Efficient Probabilistic Back-Analysis of Slope Stability Model Parameters
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 136, Issue 1
Abstract
Back-analysis of slope failure is often performed to improve one’s knowledge on parameters of a slope stability analysis model. In a failed slope, the slip surface may pass through several layers of soil. Therefore, several sets of model parameters need to be back-analyzed. To back-analyze multiple sets of slope stability parameters simultaneously under uncertainty, the back-analysis can be implemented in a probabilistic way, in which uncertain parameters are modeled as random variables, and their distributions are improved based on the observed slope failure information. In this paper, two methods are presented for probabilistic back-analysis of slope failure. For a general slope stability model, its uncertain parameters can be back-analyzed with an optimization procedure that can be implemented in a spreadsheet. When the slope stability model is approximately linear, its parameters can be back-analyzed with sensitivity analysis instead. A feature of these two methods is that they are easy to apply. Two case studies are used to illustrate the proposed methods. The case studies show that the degrees of improvement achieved by the back-analysis are different for different parameters, and that the parameter contributing most to the uncertainty in factor of safety is updated most.
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Acknowledgements
This research was substantially supported by the Research Grants Council (RGC) of the Hong Kong SAR (Project Nos. UNSPECIFIED620206 and UNSPECIFIED6294/04E).
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Information
Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 136 • Issue 1 • January 2010
Pages: 99 - 109
Copyright
© 2010 ASCE.
History
Received: Apr 20, 2008
Accepted: Jul 23, 2009
Published online: Dec 15, 2009
Published in print: Jan 2010
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