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Slope Stability Analysis Based on Autocorrelated Shear Strength Parameters

La stabilité d’un versant basé sur l’autocorrélation de la résistance de cisaillement

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Abstract

The stability of a slope is governed by the spatial average of the shear strength over the extent of the failure surface. In Eurocode 7 the average soil properties are taken into account by defining the characteristic soil parameter as being “a cautious estimate of the value affecting the occurrence of the limit state” and further stating that this value should be based on, among other factors, “the extent of the zone of ground governing the behavior of the geotechnical structure at the limit state being considered”. To completely quantify the characteristic shear strength along a failure surface, three statistical values are required: the arithmetic mean, the variance and the spatial correlation. The mean soil properties and to a lesser degree the variance (or equivalently the standard deviation or the coefficient of variation) are known and used by most geotechnical engineers for the selection of characteristic soil properties. The scale of fluctuation, however, is not generally used. The scale of fluctuation is a measure of the soil spatial variability and can be understood as the range within which soil properties are correlated and beyond which they are statistically uncorrelated. This paper investigates the influence of the variability of shear strength on the reliability of slopes based on simulated autocorrelated random fields created by the turning bands method. In particular, the influence of the length of the failure surface on the characteristic value is investigated. Numerical Monte Carlo analyses verify the validity of a simplified practical approach presented to determine the characteristic soil properties according to Eurocode 7.

Résumé

La stabilité d’un versant est régnée par la moyenne spatiale de la résistance de cisaillement sur l’extension de la surface coulissante. Dans l’Eurocode 7 une moyenne des propriétés du sol est tenue compte, par définir le paramètre caractéristique du sol comme “une estimation prudent de la valeur, qui concerne l’apparition de l’état limité” et puis, que cette valeur devrait, entre autres facteurs, être basée sur “l’implication de l’extension de la zone du sol régné du comportement de la structure géotechnique dans l’état limité”. Pour pouvoir quantifier complètement les caractéristiques de la résistance de cisaillement le long de la surface coulissante, il y en a besoin de trois valeurs: la valeur moyenne arithmétique, la variance et la corrélation spatiale. La valeur moyenne des propriétés du sol, et dans une moindre mesure la variance (ou bien aussi l’écart normal ou le coefficient de variation) sont connus et utilisés d’une majorité des ingénieurs en géotechnique pour sélectionner des propriétés caractéristiques du sol. La corrélation spatiale n’est pas beaucoup utilisée en général. C’est une mesure pour l’échelle de fluctuation, par exemple la marge entre les propriété du sol qui sont en corrélation et au-delà quelles ne sont statistiquement pas en corrélation. Cette mémoire recherche l’influence de la variabilité de la résistance de cisaillement sur la fiabilité d’un versant, basé sur des prélèvements simulés en autocorrélation avec la turning bands method. L’influence de la longueur de la surface coulissant sur la valeur caractéristique est en particulier recherchée. L’analyse numérique de Monte Carlo vérifie la validité d’une approche plus simple et plus pratique, présenté pour déterminer les caractéristiques des propriétés du sol selon l’Eurocode 7.

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Acknowledgments

We gratefully acknowledge the support of HSR (University of Applied Sciences, Rapperswil, Switzerland) and the contributions of Santiago Quinteros (HSR).

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Correspondence to P. Fitze.

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*Previously published in Anagnostopoulos et al. (2011). Reprinted—Published in revised form with kind permission of IOS Press.

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Tietje, O., Fitze, P. & Schneider, H.R. Slope Stability Analysis Based on Autocorrelated Shear Strength Parameters. Geotech Geol Eng 32, 1477–1483 (2014). https://doi.org/10.1007/s10706-013-9693-8

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  • DOI: https://doi.org/10.1007/s10706-013-9693-8

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