Byrne, C, Rogers, S, Stevenson, M, Pothitos, F & Tennant, D 2025, 'Bench design optimisation in a sparsely structured rock mass', in JJ Potter & J Wesseloo (eds), SSIM 2025: Fourth International Slope Stability in Mining Conference, Australian Centre for Geomechanics, Perth, https://doi.org/10.36487/ACG_repo/2535_06
(https://papers.acg.uwa.edu.au/p/2535_06_Byrne/)
Abstract: The quality of bench faces in the North Wall of Red Chris Mine has greatly improved since their blasting method was amended to include pre-splitting. This improvement in bench stability performance offered an opportunity to optimise bench design. Analysis of the south facing benches shows that stability is in part controlled by a sparse network of longer structures, comprising of both joints and faults. Conventional benchscale kinematics is not suited to considering sparse networks such as this, where in reality the probability of occurrence (POBO) of problematic wedges is typically low, while conventional combinatorially modelled wedges (e.g. SWedge) result in a POBO that is unrealistically high. This results in unnecessarily conservative design recommendations. 
In contrast, the generation of a discrete fracture network (DFN) model provides a more realistic definition of the structural model based upon stochastic inputs from identified structural sets. Estimates of structure size and intensity were made from local bench mapping and photogrammetry. DFN model analysis, with its realistic structural description, allows the more reliable identification of potential wedges, the classification of unstable wedges, and the estimation of back-break. The combination of POBO and probability of sliding (POS) for modelled wedges, resulted in an overall probability of failure (POF) well within the design acceptance criteria (DAC) and simulated back-break values that were consistent with field observations. Under the right conditions, DFN wedge analysis can justify steeper bench face angles (BFAs) when compared to conventional kinematic analysis.

Keywords: discrete fracture network, optimisation, stability, structural