Development of a DFN-based probabilistic block theory approach for bench face angle design in open pit mining

In open pit mining, uncontrolled block instabilities have serious social, economic and regulatory consequences, such as casualties, disruption of operation and increased regulation difficulties. For this reason, bench face angle, as one of the controlling parameters associated with block instabilities, should be carefully designed for sustainable mining. This study introduces a discrete fracture network (DFN)-based probabilistic block theory approach for the fast design of the bench face angle. A major advantage is the explicit incorporation of discontinuity size and spatial distribution in the procedure of key blocks testing. The proposed approach was applied to a granite mine in China. First, DFN models were generated from a multi-step modeling procedure to simulate the complex structural characteristics of pit slopes. Then, a modified key blocks searching method was applied to the slope faces modeled, and a cumulative probability of failure was obtained for each sector. Finally, a bench face angle was determined commensurate with an acceptable risk level of stability. The simulation results have shown that the number of hazardous traces exposed on the slope face can be significantly reduced when the suggested bench face angle is adopted, indicating an extremely low risk of uncontrolled block instabilities.