Adopting Reliability-Based Design Acceptance Criteria in Probabilistic Open Pit Slope Analysis: A Parametric Study

Design of open pit slopes is a decision-making process which aims to maximize ore recovery while minimizing the stripping ratio. Slope design will typically meet a Design Acceptance Criteria (DAC), and the current practice of designing open pit slopes adopts the industry-wide accepted Guidelines of...

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Bibliographic Details
Published in:Geotechnical and geological engineering Vol. 42; no. 5; pp. 3635 - 3669
Main Authors: Velarde, Gustavo, Macciotta, Renato
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 01-07-2024
Springer Nature B.V
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Summary:Design of open pit slopes is a decision-making process which aims to maximize ore recovery while minimizing the stripping ratio. Slope design will typically meet a Design Acceptance Criteria (DAC), and the current practice of designing open pit slopes adopts the industry-wide accepted Guidelines of Open Pit Slope Design published in 2009. However, designing open pit slopes is a complex process that involves inherent risks and geotechnical uncertainties. Consequently, reliability analyses have become a valuable tool in managing uncertainties. This paper presents a parametric study that considers uncertainties related to the rock mass strength properties and the slope geometric configurations, evaluated at three different design reliability levels. This parametric study adopts a reliability-based DAC (RBDAC) approach presented in 2020. The reliability assessment is carried out using probabilistic analyses adopting the 2D limit equilibrium method along with Monte Carlo simulations. The input variables for the rock mass strength are defined through Probability Density Functions (PDFs) that capture the natural variability while the input variables of geological structures are defined through kinematic assessments. The PDFs of the rock mass strength properties were modelled based on the generalized Hoek-Brown criterion using the mean, coefficient of variation (COV), and correlation coefficient. Probabilistic analysis results show that most of the resultant pairs of Factor of Safety (FoS) and Probability of Failure, and associated COV of the resulting FoS (COV FoS ) are consistent with the RBDAC approach. This approach has significant implications for slope optimization for planned pit pushbacks.
ISSN:0960-3182
1573-1529
DOI:10.1007/s10706-024-02749-w