Tyler, A, Goulet, A, Heinsen Egan, M, Wesseloo, J, Potvin, Y & Chester, C 2026, 'Probabilistic versus deterministic wedge formation methods', in D Cumming-Potvin & J Wesseloo (eds), Ground Support 2026: Proceedings of the 11th International Conference on Ground Support in Mining, Australian Centre for Geomechanics, Perth, pp. 1-11, https://doi.org/10.36487/ACG_repo/2625_26
(https://papers.acg.uwa.edu.au/p/2625_26_Tyler/)
Abstract: The stability assessment of rock blocks/wedges in the underground environment is a critical design process in the prevention of uncontrolled failures. Traditionally a deterministic ‘worst-case scenario’ wedge analysis method is adopted which results in overly conservative ground support designs. 
Advances in data collection, computational hardware and software design tools allow probabilistic analytical methods, which capture the natural variability of the structural environment, to be routinely used in ground support design workflows that are undertaken on site. This shift allows for the potential to optimise ground support designs, with improved safety, cost and efficiency outcomes.
To highlight the benefits of a probabilistic approach, this paper presents a comparative study of the 2 methodologies, utilising a commercially available wedge analysis tool and the mXrap Discrete Fracture Network (DFN) generator and DFN Block Analyser. Using the same input parameters, the study compared wedge size, weight and orientation and Factor of Safety (FoS). Additionally, the study evaluated the difference in ground support requirements between the methods required to achieve a predetermined FoS. 
The work highlights the advantages of probabilistic approaches in producing designs that balance safety and economy, while reducing the reliance on ‘worst-case’ assumptions. This comparison addresses a critical gap in the practical adoption of probabilistic methods in underground kinematic wedge analysis, offering a pathway to more reliable and economically sustainable ground support strategies.

Keywords: kinematics, probabilities, case study