Discontinuous flying particle swarm optimization algorithm and its application to slope stability analysis

Advances in Civil Engineering

2019

Self Cite

This paper aims to investigate the differences in factor of safety (FS) and failure mechanism (FM) for spatially variable undrained soil slope between using finite element method (FEM) , finite difference method (FDM), and limit equilibrium method (LEM). The undrained shear strength of cohesive soil slope is modeled by a one-dimensional random field in the vertical direction. The FS and FM for a specific realization of random field are determined by SRT embedded in FEM- and FDM-based software (e.g., Phase2 6.0 and FLAC) and LEM, respectively. The comparative study has demonstrated that the bishop method (with circular failure surface) exhibits performance as fairly good as that of SRT both in FS and FM for the undrained slope cases where no preferable controlling surfaces such as hydraulic tension crack and inclined weak seams dominate the failure mechanism. It is, however, worthwhile to point out that unconservative FM is provided by the Bishop method from the aspect of failure consequence (i.e., the failure consequence indicated by the FM from the Bishop method is smaller than that from SRT). The rigorous LEM (e.g., M-P and Spencer method with noncircular failure surface) is not recommended in the stability analysis of spatially variable soil slopes before the local minima and failure to converge issues are fully addressed. The SRT in combination with FEM and/or FDM provides a rigorous and powerful tool and is highly preferable for slope reliability of spatially variable undrained slope.

Section: Ree Numerical Procedures For the Calculation Of Fsmentioning

confidence: 99%

Failure Mechanism and Factor of Safety for Spatially Variable Undrained Soil Slope

Advances in Civil Engineering

2019

Self Cite

“…An in-house Fortran-based software package for deterministic slope stability analysis has been developed and used successfully in previous studies (Li et al, 2010;Chu, 2011, 2014;Li et al, 2013aLi et al, , 2013b. The software package is equipped with HS algorithm and particle swarm optimization algorithm for efficient location of the deterministic critical slip surface.…”

Section: Software Package For Deterministic Stability Analysismentioning

confidence: 99%

Comparative study on response surfaces for reliability analysis of spatially variable soil slope

2015

China Ocean Eng

Self Cite

This paper focuses on the performance of the second-order polynomial-based response surfaces on the reliability of spatially variable soil slope. A single response surface constructed to approximate the slope system failure performance function G(X) (called single RS) and multiple response surfaces constructed on finite number of slip surfaces (called multiple RS) are developed, respectively. Single RS and multiple RS are applied to evaluate the system failure probability p f for a cohesive soil slope together with Monte Carlo simulation (MCS). It is found that p f calculated by single RS deviates significantly from that obtained by searching a large number of potential slip surfaces, and this deviation becomes insignificant with the decrease of the number of random variables or the increase of the scale of fluctuation. In other words, single RS cannot approximate G(X) with reasonable accuracy. The value of p f from multiple response surfaces fits well with that obtained by searching a large number of potential slip surfaces. That is, multiple RS can estimate G(X) with reasonable accuracy.

“…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]. 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].…”

Section: Introductionmentioning

confidence: 99%

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

Advances in Civil Engineering

Ming

2019

Self Cite

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.