The discrete element method (DEM) has been widely employed to model processes in different industries, such as mining, agriculture, pharmaceuticals, and food. One of the main lines of research, and in which different authors propose several approaches, is the calibration of parameters. Bulk calibration (BCA) is a common approach used that does not necessarily represent the individual behavior of each particle. On the other hand, direct measurement (DMA) is another approach employed in some cases. This work presents a comparison between calibration of DEM model parameters with non-cohesive spherical and polyhedral particles using a combination of direct measurement and bulk calibration. BCA is employed to calibrate friction parameters and DMA to characterize shape of the particles and coefficient of restitution of the contact between particles. Experimental data from Draw Down Tests are used to calibrate the friction parameters. Numerical optimization of the parameters is conducted by altering the coefficients of friction regarding the objective variables of mass flow, final mass, shear angle, and angle of repose. Quartz, granite, and coal are calibrated, obtaining good agreement with the experimental results. The influence of particle shape is tested, proving that more complex particles obtain better results for the analyzed case.

Comminution by gyratory crusher is the first stage in the size reduction operation in mineral processing. In the copper industry, these machines are widely utilized, and their reliability has become a relevant aspect. To optimize the design and to improve the availability of gyratory crushers, it is necessary to calculate their power and torque accurately. The discrete element method (DEM) has been commonly used in several mining applications and is a powerful tool to predict the necessary power required in the operation of mining machines. In this paper, a DEM model was applied to a copper mining gyratory crusher to perform a comprehensive analysis of the loads in the mantle, the crushing torque, and crushing power. A novel polar representation of the radial forces is proposed that may help designers, engineers, and operators to recognize the distribution of force loads on the mantle in an easier and intuitive way. Simulations with different operational conditions are presented and validated through a comparison with nominal data. A calculation procedure for the crushing power of crushers is presented, and recommendations for the selection of the minimum resolved particle size are given.

Gyratory crushers are fundamental machines in aggregate production and mineral processing. Discrete Element Method (DEM) simulations offer detailed insights into the performance of these machines and serve as a powerful tool for their design and analysis. However, these simulations are computationally intensive due to the large number of particles involved and the need to account for particle breakage. This study aims to investigate the effect of particle shape and size distribution on the performance of a DEM model of a gyratory crusher. The selected study case corresponds to a primary gyratory crusher operating in a copper processing industry. As particle shapes, spheres and polyhedrons are used with a particle replacement scheme. This study utilizes two different size distributions, with variations also applied to the minimum particle size. The results are analyzed in terms of the impact of these factors on the power draw, mass flow, and product size distribution for each of the combinations explained. The findings demonstrate that particle shape primarily influences the product size distribution, whereas variations in particle size distribution have a pronounced effect on power draw, mass flow rate, and product size distribution. Based on the results, recommendations are provided regarding the selection of the minimum particle size. It is concluded that the minimum particle size should not exceed a third of the closed-side setting to ensure accurate and reliable simulation outcomes.

Wet agglomeration is essential in heap leaching of minerals, as it improves permeability by forming agglomerates through capillary and viscous forces. The Discrete Element Method (DEM) has been used to model this phenomenon, enabling the detailed tracking of interactions between individual particles. This study employs DEM to analyze the effect of particle-size distribution (PSD) on agglomerate formation inside a rotating agglomeration drum. The DEM model was validated using geometry and parameters reported in the literature, which are based on experimental studies of agglomeration in rotating drums. Both wide and bimodal PSD cases were simulated. The results demonstrate that DEM simulations of drums with exclusively fine particles are prone to producing poorly defined macrostructures. In contrast, the presence of coarse particles promotes the formation of stable agglomerates with fine particles attached to them. Additionally, decreasing the maximum particle size increases the number of agglomerates and improves the homogeneity of the final PSD. These findings improve our understanding of wet agglomeration dynamics and provide practical criteria for optimizing feed design in mineral-processing applications.

The initiation of the caving process in block/panel caving is critical to the success of mines. However, there is no widely adopted methodology for modeling the onset of caving. This study proposes a methodology to model the initial stages of caving using the Discrete Element Method, in which the rock mass is represented using the Bonded Particle Model, and the undercut material is modeled with non-cohesive discrete particles. The collapse of the rock mass was replicated following a parameter calibration process, and the results were compared with actual mining data of the observed initial fragmentation. Key parameters were identified, such as allowable normal and shear stresses, which are essential to accurately represent the collapse of the rock mass and the evolution of the early stage of rock fragmentation. Low allowable stress values led to premature collapse and finer fragmentation, whereas higher values delayed cave back failure and resulted in coarser initial fragmentation. The results showed the formation of large rock fragments between 14 and 15 m during the initial cave back failures. Subsequently, larger fragments ranging from 2 to 9 m were observed detaching from the cave back as draw progressed, with sizes comparable to those reported in some block/panel caving operations. The main contribution of this work is a methodology that demonstrates the feasibility of modeling caving initiation, which is crucial in a context where increasing rock mass strength and deposit depth require design changes at the production level and pose significant uncertainty in the rock mass response.