An adaptive sampling approach to reduce uncertainty in slope stability analysis

Cai, Jing‐Sen; Yeh, Tian‐Chyi Jim; E, Yan; Tang, Rui-Xuan; Wen, Jet‐Chau; Huang, Shao-Yang

doi:10.1007/s10346-017-0936-2

Cited by 10 publications

(3 citation statements)

References 39 publications

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“…Specifically, cases 1 and 2 focus on the effects of variance in the logarithm of the saturated hydraulic conductivity, σ 2 lnK s ; cases 1, 3, and 4 focus on the effects of the horizontal correlation scale of saturated hydraulic conductivity, λ h ; cases 1 and 5 focus on the effects of the vertical correlation scale, λ v ; and cases 1 and 6 focus on the effects of the one-way time consumption of fluctuations, T. To demonstrate the effectiveness of the probabilistic description method, one realization to each case is generated for cases 1 to 5. These realizations are generated using the Karhunen-Loève (K-L) expansion [22][23][24][25][26][27][28][29]. The spatial distributions of K s fields, phreatic surface (denoted by the black dot dash line), pressure head p (denoted by the white dashed lines with labels), and streamlines (denoted by the black solid line with arrows) of the five cases at t = 3 days are presented in Figure 6.…”

Section: Probabilistically Description Of Layered Structurementioning

confidence: 99%

Groundwater Responses of Foundation Subjected to Water Level Fluctuation of Reservoir Considering Variability of Layered Structure

Tang,

Wen,

Bao

et al. 2023

Water

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The effect of the variability in a layered structure, characterized by the spatial variability of the saturated hydraulic conductivity, on the distribution of a pressure head p in a foundation subjected to water level fluctuation in a reservoir is investigated with the aid of the random field theory, Karhunen–Loève (K-L) expansion, first-order moment approach, and cross-correlation analysis. The results show that the variability in the foundation structure has significant impacts on the groundwater response to the reservoir’s water level fluctuations. Regions with relatively large uncertainties of the p and σp values in the foundation are those around the initial water level at the reservoir side, and those at the distal end away from the reservoir. In addition, there is a larger variance of Ks, denoted as σlnKs2, a larger correlation scale in the horizontal direction λh, a larger correlation scale in the vertical direction λv, and a larger one-way time consumption of fluctuations T to a larger uncertainty in p. Moreover, the four factors (σlnKs2, λh, λv, and T) all have positive correlations with σp. σlnKs2 has the largest impact on σp in the foundation, λv has the second largest impact, and λh has the smallest impact. A foundation with small Ks values around the initial water level at the reservoir side and large Ks values around the highest water level at the reservoir side may produce larger p values in the foundation. These results yield useful insight into the effect of the variability in a layered structure on the distribution of the pressure head in a foundation subjected to water level fluctuation in a reservoir.

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Section: Probabilistically Description Of Layered Structurementioning

confidence: 99%

Groundwater Responses of Foundation Subjected to Water Level Fluctuation of Reservoir Considering Variability of Layered Structure

Tang,

Wen,

Bao

et al. 2023

Water

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“…Tere are many uncertainties in the actual slope engineering, so it is important to study these uncertainties for slope stability. For example, Cai et al [2] proposed an adaptive sampling method based on limit equilibrium model and stochastic condition method in slope stability analysis to reduce the uncertainty. In order to determine the availability of qualitative and quantitative methods for uncertainty analysis in rock slope stability, Abdulai and Sharifzadeh [3] analyzed and summarized the uncertainty and uncertainty analysis methods, problems, and development in geotechnical engineering modeling.…”

Section: Introductionmentioning

confidence: 99%

Stability Evaluation of Slope Based on Global Sensitivity Analysis

Xu,

Wang,

Guo

et al. 2024

Complexity

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The uncertainty of parameters will have a significant impact on slope stability, where sensitivity analysis is a commonly used method in uncertainty research. However, traditional sensitivity analysis method costs much computation time. When calculating the sensitivity index of one parameter, all other parameters are taken as fixed values, and the uncertainty of all parameters cannot be considered simultaneously. Therefore, the variance-based and the moment-independent global sensitivity analysis (GSA) methods are both introduced to determine the influence of geotechnical parameters on slope stability in this study. To solve the importance index of GSA, the least angle regression algorithm, the kernel density estimation, and orthogonal polynomial estimation methods are developed to obtain variance-based importance index and the moment-independent importance index, respectively. The proposed methods allow all variables to change simultaneously within their variation range and have high computational efficiency. The results are in good at with those obtained by the variance-based Monte Carlo simulation method, which is considered as the exact solution forobtaining the importance index. The influence of the correlation between the shear strength parameters (c and φ) on the importance index is also studied, which indicates that the negative correlation will have a great impact on the importance index, which in turn affects the safety assessment of slope. Three engineering cases have been studied for engineering application, and the compared results indicate that the impact of the geotechnical parameters uncertainty on the safety factor (Fs) and failure probability (pf) are different. Therefore, the approaches based on GSA which can integrate the Fs with pf will be a promising approach for slope stability evaluation.

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“…For a slope reliability analysis, many methods are available, such as stochastic finite element method [16,17], response surface method [18], and Monte Carlo method [19]. With the development of computer calculate capability, the Monte Carlo method is increasingly used in the reliability simulation of slope [20][21][22]. Moreover, the influence of variability of loess strength parameters on slope reliability is also studied by some scholars [10,23].…”

Section: Introductionmentioning

confidence: 99%

Distribution Property of Shear Strength Parameters of Q2 and Q3 Loess in Northwest China and Its Application in Reliability Analysis of Natural and Filled Slopes

Wang

Yuan

et al. 2021

Advances in Civil Engineering

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Geological materials have randomness in nature. Statistical analysis can help revealing the variation pattern of the material parameters and the reliability of the slope. In this paper, the probability distribution and variability of shear strength parameters of typical Q2 and Q3 loess in Northwest China were statistically analysed using the collected geological survey data in Yan`an, Shaanxi Province. Resulting probability properties were applied to the reliability analysis for the natural and fill slope in loess area using the Monte Carlo Method. Finally, an optimization analysis was carried out for the fill slope in the background engineering project. Research results show that normal distribution and lognormal distribution can be used to describe the statistical properties of c and φ of Q2 and Q3 loess. Variance of c is large while the variability of φ is relatively small. The influence of the variability of φ on the reliability index of loess natural slope is generally larger than that of c. On the contrary, influence of the variability of c on the reliability index of the fill slope is generally greater than that of φ, which is related to the structural and uniformity of the soil. Finally, relation between slope height and minimum gradient coefficient is linear when the failure probability of fill slope is less than 10%. Results in this study can be used as a reference for the slope design and construction for the cut and fill engineering in loess area.

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An adaptive sampling approach to reduce uncertainty in slope stability analysis

Cited by 10 publications

References 39 publications

Groundwater Responses of Foundation Subjected to Water Level Fluctuation of Reservoir Considering Variability of Layered Structure

Groundwater Responses of Foundation Subjected to Water Level Fluctuation of Reservoir Considering Variability of Layered Structure

Stability Evaluation of Slope Based on Global Sensitivity Analysis

Distribution Property of Shear Strength Parameters of Q2 and Q3 Loess in Northwest China and Its Application in Reliability Analysis of Natural and Filled Slopes

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