Area failure probability method for slope system failure risk assessment

Li, Dianqing; Yang, Zhiyong; Cao, Zhengguo; Zhang, Li Min

doi:10.1016/j.compgeo.2018.11.017

Cited by 31 publications

(13 citation statements)

References 35 publications

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“…As for the proposed method, the failure risk is attributed to a nite number of sources rather than only one source owing to the consideration of whole process of slope failure. When λ is equal to 2 m, the respective frequency corresponding to area of sliding mass interval [2,3], [3,4], [4,5], [5,6], [6,7], [7,8], [8,9], [9,10], [10,11], [11,12], [12,13], [13,14], [14,15], and [15,16] is 0, 43, 72, 61, 26, 19, 4, 0, 1, 0, 0, 0, 0, and 0. When it is compared with the results from the conventional method, the failure risk is deaggregated to 7 sources by the proposed method.…”

Section: Risk Deaggregation Of Slope Failure Risk For Homogeneous Slopementioning

confidence: 99%

“…When it is compared with the results from the conventional method, the failure risk is deaggregated to 7 sources by the proposed method. Besides the area of sliding mass interval [3,4], the slope failure may occur leading to the area of sliding mass within other intervals such as [4,5], [5,6], [6,7], and [7,8]. Accordingly, the risk obtained by the proposed method is 1. slightly about 10.…”

Section: Risk Deaggregation Of Slope Failure Risk For Homogeneous Slopementioning

confidence: 99%

“…e failure probability and the consequence were evaluated based on the critical slip surface with the minimum factor of safety (FS) in most of the previous research [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. Although the area (volume for 3D case) of sliding mass corresponding to the critical slip surface with the minimum FS can serve as an index to quantify the consequence of a slope failure, current studies have shown that the critical slip surface with minimum FS is only an initial location of a slope failure, and it cannot represent the whole process of a slope failure, including not only the initiation stage but also the propagation and the evolution stages [8]. erefore, the use of critical slip surface to determine the consequence is a simple tool, and further studies should be conducted.…”

Section: Introductionmentioning

confidence: 99%

“…Risk assessment of slope failure accounting for both failure probability and the consequences plays a vital role in slope design and risk mitigation [1,2]. Much attention has been focused on the issue of quantitative risk assessment of slope failure [3][4][5][6][7][8][9][10][11]. e failure probability and the consequence were evaluated based on the critical slip surface with the minimum factor of safety (FS) in most of the previous research [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

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Risk Assessment of Slope Failure Using Assumption of Maximum Area of Sliding Mass and Factor of Safety Equal to Unit

Chu

Ming

2019

Advances in Civil Engineering

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This paper aims to develop an effective tool for quantifying the risk of slope failure and identifying the sources of failure risk by combining the limit equilibrium method and the assumption of maximum area of sliding mass with factor of safety = 1. The assumption adopted in this study is firstly validated through the results from the homogeneous slope model, the laboratory experiment, and the smoothed particle hydrodynamics (SPH) program, respectively. Secondly, the proposed method is implemented through the quantification of slope failure risk and the identification of failure sources for a homogeneous slope and a cohesive slope. The conventional method which quantifies the failure risk based on the slip surface with minimum factor of safety (FS) is also performed to enable the comparison with the proposed method. The comparative study has demonstrated that the conventional method tends to underestimate the failure risk due to the negligence of the whole failure process as compared with the proposed method. The failure risk has a tendency to increase as vertical spatial variability of friction angle and Su grow less significant for both proposed method and conventional method. However, the failure sources identified by the conventional method are more likely to decrease as the vertical spatial variability of Su becomes less significant for cohesive slope, whereas the proposed method is able to find a nearly constant number of failure sources by considering the whole process of slope failure. As a result, it is worthwhile to point out that attention is highly recommended to be focused on the failure sources when the spatial variability is less significant, even if it is not considered during the risk mitigation and reinforcing works.

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Section: Risk Deaggregation Of Slope Failure Risk For Homogeneous Slopementioning

confidence: 99%

Section: Risk Deaggregation Of Slope Failure Risk For Homogeneous Slopementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Risk Assessment of Slope Failure Using Assumption of Maximum Area of Sliding Mass and Factor of Safety Equal to Unit

Chu

Ming

2019

Advances in Civil Engineering

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“…The main challenge of applying the above redefined risk assessment methodology is to assess the consequence of individual failure automatically in the simulations. Because the volume of the sliding mass is directly related to the consequence of a landslide, this quantity can be used to quantify consequence (e.g., Li et al 2019). A more complete assessment of the consequence should also quantify the dynamic behaviour of the sliding soil.…”

Section: Quantitative Risk Assessmentmentioning

confidence: 99%

Quantitative Risk Assessment of Individual Landslides

Huang¹,

Griffiths²,

Fenton³

2019

Proceedings of the 7th International Symposium on Geotechnical Safety and Risk (ISGSR 2019)

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Slope failures or landslides are reported every year in different countries. In spite of improvements in landslide hazard recognition, prediction, mitigation measures, and warning systems, worldwide landslide activity is increasing. Uncertainty is a dominant feature of all landslides. Various uncertainties arise during the resolution of the problem, from climate data of rainfall, to infiltration rate, to site characterization, to material properties, to analysis, design and consequence assessment. These variabilities are rarely taken into account directly in traditional geotechnical analysis, rather some "average" or suitably "pessimistic" property is assumed to act across the whole region of interest. This keynote will focus on the modelling of spatial variability of soil properties in the quantitative risk assessment of individual landslides. Firstly, infinite (1D), two dimensional (2D) and three dimensional (3D) slope examples are used to demonstrate the importance of modelling spatial variability in the risk assessment of landslides. The infinite slope example shows that ignoring spatial variability will lead to unconservative estimation of slope failure. The 2D slope example shows that the slope failure can have multiple possible failure modes. The 3D slope example shows that ignoring the spatial variability in the third direction can lead to unconservative estimation of slope failure probability if the slope is long. Then the framework of quantitative risk assessment of landslides is discussed. Slope or landslides can fail shallowly or deeply. Because deep failure leads to more severe consequence than shallow failure, each potential failure mode has a specific consequence associated with it. It is thus necessary to redefine risk as mean consequence rather than assuming a constant consequence for all failure modes. One challenge for quantitative risk assessment of landslides is to automatically identify failure modes and assess associated consequences. This issue can be overcome by introducing Machine Learning algorithms within the framework of Monte Carlo simulations.

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Identification of arbitrarily shaped critical 3D failure surface of a slope based on the sliding direction

Sun,

Yu,

Dong

2023

Num Anal Meth Geomechanics

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The determination of critical failure surface and stability evaluation of 3D slopes have been a hot and difficult problem in geotechnical engineering. The conventional method defines the critical failure surface using the safety factor (SF) whereas it is powerless for some special problems, such as two different failure surfaces with equal SFs. So far, many studies on the critical failure surface of a 3D slope have mainly focused on rotational ellipsoid, while less research has been done on the arbitrary shape. To solve the above problems, we develop a model for constructing a arbitrarily shaped failure surface and ascertain the critical failure surface by the sliding direction (SD). To verify rationality of the introduced theory, the critical failure surfaces of two benchmark symmetric slopes and corresponding SFs are reanalyzed, and the results are compared with the reference solutions. Meanwhile, the results obtained by the proposed method are also consistent with the reference solutions for the complex slope with the asymmetric failure surface. The parametric analysis explores the relationships between the mechanical properties of soil and the SD as well as the SF. Furthermore, influence factors of the spatial characteristics of sliding mass are also revealed. The proposed method is used as a helpful complement to the existing methods.

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Area failure probability method for slope system failure risk assessment

Cited by 31 publications

References 35 publications

Risk Assessment of Slope Failure Using Assumption of Maximum Area of Sliding Mass and Factor of Safety Equal to Unit

Risk Assessment of Slope Failure Using Assumption of Maximum Area of Sliding Mass and Factor of Safety Equal to Unit

Quantitative Risk Assessment of Individual Landslides

Identification of arbitrarily shaped critical 3D failure surface of a slope based on the sliding direction

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