DEM-PBM approach to predicting particle size distribution in tumbling mills

Abstract

Tumbling mills using balls as grinding media are used extensively in the mining and cement industries to produce fine powders; however, it is well known that the process of size reduction is highly energy-intensive. For this reason, much of today’s comminution research is aimed at understanding grinding mechanisms, by estimating power draft and modeling milling circuits using the discrete element method (DEM). DEM predicts individual particle trajectories, the distribution of energy and contact forces at each collision, lifter wear and power draw. This paper presents a prediction of the discharge particle size distribution using three components, mass balance model (sometimes referred to as a population balance model, PBM), impact energy distribution of the mill obtained from the simulation of the charge motion using DEM and breakage characteristics of particles determined from drop-ball tests DEM simulation of the charge of a tumbling mill was done using the code MinProSim 1.0 to obtain impact spectra at different operative conditions. Then, thepopidation balance model (PBM), based on impact energy distribution, was used to predict the final particle size distribution in a batch mill and compared with experimental data. It is demonstrated that the DEM-PBM approach allows a reliable solution to predict particle size distribution for tumbling mills. Ideally, the model has to predict size distribution for any operational condition and feed characteristic; however, it has been shown that predictions include some degree of error.