Probabilistic assessment of rock slope stability using response surfaces determined from finite element models of geometric realizations

A methodology is developed for probabilistic rock slope stability assessment using numerical modelling that incorporates statistical analysis of the variability of joint set geometric parameters. Each probabilistic input parameter is substituted by its two point estimates. Half-factorial and central composite designs are implemented to obtain a minimum number of representative slope realizations to model. The output from the numerical models is used to construct mathematical prediction models or response surfaces. A response surface can be used to predict the factor of safety of arbitrary realizations without further numerical modelling and can be used to determine the probability of slope failure.     

Probabilistic stability analyses of undrained slopes by 3D random fields and finite element methods

A long slope consisting of spatially random soils is a common geographical feature. This paper examined the necessity of three-dimensional(3 D) analysis when dealing with slope with full randomness in soil properties. Although 3 D random finite element analysis can well reflect the spatial variability of soil properties, it is often time-consuming for probabilistic stability analysis. For this reason, we also examined the least advantageous(or most pessimistic) cross-section of the studied slope. The concept of"most pessimistic" refers to the minimal cross-sectional average of undrained shear strength. The selection of the most pessimistic section is achievable by simulating the undrained shear strength as a 3 D random field. Random finite element analysis results suggest that two-dimensional(2 D) plane strain analysis based the most pessimistic cross-section generally provides a more conservative result than the corresponding full 3 D analysis. The level of conservativeness is around 15% on average. This result may have engineering implications for slope design where computationally tractable 2 D analyses based on the procedure proposed in this study could ensure conservative results.     

Stochastic response surface method for reliability analysis of rock slopes involving correlated non-normal variables

This paper proposes a stochastic response surface method for reliability analysis involving correlated non-normal random variables, in which the Nataf transformation is adopted to effectively transform the correlated non-normal variables into independent standard normal variables. Transformations of random variables that are often used in reliability analyses in terms of standard normal variables are summarized. The closed-form expressions for fourth to sixth order Hermite polynomial chaos expansions involving any number of random variables are formulated. The proposed method will substantially extend the application of stochastic response surface method for reliability problems. An example of reliability analysis of rock slope stability with plane failure is presented to demonstrate the validity and capability of the proposed stochastic response surface method. The results indicate that the proposed stochastic response surface method can evaluate the reliability of rock slope stability involving correlated non-normal variables accurately and efficiently. Its accuracy is shown to be higher than that for the first-order reliability method, and it is much more efficient than direct Monte-Carlo simulation. The results also show that the number of collocation points selected should ensure that the Hermite polynomial matrix has a full rank so that different order SRSMs can produce a robust estimation of probability of failure for a specified performance function. Generally, the accuracy of SRSM increases as the order of SRSM increases.     

Efficient system reliability analysis of soil slopes using multivariate adaptive regression splines-based Monte Carlo simulation

System effects should be considered in the probabilistic analysis of a layered soil slope due to the potential existence of multiple failure modes. This paper presents a system reliability analysis approach for layered soil slopes based on multivariate adaptive regression splines (MARS) and Monte Carlo simulation (MCS). The proposed approach is achieved in a two-phase process. First, MARS is constructed based on a group of training samples that are generated by Latin hypercube sampling (LHS). MARS is validated by a specific number of testing samples which are randomly generated per the underlying distributions. Second, the established MARS is integrated with MCS to estimate the system failure probability of slopes. Two types of multi-layered soil slopes (cohesive slope and c–φ slope) are examined to assess the capability and validity of the proposed approach. Each type of slope includes two examples with different statistics and system failure probability levels. The proposed approach can provide an accurate estimation of the system failure probability of a soil slope. In addition, the proposed approach is more accurate than the quadratic response surface method (QRSM) and the second-order stochastic response surface method (SRSM) for slopes with highly nonlinear limit state functions (LSFs). The results show that the proposed MARS-based MCS is a favorable and useful tool for the system reliability analysis of soil slopes.     

Reliability analysis using radial basis function networks and support vector machines

To reduce computational costs in structural reliability analysis, utilising approximate response surface functions for reliability assessment has been suggested. Based on the similarities of two adaptive and flexible models, the radial basis function neural network (RBFN) and support vector machine (SVM), the derivatives of the approximate functions of RBFN and SVM models with respect to basic variables are given, and two RBFN-based RSMs (RBFN-RSM1, RBFN-RSM2) and two SVM-based RSMs (SVM-RSM1, SVM-RSM2) are studied. The similarities and differences of these methods are reviewed, and the applicability of these methods is illustrated using five examples. It is shown that there is no obvious difference between RBFN-based RSMs and SVM-based RSMs, and the number of samples needed in RBFN/SVM-RSM2 is smaller than that of RBFN/SVM-RSM1.     

Identification of representative slip surfaces for reliability analysis of soil slopes based on shear strength reduction

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.     

Probabilistic analysis of underground rock excavations using response surface method and SORM

Probabilistic analysis of underground rock excavations is performed using response surface method and SORM, in which the quadratic polynomial with cross terms is used to approximate the implicit limit state surface at the design point. The response surface is found using an iterative algorithm and the probability of failure is evaluated using the first-order and the second-order reliability method (FORM/SORM). Independent standard normal variables in U-space are chosen as basic random variables and transformed into correlated non-normal variables in the original space of random variables for constructing the response surface. The proposed method is first illustrated for a circular tunnel with analytical solutions considering Mohr–Coulomb (M–C) and Hoek–Brown (H–B) yield criteria separately. The failure probability with respect to the plastic zone criterion and the tunnel convergence criterion are estimated from FORM/SORM and compared to those obtained from Monte Carlo Simulations. The results show that the support pressure has great influence on the failure probability of the two failure modes. For the M–C model, the hypothesis of uncorrelated friction angle and cohesion will generate higher non-performance probability in comparison to the case of negatively correlated shear strength parameters. Reliability analyses involving non-normal distributions are also investigated. Finally, an example of a horseshoe-shaped highway tunnel is presented to illustrate the feasibility and validity of the proposed method for practical applications where numerical procedures are needed to calculate the performance function values.     

Selected aspects of the stability assessment of slopes with the assumption of cylindrical slip surfaces

A comprehensive analysis of maintaining stability by model homogeneous and stratified slopes, with possible surcharge loading, is carried out within the article. Calculations are performed by the Swedish method of Fellenius under the assumption of a cylindrical slip surface passing through the slope foot. Proposals for searching for the reach of the break-off wedge of a potential slip surface are put forward. An analysis of the effect of surcharge load location on general slope stability is also made, providing the capability to determine the safe distance of positioning of an excavator on the surcharge of a non-encased excavation.     

Determination of the critical failure surface for slope stability analysis using ant colony optimization

Slope stability analysis of any natural or artificial slope aims at determining the factor of safety of the slip surface that possesses the lowest factor of safety. In this study, an ant colony optimization (ACO) algorithm is developed to solve this factor-of-safety minimization problem. Factors of safety of slip surfaces are found by using the Morgenstern–Price method, which satisfies both force and moment equilibrium. Nonlinear equations from the Morgenstern–Price method are solved numerically by the Newton–Raphson method. In the proposed ACO algorithm, the initiation point and the shape of the slip surface are treated as the search variables. The proposed heuristic algorithm represents slip surfaces as piecewise-linear curves and solves for the optimal curve yielding the minimum factor of safety. To demonstrate its applicability and to investigate the validity and effectiveness of the algorithm, four examples with varying complexity are presented. The obtained results are compared with the available literature and are found to be in agreement.     

人工神经网络在石佛寺滑坡稳定性评价中的应用

综合考虑影响滑坡稳定性的众多因素,建立了基于人工神经网络的滑坡稳定性预测模型,并结合已有的工程实例对所建立的神经网络进行训练,在网络模型的训练过程中,还针对不同训练函数的训练效果进行了对比研究。最后针对湖北省兴山县高阳峡口复建公路段沿线石佛寺Ⅰ、Ⅱ滑坡的稳定性问题进行了预测。结果表明,所建立的滑坡稳定性预测模型具有较好的预测精度,同时也说明了神经网络方法在滑坡稳定性预测中的有效性及良好的发展前景。     

Prediction of surface crown pillar stability using artificial neural networks

A relatively novel technique, artificial neural networks (ANN), is used in predicting the stability of crown pillars left over large excavations. Data for the training and verification of the networks were obtained from the literature. Four artificial networks, based on two different architectures, were used. The networks used different numbers of input parameters to predict the stability or failure of crown pillars. Multi‐layer perceptron networks using mine type, dip of orebody, overburden thickness, pillar thickness, pillar length, stope height, backfill height, Rock Mass Rating (RMR) of the host rock and RMR of the orebody showed excellent performance in training and verification. Adding three more variables, namely pillar width, rock density and pillar thickness to width ratio, showed symptoms of over‐learning without degrading performance significantly. Radial basis function networks were capable of predicting crown pillar behaviour on the basis of few input functions. It was shown that mine type, dip and pillar thickness to width ratio can be used for a preliminary estimation of stability. Copyright © 2006 John Wiley & Sons, Ltd.     

Probabilistic analysis of reinforced slopes using RFEM and considering spatial variability of frictional soil properties due to compaction

Probabilistic stability analyses of constructed wrapped-face reinforced slopes (or embankments) using frictional soils were carried out using the random finite element method (RFEM). Soil properties reported in the literature for unsaturated frictional fills compacted to different densities were used in the simulations. Bar elements were added to the RFEM code to simulate extensible geosynthetic reinforcement layers and the Davis approach was used to improve numerical stability for purely frictional soil slopes at collapse. The influence of isotropic and anisotropic spatially variable soil strength was investigated and shown to have a large influence on the variation of maximum mobilised tensile forces in reinforcement layers for the steep 5 m-high slopes in the study. The influence of fill placed at different layer thickness and compacted to different levels was simulated by adjusting the soil strength and unit weight, and the vertical strength correlation length in the anisotropic spatially variable strength field used in each slope realisation. Numerical results showed that vertical strength correlation lengths approaching the magnitude of fill lift heights can control the probability of failure for reinforced slopes constructed with weak fills placed in lift heights close to but less than the wrapped reinforcement spacing used in the study.     

基于响应面法的边坡稳定二阶可靠度分析

提出了基于响应面法的边坡稳定二阶可靠度分析的实用算法。选择U空间中的随机变量,通过空间变换和相关矩阵分解,计算试验点的功能函数;通过迭代算法构造响应面、以确保通过最小的计算量获得最优精度,并在此基础上进行FORM/SORM计算。以一岩石边坡的平面滑动问题为例,通过与蒙特卡洛模拟、FORM及随机响应面法的比较,证明了该方法的准确性和高效性。分析了参数的相关性及试验点取值范围对计算结果的影响,讨论了可靠度分析结果中参数敏感性和物理属性问题。该方法可为实际边坡问题的可靠度分析提供参考,并可以用来进行基于可靠度分析的加固设计。     

Numerical simulation of the undrained stability of slopes in anisotropic fine-grained soils

The undrained stability of slopes in anisotropic fine-grained soils is studied in this paper using the finite element method (FEM). A constitutive model is presented, able to account for the observed variation of undrained strength with loading direction. The model is able to encompass the different strength distributions observed in normally, slightly overconsolidated and heavily overconsolidated soils. A series of stability analyses have been performed to explore the effect of the type of undrained strength anisotropy on the stability and failure mechanisms of slopes of different inclinations. In addition, a real case study of the failure of an underwater slope is analysed with the numerical approach presented. It suggests that, by considering undrained strength anisotropy, the failure can be satisfactorily explained.     

Influence of rainfall-induced wetting on the stability of slopes in weathered soils

Shallow failures of slopes in weathered soil are caused by infiltration due to prolonged rainfall. These failures are mainly triggered by the deepening of the wetting band accompanied by a decrease in matric suction induced by the water infiltration. This paper reports trends of rainfall-induced wetting band depth in two types of weathered soils that are commonly found in Korea. Both theoretical and numerical analyses for wetting band depth are presented based on the soil–water characteristic curve obtained using filter paper as well as tensiometer tests. It is found that the magnitude of wetting front suction plays a key role in the stability of slopes in weathered soils. Theoretical analysis based on modified Green and Ampt model tends to underestimate the wetting band depth for typical Korean weathered soils. It was also deduced that for Korean weathered soils, the factor of safety drops rapidly once the wetting band depth of 1.2 m reached.     

System reliability analysis of soil slopes with general slip surfaces using multivariate adaptive regression splines

A data driven multivariate adaptive regression splines (MARS) based algorithm for system reliability analysis of earth slopes having random soil properties under the framework of limit equilibrium method of slices is considered. The theoretical formulation is developed based on Spencer method (valid for general slip surfaces) satisfying all conditions of static equilibrium coupled with a nonlinear programming technique of optimization. Simulated noise is used to take account of inevitable modeling inaccuracies and epistemic uncertainties. The proposed MARS based algorithm is capable of achieving high level of computational efficiency in the system reliability analysis without significantly compromising the accuracy of results.     

Probabilistic analysis of simple slopes with cohesive soil strength using RLEM and RFEM

The 2D random finite element method and the one-dimensional and 2D random limit equilibrium method are used to investigate the influence of spatial variability of soil strength parameters on the probability of failure of simple soil slopes with cohesive undrained shear strength. The combined influence of spatial variability of soil properties and cross-correlation between undrained soil strength and unit weight on the computed probability of failure is explored. The paper identifies conditions where numerical outcomes are similar and where they are not. The limitations of each analysis method are described and implications to analysis and design are identified.

Abbreviations: FEM: finite element method; LEM: limit equilibrium method; RFEM: random finite element method; RLEM: random limit equilibrium method     

边坡稳定性神经网络评价模型中断裂构造的定量化处理

神经网络模型应用于边坡稳定性评价已取得不少成果,但总体上仍处于理论研究阶段,因子的选择及因子的定量化处理问题尚无统一认识,因断裂构造因素难以量化处理,很多评价中未进行考虑,影响了边坡稳定性评价的效果。本文提出用岩体完整性指数反映断裂构造作用对边坡稳定性的影响,具有一定的地质依据,为神经网络模型评价过程中断裂构造因素的定量化处理提供了一种思路,具有一定的实践意义。     

Shear strength of municipal solid waste for stability analyses

This paper investigates the shear strength of municipal solid waste (MSW) using the back analysis of failed waste slopes as well as field and laboratory test results. Shear strength of MSW is a function of many factors such as waste type, composition, compaction, daily cover, moisture conditions, age, decomposition, overburden pressure, etc. These factors together with non-standardized sampling methods, insufficient sample size to be representative of in situ conditions, and limited shear displacement or axial strain imposed during the laboratory shear testing have created considerable scatter in reported results. Based on the data presented herein, large shear displacements are required to mobilize the peak shear strength of MSW which can lead to displacement incompatibility between MSW and the underlying material(s) such as geosynthetic interfaces and foundation soils. The data presented herein are used to develop displacement compatible shear strength parameters for MSW. Recommendations are presented for modeling the displacement and stress dependent strength envelope in stability analyses.     

Slope vulnerability to earthquakes at subregional scale, using probabilistic techniques and geographic information systems

The susceptibility of slopes to failure during earthquakes is calculated, in terms of critical horizontal acceleration, on a subregional scale for the upper part of the Serchio River basin (Tuscany, Italy). According to the working scale (1:10 000) and to the availability and accuracy of the input data, the infinite slope analysis was judged to be the most appropriate method, but particular attention was devoted to the error evaluation due to spatial variability of the geotechnic, geometric, and hydrologic parameters. A geologic, geomorphologic and hydrologic survey of the area was therefore performed, and the geotechnic parameters were collected at local administrations. All the data were stored in a GIS, used as a tool to build the spatial and attribute data base and to prepare the input data layers for the stability analysis. In order to assess the variability of geotechnic parameters, a statistical analysis was performed to assign the best-fitting probability distribution to cohesion, angle of internal friction and unit weight of the soil. As hydrogeologic data were not available for the area, only surface hydrology information could be used; a map of probability of spring occurrences was derived by a bayesian method, the Weight of Evidence Modelling, and was used as groundwater indicator. A Monte Carlo procedure and a first-order second-moment method were applied and compared as error estimators in assessing the slope susceptibility to failure. The differences between the two methods are discussed, and two maps showing, respectively, the critical horizontal acceleration and the probability of failure associated with each slope are presented, together with the curve plotting the reliability index against the probability of failure.