STUDY OF MECHANICAL BEHAVIOR OF MINING IRON ORE TAILINGS USING DISCRETE ELEMENTS METHOD
Discrete Elements Method; Mining tailings; PFC2D; Numerical modeling; Rolling Resistance Linear Model; Micromechanical Analysis
The present work studied the influence of microscopic parameters on the mechanical behavior of iron ore mining tailings using the discrete element method (DEM). The two-dimensional program Particle Flow Code (PFC2D) from Itasca company was used for the numerical simulations of the laboratory tests that comprised of drained triaxial compression tests on sandy iron ore tailings samples. In the DEM model, drained biaxial compression tests were simulated on numerical samples with a grain size distribution curve proportional to that of the mining tailings and with a relative density between 60-65% for the confining stresses of 100, 200, and 400 kPa, which represent the same conditions adopted in the laboratory tests. In order to represent the effect of the irregularities in the shape of the tailings grains, the Rolling Resistance Linear Contact Model (RRLCM) was used in DEM simulations. The micromechanical properties of the numerical sample, such as the normal and shear rolling stiffness, and the rolling friction coefficient, were selected using a proposed methodology for calibrating the model in order to reproduce the overall mechanical behavior observed in the laboratory tests on mining tailings. The macroscopic mechanical behavior was evaluated in the DEM model based on the contact force network, velocity vectors, rolling resistance, particle rotation and coordination number measured from the interactions between particle-particle and particle-wall. During the simulations of the drained biaxial tests, it was also possible to identify the location and inclination of the shear band. In conclusion, the results obtained from the DEM model using the RRLCM model indicated good agreement between the stress-strain response and the experimental data from the laboratory tests. However, the volumetric deformation curves were not able to fully represent the volumetric deformation of the tailings due to the simplifying assumptions adopted in the model development. In summary, the present work provides a starting basis for further investigations of mining tailings using DEM.