Behavioural zone identification in rotary mills

Abstract

Semi-autogeneous grinding mills are used widely to reduce the size of mined ores and extract minerals of interest. However, these mills are extremely energy consuming. To reduce the energy wasted by mostly moving and shearing instead of grinding the material, a good understanding of the behaviour of the charge in the mill is crucial. In this paper, we first establish different smooth fields of internal variables such as density, strain rates, and pressure, for a rotary mill simulated using discrete element modelling. As these fields are interrelated, we then use a clustering method to identify well-defined zones of distinct behaviour within the mill. This approach allows us to analyse and summarise the behaviour of complex flows as a set of localised zones with well identified physical properties. These zones resemble the ones which were previously sketched intuitively based on experimental observations for specific parameters, including the rotation rate and filling fraction of the charge. On the other hand, the dependence of those zones on the operating parameters of the mill provides a direct interpretation of the effects of adjusting the available operating conditions in the field. The method can be readily generalised to other geometries and particle technologies, and can therefore provide a convenient approach for both comprehensive and manageable understanding of material behaviour in a wide range of applications.