Runout exceedance prediction for open pit slope failures
| Autor: | Whittall, John Russell |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Druh dokumentu: | Text |
| Popis: | Consequences from recent large open pit slope failures have increased industry and regulatory interest in establishing exclusion zones beneath an impending slope failure. Damaged infrastructure, equipment, and fatalities have resulted despite geotechnical staff effectively identifying the hazard and predicting the timing of the failure. Creating exclusion zones is a common response to reduce risk, however uncertainty remains as to how far they should extend. Advances in natural landslide research have created useful tools for landslide risk management. These tools have clear applications to pit slopes but most have not been tested or validated. This thesis validates empirical runout tools to a dataset of 105 pit slope failures and provides design charts to explicitly account for runout and runout exceedance in emergency response procedures. Results from the analysis presented demonstrate that Fahrböschung angle vs. volume, Fahrböschung angle vs. slope angle, and inundation area vs. volume relationships follow the general trend of established natural landslide models with similar scatter. However differences in liquefiable substrate, topographic confinement, and a clear dependence on material properties and slope angle necessitate a tool calibrated to open pits. Open pit specific linear regressions are provided and a new mobility index is proposed to accommodate the geometric and material constraints affecting mobility. A design tool is provided to map the inundation area back from the estimated deposit toe. These tools are best applied in a probabilistic framework to scale runout to the mine’s tolerable risk level. Runout exceedance probability charts and simple equations are provided to estimate exclusion zones and integrate runout into the mine’s risk management plan. Science, Faculty of Earth, Ocean and Atmospheric Sciences, Department of Graduate |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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