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By J. Wesseloo

Empirical approaches, numerical modelling, and analytical methods are employed in ground support design for rockburst conditions, but only analytical approaches attempt to quantify the safety margins of a design. The Canadian Rockburst Handbook approach is the most widely known analytical approach. Stacey (2016) identified a state of ‘design indeterminacy’, arguing that neither demand nor capacity can be determined with sufficient accuracy for conventional design processes. Since then, several important advancements were made with the development of the deformation-based support design approach. An independent appraisal of the DBSD approach is lacking. This paper provides an independent appraisal of the deformation-based support design method, summarising the approach, identifying implicit and explicit assumptions, highlighting uncertainties, and raising questions requiring resolution. The resolution of the identified issues is necessary to demonstrate that the deformation-based support design methodology – when applied as a design tool – satisfies the standards expected of a robust engineering approach.

Sep 3, 2026

By J. K. Hamidi, A. Esmaeili, A. Mousavi

This study introduces a new hybrid algorithm designed to optimise stope boundaries in sublevel-stoping mines. Stopes were delineated based on the raises’ locations and relevant constraints, including minimum and maximum stope dimensions, stope overlaps, and geotechnical considerations. Particle swarm optimisation was used to determine the optimal locations of raises, while a network-flow algorithm applied constraints and generated stopes surrounding each raise, defining their size and shape. The hybrid algorithm was implemented on a copper deposit in Chile at a depth of 1,000 meters below the surface. A comparative analysis against the network-flow and maximum-value neighborhood algorithms showed that the economic value of stopes produced by the hybrid algorithm exceeds that of the network-flow algorithm by about 4% and exceeds that of the maximum-value neighborhood algorithm by about 7.5%. Moreover, the proposed algorithm was able to produce stable stope layouts for large-scale problems within a reasonable solution time. These findings are promising, particularly given the growing prevalence of high-tonnage, low-grade deposits in the mining industry.

Sep 3, 2026

By T.M. Mmola

Ambition, while necessary, is insufficient on its own. Material change depends on whether ambition is translated into purposeful action, whether that action takes place within an enabling system, and whether its effects can be demonstrated as meaningful impact. Drawing on experience from the Southern African Institute of Mining and Metallurgy, and in particular the development of the Young Professionals’ Council, the argument is organised around five linked ideas: ambition, the enabling conditions for purposeful action, the distinction between activity, output, outcome and impact, the role of time in the development of impact, and the importance of measurement, learning and adaptation. Professional institutions should therefore judge their success not primarily by the volume of activity they generate, but by the extent to which they strengthen capability, widen participation, support knowledge exchange, and contribute to meaningful and measurable change in the professions and sectors they serve.

Sep 3, 2026

By H. Madani, S. Afraei, F. Sereshki, H. Ghasemzadeh

Spontaneous combustion of coal remains one of the most critical safety challenges in underground coal mining, posing significant risks to personnel, operational continuity, and the environment. Reliable prediction of coal self-heating potential is therefore essential for effective risk management throughout the mine life cycle. This study presents a data-driven framework for evaluating coal spontaneous combustion potential based on intrinsic coal properties derived from proximate and maceral analyses. A comprehensive dataset comprising 165 coal samples was compiled from published experimental studies, representing a wide range of coal characteristics. The crossing point temperature was adopted as a quantitative indicator of spontaneous combustion tendency. To investigate the complex relationships between coal properties and crossing point temperature, a combination of statistical and intelligent modelling approaches was employed, including nonlinear regression, artificial neural networks (multilayer perceptron and radial basis function), and a decision tree classifier. The results demonstrate that the relationship between intrinsic coal parameters and spontaneous combustion potential is inherently nonlinear and multivariate. While nonlinear regression achieved acceptable predictive performance (R² = 0.82), its mathematical complexity limits practical applicability. Among the developed intelligent models, the radial basis function neural network achieved the lowest prediction error (approximately 5.7%). In parallel, the decision tree model achieved a classification error of about 8% while providing a transparent and interpretable structure for practical decision-making. A key contribution of this study is the development of an integrated and interpretable classification framework based on readily available proximate and maceral analysis parameters, addressing the practical limitations associated with the lack of detailed elemental data in many mining operations. The developed framework was further evaluated using independent field samples from the Parvadeh coal mines (Tabas coalfield, Iran), confirming its applicability under real mining conditions. Unlike previous studies that mainly focused on individual algorithms or laboratory-scale datasets, this study establishes a comparative modelling framework by integrating multiple statistical and intelligent approaches using a comprehensive database of 165 coal samples and independent field validation. The proposed approach provides a practical and interpretable tool for assessing coal spontaneous combustion potential, with potential applications in mine design, operational planning, and post-closure risk management.

Sep 3, 2026

By T. J. Otto, M. Mpofu, N. Tlotleng, N. Z. Nkosi, F. Magweregwede, S. Ngobese

Scraper winches remain the primary machinery for moving broken rock in underground narrow reef hard rock mines in South Africa. Despite their longstanding use, significant safety hazards and risks associated with these systems remain. Recent analyses of scraper-winch-related accident data (2015 – 2024) confirmed that scraper winch ropes remain the main hazard and are often linked to insufficient situational awareness and task supervision. A review of scraper winch technologies and alternative broken rock cleaning systems revealed that most potential solutions were previously recommended through research initiatives like the Chamber of Mines Research Organisation, Deepmine, and Futuremine. The implementation of these potential solutions has been constrained by factors such as cost, reliability, and infrastructure compatibility. Key recommendations for improving safety in existing scraper winch operations include proactive rope condition monitoring, improved anchor point rigging, and the integration of proximity detection systems to reduce risks related to worker exposure to the moving parts of the scraper winch system. The implementation of alternative cleaning equipment such as waterjets for face cleaning and ultra-low profile dozers can further improve safety and production. However, the implementation of ultra-low profile dozers is limited by geological and infrastructure constraints. The above solutions focus directly on enhancing the scraper winch system or replacing it with alternative cleaning solutions. Alternatives that would result in the elimination of scraper winch hazards require a change in the mining method. Such solutions include mechanical, ropeless mining methods such as reef boring and reef cutting. Although these technologies offer safety advantages and a means to eliminate scraper-winch-related risks, their economic viability in the South Africa’s narrow reef tabular environments remains challenging.

Sep 3, 2026