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Probabilistic methods applied to slope stability analysis

by St. George, J. D.

Abstract (Summary)
In slope stability analysis, as with other areas of geotechnical engineering, there is a high degree of uncertainty associated with design parameters. Engineers rely heavily on historical information and present performance to establish criteria. The observational approach which is essentially taking a Bayesian stance is advocated in most projects. The purpose of this study was to develop a method which will augment current design practice for mine slope stability, with the use of strength parameters derived from the back analysis of failures. A computerised database system for the storage of slope instability cases was developed using a commercial package. This enabled consistent and complete records of failures to be stored and recalled for analysis. To utilize these back analysis results in a probabilistic framework, a Bayesian approach was formulated to calculate the probability distribution of c-?. Two separate likelihood functions were derived from the observations of slope failures in similar materials for 1) The functional relationship between the c-? parameters required to meet critical equilibrium conditions. 2) The average normal and shear stress conditions on the failure surface. Uniform prior distributions were used to assess the likelihood function. Strength properties from tests and other sources were collated into informative priors and the corresponding posterior distributions defined. Both likelihood functions produced results in agreement with reported test results. A probabilistic model based on the first-order second moment approach was developed to cope with circular and non-circular slope stability analyses. The spatial variability of the random variables was incorporated into this model and by considering the contributions of the end resistance a quasi 3-D probability of failure was derived. All the case studies were analysed using this model with the posterior strength parameters. It was found that the spatial variability only had a major effect when the range of influence of the variability was small compared to the size of the slope. Both watertable and model error had much greater effect on the variance. The 3-D aspects of failure were investigated and a lateral release factor was introduced to assess the importance of the end resistance on the failure probability. A predictive analysis was presented to demonstrate the use of these methods in slope design. End resistance was shown to have most impact on 3-D probability of failure.
Bibliographical Information:

Advisor:Dr W. Schaap

School:The University of Auckland / Te Whare Wananga o Tamaki Makaurau

School Location:New Zealand

Source Type:Master's Thesis

Keywords:fields of research 290000 engineering and technology

ISBN:

Date of Publication:01/01/1991

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