The question of effective energy utilisation in grinding mills is not new. There are several conflicting arguments about tumbling mills, whether the efficiency is around one per cent or maybe ten per cent, or even much lower. The energy not used is assumed to be lost as heating of the pulp, the grinding mill body, the charge, generation of shockwaves and vibrations, etc. Stirred media mills on the other hand are generally considered to have better energy utilisation, but their energy efficiency is still not that clear. To shed some light on this a pilot-scale, wet stirred media mill was investigated over a range of operating conditions. The wet stirred media mill is a Drais PMH 5 TEX pearl mill fitted with an electric motor at 11 kW. It has been investigated over a range of operating conditions to try to balance the dissemination of the input energy in forms of the net grinding energy, mechanical energy losses, and the heating transferred to the pulp, the mill, the charge, and the cooling water. It is found that approximately 20 – 40 per cent of the input energy accounts for the grinding process. Also, that the difference between gross and net input electrical energy is mainly disseminated as heating of the pulp and cooling water. Mechanical energy losses appear to be much smaller than the heating effects. The use of a dispersant seems to mainly influence the heating effect.

Understanding and optimizing the comminution process in terms of mineral liberation, fragmentation, and fracture energy are aligned with sustainable approaches and overall international goals of green solutions. This study investigates the combined effect of material properties (ore textural features) and process factors (displacement rate) on mineral liberation, fracture energy, and fragmentation. For achieving this aim, multivariate data analysis tools are used to examine the fragmentation by compression of multiple layers of iron oxide minerals in a particle bed. The results indicate that ore textural features distinctively influence particle fragmentation, mineral liberation, and fracture energy and the ore textural effects are more pronounced compared to displacement rate.

Comminution is the process for the liberation and size reduction of ores prior to separationprocesses. Generally, in mineral processing, grinding is done using rod, ball, autogenous, or semiautogenous mills. The fully autogenous grinding (AG) is the most cost- and process-efficient grinding by benefiting from eliminating steel grinding media. It is also a superior choice for downstream processes such as flotation of some sulphide minerals that are sensitive to the reducing conditions caused by iron chipped away from the steel media.

One of the main factors affecting the suitability of an ore for autogenous grinding is the ore competency, i.e., provide enough critical stones for the grinding process. Several experimental test routines exist and are used for assessing the viability of the ore for autogenous grinding. However, very little attention is given to the generation of fatigue in large stones experiencing repeated shocks in the mill. To investigate this, large pebbles sampled from industrial autogenous grinding mills for hard and soft ores which were categorized based on the grinding energy.

From the pebbles, small drill core samples were prepared and went through a series of fatigue cycle tests. Both hard and soft ores showed similar average resistance to failure in compression tests, but the hard ore had a consistent resistance with lower variations. The cores were scanned before and in-between fatigue tests at the highest reachable resolution, 1.5 µm voxel size. The outcome showed that higher number of micro-cracks were visible in the soft ore compared to the hard ore. The frequency of micro-crack development in the soft ore may be the reason for its lower specific grinding energy compared to the hard ore.

It is obvious that for realistic conditions in an autogenous grinding mill, stones are pre-weakened by fatigue before they fracture. Therefore, shortcut methods focusing only on running tests on fresh and small samples may operate in unrealistic conditions by ignoring the fatigue phenomenon. This is even more important for ores that are in between the soft and hard ore boundary or on the borderline to be considered as a competent ore for autogenous milling.

Wet comminution is an important process in the mineral processing industry. Modelling of wet comminution in stirred media mills requires the simultaneous modelling of grinding media, a moving internal stirrer, and slurry. In the present study, a novel approach for modelling the physical interactions between slurry, grinding media and mill structure in a stirred media mill is presented. The slurry is modelled with the particle finite element method (PFEM). The grinding media is modelled using the discrete element method (DEM) and the mill structure is modelled using the finite element method (FEM). The interactions between slurry, grinding media and mill structure are modelled by two-way couplings between the PFEM, the DEM and the FEM models. The coupled model of the present study is used to predict the motion of slurry and grinding media, and to calculate the power draw during wet comminution in a pilot scale horizontal stirred media mill. Furthermore, the model is used to compare a Newtonian and a non-Newtonian model of the slurry, where the non-Newtonian model is used to capture experimentally observed shear-thinning. The coupled PFEM-DEM-FEM model preserves the robustness and efficiency of each of the methods and it gives the possibility to use large time increments for the fluid, greatly reducing the computational expense. The coupled model of the present work provide information on the complex dynamics of slurry and grinding media. The numerical model is shown to be a useful tool for increasing the knowledge and understanding of wet comminution in stirred media mills.

As part of a geometallurgical program for the Leveänimei iron ore mine, the Davis tube was used as proxy to classify ore types, predict iron recoveries in wet low-intensity magnetic separation (WLIMS), and to estimate liberation of mixed particles. The study was conducted by testing 13 iron ore samples with a Davis tube and a laboratory WLIMS. Ore feed was studied for modal mineralogy and liberation distribution with Automated Scanning Electron Microscopy. Data analyses to detect the patterns and data dependencies were done with multivariate statistics: principal component analysis, and projection to latent structures regression. Results show that a simple index (X_LTU) based on mass pull (yield) in the Davis tube is capable of easy classification of magnetite ores. Using Davis tube mass pull and iron recovery, together with iron and Satmagan head grades may predict iron recovery in WLIMS. Also, the variability in Fe-oxides liberation pattern for magnetite semi-massive ores can be explained with the chemical composition of the Davis tube concentrate. It is concluded that the Davis tube test is better used only for marginal ores, since iron oxide minerals tend to be fully liberated in high-grade magnetite massive ores after grinding. The developed models may be used in populating a production block model.

A probalistic screen with electrically heated decks has been used to produce narrow size fractions of magnetite and olivine below 1 mm. The results indicate that the major limiting production factor is the amount of too fine materials in the desired size fraction. This can be corrected by re-screening the narrow size fraction in various ways, but the best result is had with an air classifier.

The best way to evaluate the screening results is to plot the proportion of finished product, and the loss of the correct fraction as a function of feed rate and moisture content. These being quantity results, they need to be supplemented with quality parameters, and the best seem to be the weight percentage of too coarse (plus material) and too fine (minus material) particles in the finished product. There appears to be some threshold level for the heating effect, but to what extent this is related to the screen deck type, the heat capacity, and density of the material, or the particle size, is still unclear.

Modelling of wet grinding in tumbling mills is an interesting challenge. A key factor is that the pulp fluid and its simultaneous interactions with both the charge and the mill structure have to be handled in a computationally efficient way. In this work, the pulp fluid is modelled with a Lagrange based method based on the particle finite element method (PFEM) that gives the opportunity to model free surface flow. This method gives robustness and stability to the fluid model and is efficient as it gives possibility to use larger time steps. The PFEM solver can be coupled to other solvers as in this case both the finite element method (FEM) solver for the mill structure and the DEM solver for the ball charge. The combined PFEM-DEM-FEM model presented here can predict charge motion and responses from the mill structure, as well as the pulp liquid flow and pressure. All cases presented here are numerically modelled and validated against experimentally measured driving torque signatures from an instrumented small-scale batch ball mill equipped with a torque meter and charge movements captured from high-speed video. Numerical results are in good agreement with experimental torque measurements and the PFEM solver also improves on efficiency and robustness for solving charge movements in wet tumbling mill systems.

Wet fine grinding is an important process in the minerals industry. Modelling of wet grinding in stirred media mills is challenging since it requires the simultaneous modelling of grinding media consisting of a huge number of small grinding bodies, moving internal stirrer, and the pulp fluid. All of them in interaction with each other. In the present study, wet grinding in a stirred media mill is studied using coupled incompressible computational fluid dynamics (ICFD) and discrete element method (DEM) and finite element method (FEM) simulations. The DEM is used to model the grinding media, and the pulp fluid flow is modelled using the ICFD. Moreover, the FEM is used to model the structure of the mill body and is in combination with DEM used to estimate the wear rate in the system. The present implementation of the coupled ICFD-DEM-FEM preserves the robustness and efficiency of both methods, and it gives the possibility to use large time steps for the fluid with very low computation times.