Modelling the effect of changes in mining compressed air networks on refuge chambers

Abstract

Health and safety are major talking points in the South African mining sector. Various systems are in place to ensure the safety of all mining personnel underground. One such safety device is refuge chambers. Refuge chambers are underground havens where personnel can go to escape toxic gases and smoke build-up. Refuge chambers make use of compressed air to supply safe, breathable air to the occupants of the chamber. Several studies have been done on the minimum compressed air requirements of a refuge chamber. However, there has not been adequate research done on supplying this compressed air in large and complex mining networks or what effect any changes to the network will have on the supply. With that said, studies have shown that process simulations can accurately predict what the effects of changes to a compressed air network will have on the energy consumption of the mine. Therefore, it stands to reason that process simulations could be used to predict what effect changes to a compressed air network will have on the supply of compressed air to all refuge chambers on the network. This study aimed to develop a simulation-based methodology to investigate the effects of various compressed air network configurations on the supply to the refuge chambers and then to verify the results with data acquired from a mining case study. The methodology followed to accomplish this was to gather the necessary information required to build the baseline simulation, which was then calibrated using actual data from the mine in the case study. This baseline simulation was then used to simulate and analyse various proposed changes to the network to ascertain whether the minimum supply to all refuge chambers would be met if the new configuration would be implemented. Once a suitable configuration was found it was then implemented on the mining network and the accuracy of the simulation was validated. During the case study, two possible changes to the compressed air network were identified and both changes were implemented and analysed independently. After implementation, the actual results were compared with the simulation results and Configuration 1 had a mean absolute error of 4.65% and a mean square error of 0.94 kg2/s2 and Configuration 2 had a mean absolute error of 0.78% and a mean square error of 0.40 kg2/s2. The simulation did, however, tend to underestimate the flow of compressed air to the refuge chambers, but this was not detrimental to the results as the simulation was used to ensure that the flow to the refuge chamber was above a minimum requirement and as a result this added an additional safety factor to the results. These results proved that the methodology developed, could be used to estimate what the effects on the compressed air supply to refuge bays will be, if changes to the compressed air network are introduced. This methodology can thus be used as an aiding tool in decision making and give one enough confidence to implement changes. It is also a valuable tool to test various scenarios without the need to physically perform them which is not only beneficial from a safety point of view, but also from a financial one.