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Mine Waste Failure: An Analysis of Empirical and Graphical Runout Predition Methods.

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Title: Mine Waste Failure: An Analysis of Empirical and Graphical Runout Predition Methods.
Author: Srour, Gabriel Hussein
Issue Date: 2011-04-04
Citation: Srour, Gabriel Hussein. 2011. Mine Waste Failure: An Analysis of Empirical and Graphical Runout Predition Methods. Undergraduate Honours Thesis. Department of Earth and Ocean Sciences. University of British Columbia. http://hdl.handle.net/2429/33267
Abstract: Historically, solid mine waste failures have taken many lives, destroyed many homes and have had many other negative impacts on the public and on mining companies. Laws passed after the 1966 Aberfan tragedy, which resulted in a loss of 144 lives, forced mining companies to reduce the risk involved in mine waste practice by making it illegal for mine waste dumps to fail. Since then, there have still been several failures, but mine waste management practices have improved. Recent efforts have focused on determining the risk involved with mine waste dumps. One approach to determining the risk associated with a mine waste dump is to predict the travel distance of a potential failure. The dilemma with runout prediction is that current runout prediction tools are often oversimplified, underdeveloped and under-tested. This report provides the engineer with important background information into the construction, stability and risk involved with mine waste failures. It presents seven tools used to assess this risk and it further tests the accuracy of the tools on newly gathered data. One empirical prediction tool proposed by Corominas (1996) was accurate within 7% and recorded a standard variation of 37% with respect to the observed tangent of the fahrböschung. Another formula developed by Golder (1995) was accurate within 18% and had a standard deviation of 35% with respect to the observed runout. The other three empirical tools produced less accurate predictions and are discussed in Section 4. The graphical prediction tools provided a simple and effective means of predicting runout, although inconsistencies arose with some of the case studies. These results show that empirical and graphical runout prediction tools are best used with cases of similar conditions and settings to those which they were created from. They can reliably provide order of magnitude estimations of runout, but further development and testing is necessary before they can be relied upon for accurate estimates.
Affiliation: Geological Engineering, Dept of
URI: http://hdl.handle.net/2429/33267
Peer Review Status: Unreviewed

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