In this paper we investigate the probability of failure of a cohesive slope using both simple and more advanced probabilistic analysis tools. The influence of local averaging on the probability of failure of a test problem is thoroughly investigated. In the simple approach, classical slope stability analysis techniques are used, and the shear strength is treated as a single random variable. The advanced method, called the random finite-element method (RFEM), uses elastoplasticity combined with random field theory. The RFEM method is shown to offer many advantages over traditional probabilistic slope stability techniques, because it enables slope failure to develop naturally by “seeking out” the most critical mechanism. Of particular importance in this work is the conclusion that simplified probabilistic analysis, in which spatial variability is ignored by assuming perfect correlation, can lead to unconservative estimates of the probability of failure. This contradicts the findings of other investigators w...

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Probabilistic slope stability analysis by finite elements

The impact of uncertainty on the reliability of slope design and performance assessment is often significant. Conventional slope practice based on the factor of safety cannot explicitly address unc...

Probabilistic slope stability analysis for practice

The paper investigates the probability of failure of slopes using both traditional and more advanced probabilistic analysis tools. The advanced method, called the random finite-element method, uses elastoplasticity in a finite-element model combined with random field theory in a Monte-Carlo framework. The traditional method, called the first-order reliability method, computes a reliability index which is the shortest distance (in units of directional equivalent standard deviations) from the equivalent mean-value point to the limit state surface and estimates the probability of failure from the reliability index. Numerical results show that simplified probabilistic analyses in which spatial variability of soil properties is not properly accounted for, can lead to unconservative estimates of the probability of failure if the coefficient of variation of the shear strength parameters exceeds a critical value. The influences of slope inclination, factor of safety (based on mean strength values), and cross correlation between strength parameters on this critical value have been investigated by parametric studies in this paper. The results indicate when probabilistic approaches, which do not model spatial variation, may lead to unconservative estimates of slope failure probability and when more advanced probabilistic methods are warranted.

/pdf/influence-of-spatial-variability-on-slope-reliability-using-1ygk0d3pdn.pdf

Influence of spatial variability on slope reliability using 2-D random fields.

Recent years have seen rapidly growing research into applied probability and increased interest in applications to geotechnical engineering practice. Unfortunately, probability still remains a mystery to many engineers, partly because of a language barrier and partly from lack of examples showing how the methodology can be used in the decision‐making process. The following types of applications are described and illustrated in general terms: separating systematic and random errors when evaluating uncertainty in the stability of slopes; safety factors in connection with analysis of liquefaction; optimizing the design of an embankment in the face of uncertainty concerning stability; risk evaluation for an industrial facility built over potentially liquefiable soils; and risk evaluation for earth dams. Even when a precise quantification of probability of failure is not possible, systematic formulation of an analysis aids greatly in understanding the major sources of risk and thus points the way for costeffec...

Evaluating calculated risk in geotechnical engineering

This paper discusses some improvements on the first-order second-moment (FOSM) probabilistic approach to slope design. The stability model by Morgenstern and Price is used for the formulation of th...

Probabilistic design of slopes

Probabilistic approach to design of embankments

Variable message signs (VMS) are used to provide dynamic information and one current application is to show different speed limits under different conditions. As speed is an important contributor to road accidents and also affects driver speed behavior, the present study focuses on how effective traffic advisory information is when helping drivers to divert from potentially dangerous conditions. Graphical representation of an Expressway section made it easy to isolate the effects of speed etc. by drivers with information provided through VMS under adverse fog conditions. Understanding and reacting to the VMS system by drivers is essential for its success. If drivers do not react by changing speed behavior then the VMS system will fail and further implementation may cease. In this paper an Analysis of Variance model, which is appropriate to the proposed experimental conditions, is used to study how subjects (drivers) will perceive provided information and also to find the effect of VMS on driver speed behavior on the simulated Expressway section.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/atr.5670400104

Effect of variable message signs on driver speed behavior on a section of expressway under adverse fog conditions—A driving simulator approach

A new look at fluctuating geotechnical data for reliability design

International Container Transportation Network Analysis Considering Post-Panamax Class Container Ships

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Katsuhiko Kuroda

Papers

Probabilistic approach to design of embankments

Effect of variable message signs on driver speed behavior on a section of expressway under adverse fog conditions—A driving simulator approach

A new look at fluctuating geotechnical data for reliability design

International Container Transportation Network Analysis Considering Post-Panamax Class Container Ships

Safety Assessment of Mooring at Anchor under Stormy Weather