Shui-Hua Jiang

Efficient System Reliability Analysis of Slope Stability in Spatially Variable Soils Using Monte Carlo Simulation

Abstract Monte Carlo simulation (MCS) provides a conceptually simple and robust method to evaluate the system reliability of slope stability, particularly in spatially variable soils. However, it suffers from a lack of efficiency at small probability levels, which are of great interest in geotechnical design practice. To address this problem, this paper develops a MCS-based approach for efficient evaluation of the system failure probability P f , s of slope stability in spatially variable soils. The proposed approach allows explicit modeling of the inherent spatial variability of soil properties in a system reliability analysis of slope stability. It facilitates the slope system reliability analysis using representative slip surfaces (i.e., dominating slope failure modes) and multiple stochastic response surfaces. Based on the stochastic response surfaces, the values of P f , s are efficiently calculated using MCS with negligible computational effort. For illustration, the proposed MCS-based system reliab...

A Study on the Vibration Frequency of Blasting Excavation in Highly Stressed Rock Masses

During blasting excavation in deep-buried tunnels and mines characterized by high in situ stress, the rock vibration is attributed not only to blast loading, but also to dynamic unloading caused by transient release of the in situ stress on excavation faces in the process of rock fragmentation by blasting. Understanding the vibration frequency characteristics under these two excitation sources is of important signification to determine appropriate vibration threshold limits for structure damage in deep-buried opening excavations. With a theoretical model developed for a deep-buried circular tunnel excavation by the millisecond delay blasting sequence, frequency characteristics and their influence factors are investigated and discussed for the vibrations induced by the blast loading, the dynamic unloading and the combined effects, respectively. The results show that the rising time of blast loading, the duration of dynamic unloading and the dimension of excavation boundaries are the main factors that affect the vibration frequency of blasting excavation in highly stressed rock masses. It is found that, the blast loading with a much shorter rising time accentuates higher vibration frequency than the dynamic unloading with a long duration, and it causes the blast loading vibration to be more readily attenuated as the propagation distance increases. Thus, the unloading vibration may become the main vibration component at far distances where its low-frequency vibration may exceed the vibration limits. The vibration induced by the combined effects has two distinctly dominant frequency bands corresponding to the two vibration excitation sources. The frequency analyses of the vibration records from two underground projects excavated by blasting are presented to demonstrate this finding. The findings of this study also clearly reveal that, reducing the dimension of excavation boundaries is one of the most effective means to prevent the vibrational damage to structures as it increases the vibration frequency and meanwhile reduces the peak particle velocity.

Reliability analysis of serviceability performance for an underground cavern using a non-intrusive stochastic method

This paper proposes a non-intrusive stochastic analysis procedure for reliability analysis of the serviceability performance of an underground cavern with an implicit limit state function. This procedure is formulated on the basis of the stochastic response surface method (SRSM) and the deterministic finite element method. First, the SRSM is briefly introduced and implemented through a MATLAB code. Then, the software SIGMA/W is used to perform a deterministic finite element analysis. Next, a link between the MATLAB code and SIGMA/W is developed to automatically pass exchange data between the two platforms. Finally, two examples are presented to illustrate the capacity and validity of the proposed procedure. In the first example, a closed-form limit state function is adopted to validate the SRSM by comparing it with the results obtained from a direct Monte Carlo simulation. In the second example, the serviceability performance of an underground cavern is analyzed to illustrate the capacity of the proposed procedure to handle a reliability problem with an implicit limit state function. The proposed procedure does not require the user to modify the existing deterministic finite element code. The deterministic finite element analysis and the probabilistic analysis are decoupled. This is a major practical advantage because realistic probabilistic analyses are made possible. The SRSM can produce sufficiently accurate reliability results. Furthermore, the method is much more efficient than the direct Monte Carlo simulation. Sensitivity analyses show the effect of the variability of input random variables and the correlation between them on: (1) the probability density functions, (2) the first four order statistical moments, and (3) the probability of failure, which is investigated and discussed.

Assessment of Slope Stability in the Monitoring Parameter Space

AbstractSlope monitoring is routinely conducted, and observational information such as surface/underground displacements, groundwater levels, and rock bolt forces at multiple locations is collected. How to make use of the monitoring information to reveal failure mechanisms and assess the slope stability is a key issue in slope engineering. This paper presents a method for assessing the slope stability by integrating monitoring parameters with physical analysis. The observed information first was used to back analyze the strength and loading parameters, and then the updated basic parameters were used to calculate the factor of safety or failure probability of the slope. The dominant basic parameters whose uncertainties influence the observed results the most were identified from the probabilistic back analysis. Alert levels were defined in the monitoring parameter space on the basis of a factor of safety or failure probability criterion. A rock slope example was worked out to illustrate the application of ...

Numerical simulation of macro-meso mechanical behaviours of sandstone containing a single open fissure under uniaxial compression

Abstract By employing the improved rigid block spring method, the failure process of a sandstone example containing a single open fissure under uniaxial compression is modelled. In this method, the intact rock is considered as an assemblage of rigid polygonal blocks. Macro mechanical behaviours are governed by mechanical properties of interfaces between two neighbouring blocks. In the local scale on interfaces, both tensile splitting failure and shearing sliding failure are considered. Micro properties are obtained by a calibration procedure against the stress–strain curve of intact rock under uniaxial compression in the lab. Influences of fissure inclination and length on the uniaxial compression strength (UCS) and failure modes are discussed. Comparisons between numerical simulations and laboratory tests are presented. The growth process of micro-cracks is studied and the mechanism of micro-crack propagation is studied through analysis on the displacement evolution. Some conclusions are drawn: numerical results generally agree well with those from lab tests; the UCS of fissured rock is lower than the intact one; the UCS first goes down then goes up as inclination increases, but decreases gradually as fissure length increases; the micro failure modes are governed mainly by tensile splitting failures.

Modeling multivariate distributions using Monte Carlo simulation for structural reliability analysis with complex performance function

The simulation of multivariate distributions has not been investigated extensively. This article aims to propose Monte Carlo simulation (MCS)-based procedures for modeling the joint probability distributions and estimating the probabilities of failure of complex performance functions. Two approximate methods, namely method P and method S, often used to construct multivariate distributions with given marginal distributions and covariance, are introduced. The MCS-based procedures are proposed to simulate the theoretical multivariate distributions or approximate multivariate distributions constructed by methods P and S, which are further used to compute the probabilities of failure of complex performance functions. Four illustrative examples with known theoretical joint probability distributions are investigated to examine the accuracy of the proposed procedures in modeling the multivariate distributions and estimating the probabilities of failure. The results indicate that the bivariate distributions can be effectively simulated by the proposed procedures, which can evaluate the reliability of complex performance functions efficiently. These provide a useful tool for solving the reliability problems with complex performance functions involving correlated random variables under incomplete probability information. The performance of the simulation procedures associated with the two approximate methods highly depends on the level of probability of failure, the form of performance function, and the degree of correlation between variables.

Bayesian Updating of Slope Reliability in Undrained Clay with Vane Shear Test Data

In-situ test data, monitoring data and other site-specific information are a common basis for assessing geotechnical performance. These information enable one to learn probabilistic models of uncertain geotechnical properties and update the reliability estimate of geotechnical structures. This learning process is facilitated by the application of Bayesian analysis, which makes optimal use of site-specific information. The objective of this study is to investigate the application of Bayesian analysis to update the probabilistic description of spatially varying soil properties and the reliability of slope stability with in-situ test data. For proper characterization of the prior information on the undrained shear strength s u , a non-stationary random field model is proposed to account for the depth-dependent nature of s u . Bayesian updating for learning the distribution of s u and updating the slope reliability is performed with the adaptive BUS approach with subset simulation. The approach is applied to a saturated clay slope in spatially variable soil. The spatial distribution of the s u is updated with vane shear test data. In addition, the effect of the borehole location on the updated slope reliability is investigated, to inform future optimal test program.

Reliability Analysis of Unsaturated Slope with Spatially Correlated Soil Properties

A non-intrusive stochastic finite element method is proposed for reliability analysis of unsaturated slopes considering the spatial variability of hydraulic parameters and shear strength parameters. The Karhunen-Loeve (KL) expansion technique is employed to discretize cross-correlated lognormal random fields. The factor of slope safety is explicitly expressed as input random parameters using the Hermite polynomial chaos expansion. The Latin hypercube sampling technique is used to calculate the unknown coefficients of polynomial chaos expansion. An example of reliability analysis of an unsaturated slope under the steady-state seepage flow is presented to demonstrate the validity of the proposed method. The results indicate that the proposed method can effectively evaluate the reliability of unsaturated slopes considering spatially varying soil properties. The polynomial chaos expansion combined with the Latin hypercube sampling technique can effectively estimate the probability of slope failure at a relatively low level.

A web-based GPS system for displacement monitoring and failure mechanism analysis of reservoir landslide

It is important to monitor the displacement time series and to explore the failure mechanism of reservoir landslide for early warning. Traditionally, it is a challenge to monitor the landslide displacements real-timely and automatically. Globe Position System (GPS) is considered as the best real-time monitoring technology, however, the accuracies of the landslide displacements monitored by GPS are not assessed effectively. A web-based GPS system is developed to monitor the landslide displacements real-timely and automatically in this study. And the discrete wavelet transform (DWT) is proposed to assess the accuracy of the GPS monitoring displacements. Wangmiao landslide in Three Gorges Reservoir area in China is used as case study. The results show that the web-based GPS system has advantages of high precision, real-time, remote control and automation for landslide monitoring; the Root Mean Square Errors of the monitoring landslide displacements are less than 5 mm. Meanwhile, the results also show that a rapidly falling reservoir water level can trigger the reactivation of Wangmiao landslide. Heavy rainfall is also an important factor, but not a crucial component.

Efficient System Reliability Analysis of Multi-Layered Soil Slopes Using Multiple Stochastic Response Surfaces

This paper aims to propose an efficient approach for evaluating the system reliability of multi-layered soil slopes using representative slip surfaces and multiple stochastic response surfaces (SRSs). First, the representative slip surfaces are identified from a large number of potential slip surfaces. For each representative slip surface, a stochastic response surface using the Hermite polynomial chaos expansion is constructed to estimate its factor of safety (FS). Second, direct Monte-Carlo simulations are performed to compute the system failure probability of the slope, of which the minimum FS for each random sample is calculated using SRSs of representative slip surfaces. Finally, a three-layered clay slope is investigated to demonstrate the effectiveness of the proposed approach. The results indicate that the proposed approach can effectively identify the representative slip surfaces of multi-layered soil slopes and produce accurate system failure probability which is commonly at relatively low levels. In addition, the proposed approach does not need to calculate the correlations between different potential slip surfaces for identification of the representative slip surfaces. The system failure probability of a multi-layered soil slope could be significantly underestimated if only the critical slip surface or insufficient representative slip surfaces are used.