An improved particle swarm optimization algorithm with harmony strategy for the location of critical slip surface of slopes

Li, Liang; Chu, Xuesong

doi:10.1007/s13344-011-0030-9

Cited by 33 publications

(10 citation statements)

References 21 publications

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“…They proposed a series of analytical models and systematically analyzed the in°uence mechanism of pore structure characters on the spontaneous imhibition process of wetting°uid into gas-saturated porous media, which have potential application in many science and engineering¯elds. In addition, Xiao et al 4 61 We consider the nanoparticles in suspension to be analogous to pores in fractal porous media. The cumulative number (N) of nanoparticles in nano°uids whose sizes are greater than or equal to i can be expressed according to the fractal scaling law, 29…”

Section: Methodology For the Monte Carlo Techniquementioning

confidence: 99%

Prediction of Convective Heat Transfer of Nanofluids Based on Fractal-Monte Carlo Simulations

Xiao

Jiang

Yang

et al. 2013

Int. J. Mod. Phys. C

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With the consideration of the Brownian motion of nanoparticles in°uids, the probability model for the size of nanoparticles and the model for convective heat transfer of nano°uids are derived based on the fractal character of nanoparticles. The proposed model is expressed as a function of the size of nanoparticles, the volumetric nanoparticle concentration, the thermal conductivity of base°uids, fractal dimension of nanoparticles and the temperature, as well as the random number. It is found that the convective heat°ux of nano°uids decreases with increasing of the average diameter of nanoparticles. This model has the characters of both analytical and numerical solutions. The Monte Carlo simulations combined with the fractal geometry theory are performed. Every parameter of the proposed formula on convective heat transfer of nano°uids has clear physical meaning. So the proposed model can reveal the physical mechanisms of convective heat transfer of nano°uids.

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Section: Methodology For the Monte Carlo Techniquementioning

confidence: 99%

Prediction of Convective Heat Transfer of Nanofluids Based on Fractal-Monte Carlo Simulations

Xiao

Jiang

Yang

et al. 2013

Int. J. Mod. Phys. C

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“…With the increasing complexity, the search algorithm tends to locate the local minimum instead of global minimum (i.e., local minima issue). To properly address the local minima issue, several heuristic optimization algorithms such as improved Harmony search algorithm [43,44] and discontinuous flying particle swarm optimization algorithm [45] have been proposed and used in deterministic slope stability analysis. e local minima issue arises in Slide 5.0 when the path search method with 10,000 potential failure surfaces cannot find the global minimum FS.…”

Section: Ree Numerical Procedures For the Calculation Of Fsmentioning

confidence: 99%

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

Chu

2019

Advances in Civil Engineering

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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.

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“…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

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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An improved particle swarm optimization algorithm with harmony strategy for the location of critical slip surface of slopes

Cited by 33 publications

References 21 publications

Prediction of Convective Heat Transfer of Nanofluids Based on Fractal-Monte Carlo Simulations

Prediction of Convective Heat Transfer of Nanofluids Based on Fractal-Monte Carlo Simulations

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

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

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