Abstract
The non-homogenous and often insufficiently characterised nature of rock slopes requires mining geotechnical engineers to ensure that pit design is supported by appropriate operational controls. The consequences and near misses from recent large open pit slope failures (>500 m3 failed volume) have driven industry bodies to further refine the delineation of wall failure runout distances. In managing failure hazards, a standoff distance is typically determined by the prediction of potential failure mechanism, volume, and runout distance. Accurate prediction of the runout distance is critical to mine operations for safety and economic reasons. Whilst a comprehensive dataset and research history exists for slope runout predictions in environments such as rock avalanches, landslides, and natural debris flows, similar work directly applicable to the open cut coal mining industry is in its infancy. In particular, the travel angle, or Fahrboschung angle, is a well-recognised relationship that has been used for excavated slopes but is not commonly applied to open cut coal slopes less than 100 m. This investigation has taken the opportunity to gather and interpret new data points from historic failures to improve the accuracy of runout distance predictions. The new dataset included over 50 additional historic open cut highwall failures from eight open cut coal mines situated across the Bowen Basin and the Hunter Valley. Systematic characterisation of runout distances was based on geotechnical parameters such as in situ wall failure height, floor dip, slope angle, failure mechanism, volume of failed material, and geotechnical domain. Through detailed analysis, this new dataset has been statistically evaluated and showed comparable results to previously published data, including the coal industry specific slope stability assessment methodology (SSAM) tool, as well as new empirical trends. Additionally, the investigation has considered initial works for a Fahrboschung angle relationship. This database can be used as a proactive tool to inform failure run out predictions, and also to ensure learnings and data from past failure history is captured and used by the next generation of geotechnical engineers without having to experience past failures.
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