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Climate resiliency of a tailings management facility: case study of Mont-Wright mine

ABSTRACT This study investigates the climate resiliency of the Mont-Wright mine tailings management facility (TMF) in Quebec, Canada, with a focus on tailings erosion and flooding. Ultra-high resolution (1 km) climate simulations of the global environmental multiscale (GEM) model, spanning the current (2001–2020) and future (2041–2060) periods, form the basis of this study. Comparison of GEM model outputs against gridded observation data suggests reasonable performance of the model in simulating TMF-relevant climate variables, giving confidence in the model. The analysis indicates potential increases in tailings erosion rates of up to 6% (0.01 g/m2s) for the future period due to elevated wind-induced shear stress. Floods, represented in terms of probable maximum flood, reveal future increases in magnitudes of up to 20% in summer/fall for durations of 12–72 h. Increases of up to 17% are projected for spring for the 72-h duration, with decreases noted for other durations due to precipitation efficiency reductions. The projected small increases in erosion rates, in absolute terms, are not deemed to be of any major concern. As for projected increases in flooding, Mont-Wright mine’s climate-change adaptation strategy, which is aligned with existing Quebec guidelines, seems reasonable to mitigate flooding impacts.

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Opportunities for research to achieve the vision of the Smart Mine

ABSTRACT The mining industry is being shaped by ongoing digital transformation, leading to the Smart Mine. This article aims to clarify this concept for underground extraction operations as expressed by mining practitioners and compare this vision with recent academic work. Based on an industry-focused literature review, this paper categorizes the vision of the Smart Mine in terms of objectives, solutions, and business management processes. The framework is then used to analyze academic papers selected from a systematic literature review. Results show that mining practitioners and academics are aligned in terms of the financial, operational, business, safety, and environmental objectives of the underground Smart Mine. Multiple solutions to achieve a Smart Mine are proposed and involve infrastructure, technology, people, culture, management systems, processes, and equipment. Both academics and mining practitioners focus on equipment and technology initiatives, while people and culture are underestimated. These solutions involve various business management processes, with a greater emphasis from practitioners on environmental, social, and governance (ESG) and information and data management. However, the academic literature on business management processes is relatively sparse and mainly focuses on education and training, automation management, and ESG management. Asset management, change management, and risk and safety management should be further developed.

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Rock mass strength variability for probabilistic open-pit slope stability analysis

ABSTRACT As part of reliability-based design acceptance criteria, probabilistic slope stability analysis is increasingly being used for open-pit slope design. This analysis evaluates the mean factor of safety, probability of failure, and coefficient of variation for the resulting probability density function of factor of safety values. Estimating rock mass strength variability is crucial. Hoek–Brown criteria are commonly used strength parameters, as are equivalent Mohr–Coulomb parameters (calculated from Hoek–Brown), particularly for probabilistic slope stability analysis. This article describes these two strength criteria when considering univariate and bivariate distributions of the unconfined compressive strength and rock material constant. Results demonstrate differences in the variability of the equivalent Mohr–Coulomb parameters under different dependence considerations than the Hoek–Brown parameters, potentially affecting the calculated probability of failure and factor of safety results. Furthermore, they highlight an inherent correlation between Mohr–Coulomb parameters that derives from the algorithm used to calculate them from Hoek–Brown criteria. This inherent correlation is important to obtain mean factors of safety, probabilities of failure, and coefficients of variation that are consistent with the variability in Hoek–Brown parameters estimated by the practitioner and are, therefore, key to informed implementation of reliability-based design acceptance criteria.

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