A Texture-Based Model of Mineral Liberation

Author(s) M. Andrusiewicz, C.L. Evans, R. Mariano, R.D. Morrison, and E.M. Wightman
IMPC 2016: XXVIII International Mineral Processing Congress Proceedings


The ability to optimise a concentrator from mill feed to final products requires a process simulator that integrates comminution, classification and separation stages. A key part of any such integrated process simulator is the inclusion of a model of mineral liberation in comminution to predict the particle composition distribution of the comminution products. This need was recognised by Gaudin (1939) who proposed a model of liberation based on the cubic fracture of a mineral texture composed of cubic grains of two minerals.

This paper describes the development of a texture-based model of mineral liberation that builds on the method proposed by Gaudin. The approach described here, termed the JK-Gaudin Random Liberation model (JK-GRLM) uses as its basis the measured, volumetric mineral texture data that can be quantified for a given ore using X-ray micro-tomography. The textural data required as inputs for the JK-GRLM include the mineral grain size distribution. While the Gaudin model (in common with other existing liberation models) is a two-mineral (or two-phase) system, the JK-GRLM extends the approach to multimineral systems of up to 15 individual minerals, making it more widely applicable.

An example of the application of the JK-GRLM to a base metal sulphide ore is provided. In the example the JK-GRLM is used to simulate the breakage of the measured ore texture and the particle composition distributions of the simulated progeny particles are compared to the measured particle composition distributions of ore that has been physically broken.

The ability to calibrate this mineral liberation model with measured ore texture will allow it to be applied in greenfield situations where geometallurgical programs measure texture and in brownfield applications as a key part of integrated process simulations. The development of this model enhances our ability to simulate mineral processing operations as an integrated system.