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Slope reliability and back analysis of failure with geotechnical parameters estimated using Bayesian inference

查看全文 作  者:Luis-Fernando [1]Contreras;Edwin [1]T.Brown 高影响力作者 机构地区:[1]The University of Queensland,St Lucia Campus高影响力机构 出  处:《Journal of Rock Mechanics and Geotechnical Engineering》索引2019年第11卷第3期,共16页高影响力期刊 基  金:supported by the Large Open Pit Ⅱ project through contract No.019799 with the Geotechnical Research Centre of The University of Queensland,Australia and by SRK Consulting South Africa 摘  要:A Bayesian approach is proposed for the inference of the geotechnical parameters used in slope design.The methodology involves the construction of posterior probability distributions that combine prior information on the parameter values with typical data from laboratory tests and site investigations used in design.The posterior distributions are often complex,multidimensional functions whose analysis requires the use of Markov chain Monte Carlo(MCMC)methods.These procedures are used to draw representative samples of the parameters investigated,providing information on their best estimate values,variability and correlations.The paper describes the methodology to define the posterior distributions of the input parameters for slope design and the use of these results for evaluation of the reliability of a slope with the first order reliability method(FORM).The reliability analysis corresponds to a forward stability analysis of the slope where the factor of safety(FS)is calculated with a surrogate model from the more likely values of the input parameters.The Bayesian model is also used to update the estimation of the input parameters based on the back analysis of slope failure.In this case,the condition FS?1 is treated as a data point that is compared with the model prediction of FS.The analysis requires a sufficient number of observations of failure to outbalance the effect of the initial input parameters.The parameters are updated according to their uncertainty,which is determined by the amount of data supporting them.The methodology is illustrated with an example of a rock slope characterised with a Hoek-Brown rock mass strength.The example is used to highlight the advantages of using Bayesian methods for the slope reliability analysis and to show the effects of data support on the results of the updating process from back analysis of failure. 关 键 词:BAYESIAN ANALYSIS HOEK-BROWN CRITERION SLOPE reliability Back ANALYSIS of FAILURE
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