# Segregation Modeling in Stockpile Using Discrete Element Method
###### Abstract  
During stockpile feeding, the small particles migrate to the center of the stock while large particles end up around the edges. This phenomenon influences how the mineral is fragmented in the subsequent stages of size reduction. In this study, the primary variables involved in this phenomenon were studied using the discrete element to simulate particle segregation. Results show that the ratio between coarse and fine particles strongly affects particle segregation. The segregation phenomenon was not observed when there were fewer coarse particles in the mix. The feeding height was also found to influence segregation and to affect the angles of repose and dumping. Finally, the rounded polyhedral shape of particles generated the simulation performance most similar to actual particle segregation based on a case study analyzed.  
discrete element method; granular material; gravity flow; mining; stockpile +
Footnote †: journal: Applied Sciences  
model and a mathematical model based on cellular automata; both were used to investigate size segregation during stacking and gravitational reclaim of stockpiles. Stratification patterns were observed during stockpile formation both in the physical model and in the cellular automaton-based model. Furthermore, the cellular automaton-based model successfully simulated segregation phenomena during gravitational discharging and the topological features of segregation during stockpiling and reclaim. [PERSON] et al. [7] proposed a 3D cellular automaton (CA) model of ore pile formation incorporating size segregation due to surface stratification. The model was found to adequately describe the segregation behavior at a range of model scales, where coarse particles were rolled to the outside of the pile and fine particles were concentrated at the center of the pile. Moreover, the model is fast enough to be used in real-time applications such as dynamic process control and digital twins.  
On the other hand, the discrete element method (DEM) has been employed due to its ability to model the physical behavior of particles with great precision and to control a large number of variables, including complex particles' shape [8] and interparticle friction [9]. [PERSON] et al. [10] developed an experimental model with a simulation using the DEM. Using symmetric models, they validated the discrete element method as a viable option for studying the process of stockpile formation. [PERSON] et al. [1] proposed a 3D-DEM model to study stockpile segregation. This model used two characteristic particle sizes of spheres to separate between fine and coarse particles, where the main variations were in the percentage of the mixture of fine and coarse particles with an experiment of discharge height. This research determined that particles with a higher percentage of coarseness had a higher segregation index. [PERSON] et al. [11] proposed a 2D and 3D stockpile DEM simulation with spherical particles in the contact dynamics approach framework to simulate particle segregation by varying the mixing ratio between fine and coarse particles. The preliminary results of this study established that a greater separation between particles is observed when there is a higher percentage of coarse particles.  
Few studies have analyzed the influences of relevant variables (e.g., particle shape, feeding height, and particle sizes) in stockpile during feeding and discharge; these variables can be correctly simulated using the DEM. The DEM has been used successfully to replicate segregation in stockpiles [1; 12]. In this work, stockpile segregation was studied through the discrete element method using the software Rocky DEM. Here, a sensibility analysis was performed by changing not only discharge heights, material mixture, and sizes, but also particle shapes to study the influence of all these variables on the segregation process during feeding and discharge.