Spirin, V, de Bruyn, I, Mylvaganam, J & Lium, D 2025, 'Considerations for optimal assessment of bench–berm stability and design in 
competent, fractured rock masses', 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_07
(https://papers.acg.uwa.edu.au/p/2535_07_Spirin/)
Abstract: In competent rock masses, a focus on bench stability during slope design is crucial, as the achievable overall slope angle is often constrained by appropriate bench–berm geometry rather than overall rock mass strength. However, optimising bench–berm configurations is a complex process that requires considering multiple discontinuity-related input parameters and identifying the most significant ones that control design in each domain. The wide range of available tools and methods for assessment can lead to varying outcomes, and design decisions often rely on experience and engineering judgement – both in selecting appropriate analysis methods and in interpreting their results. Consequently, identifying key factors and streamlining the design analysis process are essential for improving efficiency and optimising bench–berm configurations.
Stereographic analyses are useful for quick and straightforward assessments. Simple block-based analyses are necessary for optimisation of bench and berm design. In some cases, more advanced techniques may be beneficial; stochastic joint network analysis allows for the analysis of complex, irregularly shaped failure mechanisms. The results of simple block-based and stochastic joint network analyses are typically expressed in terms of Factor of Safety and probability of bench failure, as well as crest loss, failure volume and spill width, which reflect berm retention capacity. These outcomes are highly sensitive to input parameters such as discontinuity orientation, spacing, persistence, and shear strength, making calibration and sensitivity analysis essential.
Using case studies, this paper compares several methods for assessing Probability of Failure and spill width, and highlights their influence on bench face angle and berm width justification. The results demonstrate consistent outcomes when key controlling factors are properly considered; however, when failure mechanisms involve contributions from multiple joint sets, advanced methods are required.

Keywords: bench–berm design, Probability of Failure, berm retention capacity, crest loss, spill width