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Rockfall risk management using a pre-failure deformation database
Authors:Ryan A Kromer  Emily Rowe  Jean Hutchinson  Matt Lato  Antonio Abellán
Institution:1.Geomechanics Group, Geological Sciences and Geological Engineering,Queen’s University,Kingston,Canada;2.BGC Engineering,Ottawa,Canada;3.Scott Polar Research Institute,University of Cambridge,Cambridge,UK
Abstract:Terrestrial laser scanning (TLS) monitoring has been used to estimate the location, volume, and kinematics of a variety of small magnitude rockfalls before failure (1–1000 m3 range), and in some cases, potential failure time has been assessed through the application of inverse velocity methods. However, our current understanding of rock slope pre-failure behavior for this magnitude range and prediction ability is based on observations of a small number of failure case histories. In this study, a pre-failure deformation database was constructed for rockfall volumes exceeding 0.1 m3, observed over a 1252-day study interval at the Goldpan rock slope, British Columbia, Canada, in order to better understand the pre-failure behavior of rock slopes and provide an empirical means of estimating temporal failure ranges. Repeated TLS datasets were acquired at an average scanning interval of 2–3 months. A total of 90 rockfall events were recorded at this site, during this time period, of which 64 (71%) exhibited measurable deformation prior to failure. Classification of rockfalls by volume suggests that a scale dependency may exist, as deformation was detected for a greater proportion of rockfalls >?5 m3 (92%) than for smaller rockfalls in the range of 0.1–0.5 m3 (61%). A lower rate of pre-failure deformation detection was also reported for planar sliding failures as compared with wedge or toppling failures, suggesting that deformation was less easily detected for these failure types. This study proposes and implements a framework for rockfall assessment and forecasting that does not require continuous monitoring of deformation.
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