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For a slope with a large number of potential slip surfaces, the consequence of slope failure along different slip surfaces could be quite different. When the soil parameters are uncertain, the location of the slip surface with minimum factor of safety is also uncertain, making the consequence of slope failure also uncertain. The traditional equation for risk assessment may only be suitable for slope failure along a given slip surface, but may not be directly applicable to slope failure with a large number of potential slip surfaces. In this study, a new equation is suggested for risk assessment of slope failure considering the system failure probability. A response surface method is used to enhance the computational efficiency. Three slopes are studied to illustrate the proposed method. It is found that the consequence of slope failure is an important weighting factor in the risk assessment of slope failure. A slip surface with a larger failure probability but small consequence may be associated with a smaller risk. Hence, the most probable failure surface may not always be the slip surface with the largest risk. For the three examples studied in this paper, the risk of slope failure are all governed by the representative slip surfaces. Therefore, the risk of slope failure can then be assessed in a simplified manner by taking into account only the representative slip surfaces. Both the reliability method and empirical method can be used for representative slip surfaces identification. [ABSTRACT FROM AUTHOR]

Abstract: While a soil slope may have a large number of potential slip surfaces, its system failure probability is usually governed by a few representative slip surfaces due to the high correlation between factors of safety (FOS) of different slip surfaces. This paper shows that, despite its embedded empiricism, the Hassan and Wolff method can identify with reasonable accuracy not only the most critical slip surface, but also representative slip surface for system reliability analysis. In the Hassan and Wolff method, the assumed distribution of FOS has important effect on the calculated failure probability and it is not appropriate to always assume FOS is lognormally distributed. Whether the system effect in a slope reliability analysis is obvious can be judged easily by comparing the values of reliability index of different representative slip surfaces. Combined with the response surface method, the Hassan and Wolff method can be extended into a practical tool for system reliability analysis utilizing existing deterministic slope stability analysis programs. A simple equation is provided to estimate the bounds of system failure probability based on the most critical slip surface. [Copyright &y& Elsevier]

Piles are widely used to increase the stability of piles. Probabilistic methods can be used to explicitly consider the uncertainties involved in a slope stability analysis. Currently, most probabilistic slope stability analyses focus on the reliability of slopes without reinforcement. In this paper, an existing method for system reliability analysis of unreinforced slopes is extended to slopes reinforced with piles. The described procedure may potentially be used to convert other methods for reliability analysis of slopes without reinforcement to slopes reinforced with piles. Two examples are used to illustrate the suggested method. It is found that the location of the most critical slip surface of the reinforced slope generally differs from that of the unreinforced slope, and may change with the pile location and the pile spacing. The optimal locations of the piles with and without considering the uncertainties in the soil property are different. For slopes in layered soils, the system failure probability may be governed by several representative slip surfaces even when piles are installed. The system effect is more obvious when the pile spacing increases. To maximize the effectiveness of slope stabilization, the stabilizing piles should intersect with all representative slip surfaces with significant failure probabilities. [ABSTRACT FROM AUTHOR]

Although a slope may have numerous potential slip surfaces, its failure probability is often governed by several representative slip surfaces (RSSs). Previous efforts mainly focus on the identification of circular RSSs based on limit equilibrium methods. In this paper, a method is suggested to identify RSSs of arbitrary shape based on the shear strength reduction method. Monte Carlo simulation is used to generate a large number potential slip surfaces. The RSSs are identified through analyzing the failure domains represented by these samples. A kriging-based response surface model is employed to enhance the computational efficiency. These examples shows that the RSSs may not always be circular, and that the suggested method can effectively locate the RSSs without making prior assumptions about the shape of the slip surfaces. For the examples investigated, the system failure probabilities computed based on the shear strength reduction method are comparable to, but not the same as those computed based on the limit equilibrium methods. The suggested method significantly extends our capability for identifying non-circular RSSs and hence probabilistic slope stability analysis involving non-circular slip surfaces. [ABSTRACT FROM AUTHOR]

Site investigation is widely used for uncertainty reduction and design improvement in slope engineering. Before the site investigation is implemented, it is important to assess and compare the effectiveness of different site investigation programs. In this paper, an efficient method for analyzing the effectiveness of a site investigation program for slope stability assessment through value of information analysis is proposed. In this method, a logistic regression model is developed to approximate the relationship between failure probability of the slope and the site investigation data, through which the evaluation of posterior distribution and slope reliability analyses are both avoided. The suggested method is illustrated and verified with an example. For the example studied in this paper, the number of slope stability analyses required is only 1% of that reported in the literature. The suggested method can be used to study the effects of locations of the boreholes, the number of boreholes, and the depth of boreholes on the effectiveness of a site investigation program. [ABSTRACT FROM AUTHOR]