Optimizing roof control using probabilistic techniques in roof failure prediction

A major objective in the design stage of an underground mine is the reliable prediction of roof falls' size, frequency and location. Probabilistic simulation of potential roof control problems allows a designer to test the performance of competing mine layouts against assumed roof conditions. By comparing different roof control plans using the simulation, the option that provides the lowest overall cost can be selected. The program ROCSIM (Roof control Optimization Cost Simulation) was developed to provide a theoretical solution to this problem. The occurrence and frequency of roof falls are related to the type of roof support, support density, geology, structural discontinuities, location in the mine, and elapsed time between mining and the roof fall. Using a Roof Rating System (RRS) developed for this research, a numerical rating can be given to each area of roof. Using this rating, specific parameters can be assigned to these probability distributions to simulate the occurrence of roof falls within a given geologic setting. Once the location of a roof fall is determined, a cost is calculated taking into account the production delay that would result and the direct cost of cleaning up the fall and resupporting the roof. Assigning a cost to a roof fall allows the comparison of competing roof support designs relative to their overall cost. The final decision on the amount of support and room width must be determined based on legal restraints and minimization of mining costs.