTM Classifier, consisting of a vertical section below a system of inclined channels, operating in semi-batch configuration. Fractionation is achieved by increasing the flow rate incrementally and collecting the particles to form a series of flow fractions.

The purpose of this paper is to present this new method in the form of a case study, aimed at assessing the amenability of a low grade gold-bearing sulfide ore to pre-concentration. The robustness in the method is demonstrated through comparison with sink/float data, examining the density distribution and the liberation-limited product grade and recovery achievable. These data are then used as a benchmark to assess water-based continuous gravity separations conducted on the feed using a laboratory-scale REFLUXTM Classifier. This data set is used as the basis for process modelling and empirical validation for the recently established partition surface of the separator.

AUTHORS

C.P. Lowes1, J. Zhou2, T.D. McGrath3, J.J. Eksteen4, and K.P. Galvin5

1. PhD Candidate, Centre for Advanced Particle Processing and Transport, University of Newcastle, Callaghan NSW 2308. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

2. Senior Research Associate, Centre for Advanced Particle Processing and Transport, University of Newcastle, Callaghan NSW 2308. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

3. Senior Research Fellow, Gold Technology Group, Curtin University, Bentley WA 6102. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

4. Chair, Extractive Metallurgy, Gold Technology Group, Curtin University, Bentley WA 6102. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

5. Director, Centre for Advanced Particle Processing and Transport, University of Newcastle, Callaghan NSW 2308. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

ACKNOWLEDGEMENTS

The authors wish to thank Curtin University Gold Technology Group and the sponsors of the AMIRAP420F Gold Processing Technology project (AngloGold Ashanti, Australian Gold Reagents, Barrick Gold, CRC ORE, Evolution, FLSmidth, Gekko Systems, Gold Fields, Kemix, Lhoist, Newcrest Mining, Newmont Corporation, Northern Star Resources, Orica, Pioneera, and Vega Industries) for their financial and technical support.

Additionally, we gratefully acknowledge the support of CRC ORE in this research collaboration. CRC ORE is part of the Australian Government’s CRC Program, which is made possible through the investment and ongoing support of the Australian Government. The CRC Program supports industry-led collaborations between industry, researchers and the community.

The University of Newcastle holds international patents on the REFLUXTM Classifier and has a Research and Development Agreement with FLSmidth Pty Ltd. The inventor of the REFLUXTM Classifier, and the last author of this paper, K.P. Galvin, is a beneficiary of the University’s intellectual property policy.

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