Locations where underground mining occur normally experience downward settlement of the ground surface. This phenomenon described above is known as Subsidence. It is of note that this phenomenon is not common only to underground mining operations. Underground mining operations cause stress redistribution as a consequence, this causes some induced displacements on the ground surface. One of the consequences of this is cave-in which could lead to loss of life, materials and man hour. For rock mechanics engineers it is important to be able to determine the level of downward movement that will occur in a place where mining is taking place or will take place. It is also important to determine the magnitude of the downward movement. These are crucial because they are important inputs when planning underground mining operations.
Several methods for predicting this has been performed by various researchers. The various methods developed by researchers were empirical methods, analytical methods, numerical methods or hybrid methods. Empirical methods are based on the back analysis of ﬁeld data and can be used only where a large database of measured ﬁeld data is available. Analytical methods are based on applying mathematical solutions derived from ﬁrst principles to predict how the rock mass will behave when an excavation is made within it. Numerical methods can be used to model elastoplastic, non-linear, and post-yield behavior of rock mass and include the eﬀects of in-situ stresses and geological features on the mining-induced surface subsidence. The current approach is to use the hybrid methods, which is the combination of the analytical or numerical methods with back analysis of field data.
Dr. Mohammadali Sepehri, Professor Derek Apel and Professor Robert Hall at the University of Alberta used Diavik Diamond Mine as a test site to predict the downward settlement of the ground surface. They developed a fully three-dimensional elastoplastic finite element model. Then the initial results of the model were calibrated using two underground calibration points. Lastly the calibrated model was used to predict the induced settlement profile for the surface located in the pit at Diavik Mine. The Results of the developed finite element model were verified by comparing the outputs of the constructed finite element model with available pit monitoring data.
In comparing the actual ground monitoring data and the finite element model results, they found out that the average relative error between the measure data and finite element model predictions is low (only 8%). Therefore the University of Alberta researchers were successfully able to show that the numerical predictions of the mining-induced surface subsidence, due to the BHS mining method, matched well with the Gaussian distribution. Further research is underway to confirm the generalizability of their findings.
Figure legend: The FE model prediction of the surface subsidence matches well with the Gaussian distribution. This concept was first proposed by Peck (1969) for calculating the surface subsidence profile due to tunneling in soft ground.
Mohammadali Sepehri, Derek B. Apel, Robert A. Hall. Prediction of mining-induced surface subsidence and ground movements at a Canadian diamond mine using an elastoplastic finite element model. International Journal of Rock Mechanics and Mining Sciences Volume 100, December 2017, Pages 72-83
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