A model is created by writing a Python code that defines the possible states, 5 the transitions, and the rates of those transitions. Adjacent pairs of nodes may undergo transitions to different states, according to a user-defined average transition rate. ![]() ![]() The model domain consists of a set of grid nodes, with each node assigned an integer state-code that represents its condition or composition. Furthermore, the cellular automaton-based model has successfully simulated segregation phenomena during gravitational discharging, as well as the topological features of segregation during stockpiling and reclaim.ĬellLab-CTS 2015 is a Python-language software library for creating two-dimensional, continuous-time stochastic (CTS) cellular automaton models. Also, experiments in both physical and cellular automaton-based model were carried out to quantify the particle size time evolution of granular material leaving the discharge opening during reclaim. These stratification patterns have been observed during stockpile formation both in the physical model and in the cellular automaton-based model. Banded layers of fine, medium-sized, and coarse particles appear during the pile growth. The present model has taken into account only three particle size class. This mathematical model is based on cellular automata and was used to simulate size segregation in conical stockpiles of non-cohesive granular material and gravity flow during its reclaim, through a ground level discharge opening. ![]() A small-scale, quasi-two-dimensional physical model was used to investigate size segregation during stacking and gravitational reclaim of stockpiles and to compare experimental results to those ones generated by a simplified mathematical model. Stockpiling is a key issue in bulk material handling.
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