dc.contributor.authorJi, Jian
dc.contributor.authorLiao, H. J.
dc.contributor.authorLow, Bak Kong
dc.date.accessioned2013-06-28T07:29:53Z
dc.date.available2013-06-28T07:29:53Z
dc.date.copyright2012en_US
dc.date.issued2012
dc.identifier.citationJi, J., Liao, H. J., & Low, B. K. (2012). Modeling 2-D spatial variation in slope reliability analysis using interpolated autocorrelations. Computers and Geotechnics, 40, 135-146.en_US
dc.identifier.issn0266-352Xen_US
dc.identifier.urihttp://hdl.handle.net/10220/10833
dc.description.abstractThis paper deals with slope reliability analysis incorporating two-dimensional spatial variation. Two methods, namely the method of autocorrelated slices and the method of interpolated autocorrelations, are proposed for this purpose. Investigations are carried out based on the limit equilibrium method of slices. First-order-reliability-method (FORM) is coupled with deterministic slope stability analysis using the constrained optimization approach. Systematic search for the probabilistic critical slip surface has been carried out in this study. It is shown that both methods work well in modeling 2-D spatial variation. The results of slope reliability analysis are validated by Monte Carlo simulations. Failure probabilities obtained by FORM agree well with simulation results. It is found that 2-D spatial variation significantly influences the reliability analysis, and that the reliability index is more sensitive to vertical autocorrelation distance than to horizontal autocorrelation distance. Based on this study, failure probability is found significantly overestimated when spatial variation is ignored. Finally, the possible use of the method of interpolated autocorrelations in a probabilistic finite element analysis is suggested.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesComputers and geotechnicsen_US
dc.rights© 2011 Elsevier Ltd.en_US
dc.subjectDRNTU::Engineering::Civil engineering::Geotechnical
dc.titleModeling 2-D spatial variation in slope reliability analysis using interpolated autocorrelationsen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Civil and Environmental Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.compgeo.2011.11.002


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