Genetic algorithm search for critical slip surface in multiple-wedge stability analysis

1999 ◽  
Vol 36 (2) ◽  
pp. 382-391 ◽  
Author(s):  
Anthony TC Goh
Keyword(s):  
Genetic Algorithm ◽  
Stability Analysis ◽  
Slope Stability ◽  
Factor Of Safety ◽  
Search Strategy ◽  
Slip Surface ◽  
Pattern Search ◽  
Optimization Techniques ◽  
Thin Layers ◽  
Critical Slip Surface

Most procedures for determining the critical slip surface in slope-stability analysis rely on traditional nonlinear optimization techniques. The main shortcoming of these techniques is the uncertainty as to robustness of the algorithms to locate the global minimum factor of safety rather than the local minimum factor of safety for complicated and nonhomogeneous geological subsoil conditions. This paper describes the incorporation of a genetic algorithm methodology for determining the critical slip surface in multiple-wedge stability analysis. This search strategy is becoming increasingly popular in engineering optimization problems because it has been shown in a wide variety of problems to be suitably robust for the search not to become trapped in local optima. Three examples are presented to demonstrate the effectiveness of the genetic algorithm approach. The search strategy was found to be sufficiently robust to handle layered soils with weak, thin layers, and as efficient and accurate as the conventional pattern search method.Key words: critical slip surface, factor of safety, genetic algorithms, optimization, slope stability, wedge analysis.

An efficient search method for finding the critical circular slip surface using the Monte Carlo technique

2001 ◽  
Vol 38 (5) ◽  
pp. 1081-1089 ◽  
Author(s):  
AI Husein Malkawi ◽  
W F Hassan ◽  
S K Sarma
Keyword(s):  
Monte Carlo ◽  
Stability Analysis ◽  
Slope Stability ◽  
Factor Of Safety ◽  
Global Minimum ◽  
Reliable Method ◽  
Slip Surface ◽  
Search Method ◽  
Monte Carlo Technique ◽  
Critical Slip Surface

Locating the critical slip surface and the associated minimum factor of safety are two complementary parts in a slope stability analysis. A large number of computer programs exist to solve slope stability problems. Most of these programs, however, have used inefficient and unreliable search procedures to locate the global minimum factor of safety. This paper presents an efficient and reliable method to determine the global minimum factor of safety coupled with a modified version of the Monte Carlo technique. Examples are presented to illustrate the reliability of the proposed method.Key words: factor of safety, method of search, critical slip surface, circular, global, Monte Carlo.

Complex Slope Stability Analysis of Slip Surface Stress Method Based on Nader Hypoplastic Model

2011 ◽  
Vol 243-249 ◽  
pp. 2071-2075
Author(s):  
Bao Lin Xiong ◽  
Jin Song Tang ◽  
Chun Jiao Lu
Keyword(s):  
Slope Stability ◽  
Surface Stress ◽  
Factor Of Safety ◽  
Slip Surface ◽  
Strain Analysis ◽  
Search Method ◽  
Pattern Search ◽  
Critical Slip Surface ◽  
Hypoplastic Model ◽  
Pattern Search Method

Hypoplaticity and Nader hypoplastic model are introduced. Based on finite element stress-strain analysis of Nader hypoplastic model, slip surface stress method in the slope stability is provided. The factor of safety of the slip surface is defined as the ratio of the critical shear intensity during failure to real shear stress and the critical slip surface of slope is ascertained with pattern search method. The clay slope with a weak foundation layer and clay slope with a foundation layer including a thin weak layer under the plane strain condition are analyzed. The results are shown that the shapes of critical slip surface and the magnitude of factor of safety are obtained by this method.

A Comparative Study on Locating Critical Slip Surface in 2D and 3D Limit Equilibrium Stability Analysis of Slopes

2012 ◽  
Vol 446-449 ◽  
pp. 1905-1913
Author(s):  
Mo Wen Xie ◽  
Zeng Fu Wang ◽  
Xiang Yu Liu ◽  
Ning Jia
Keyword(s):  
Stability Analysis ◽  
Slope Stability ◽  
Safety Factor ◽  
Slip Surface ◽  
Limit Equilibrium ◽  
Three Dimensional ◽  
Slope Stability Analysis ◽  
Equilibrium Stability ◽  
Critical Slip Surface ◽  
Minimum Safety Factor

The Various methods of optimization or random search have been developed for locating the critical slip surface of a slope and the related minimum safety factor in the limit equilibrium stability analysis of slope. But all these methods are based on a two-dimensional (2D) method and no one had been adapted for a search of the three-dimensional (3D) critical slip surface. In this paper, a new Monte Carlo random simulating method has been proposed to identify the 3D critical slip surface, in which assuming the initial slip to be the lower part of an ellipsoid, the 3D critical slip surface in the 3D slope stability analysis is located by minimizing the 3D safety factor of limit equilibrium approach. Based on the column-based three-dimensional limit equilibrium slope stability analysis models, new Geographic Information Systems (GIS) grid-based 3D deterministic limit equilibrium models are developed to calculate the 3D safety factors. Several practical examples, of obtained minimum safety factor and its critical slip surface by a 2D optimization or random technique, are extended to 3D slope problems to locate the 3D critical slip surface and to compare with the 2D results. The results shows that, comparing with the 2D results, the resulting 3D critical slip surface has no apparent difference only from a cross section, but the associated 3D safety factor is definitely higher.

Search of the Most Dangerous in Slide Slope Stability Analysis Based on Genetic Algorithm

2012 ◽  
Vol 166-169 ◽  
pp. 2535-2538
Author(s):  
Ke Wang ◽  
Chang Ming Wang ◽  
Fang Qi ◽  
Cen Cen Niu
Keyword(s):  
Genetic Algorithm ◽  
Stability Analysis ◽  
Slope Stability ◽  
Slip Surface ◽  
Limit Equilibrium ◽  
Evolutionary Process ◽  
Limit Equilibrium Method ◽  
Slope Stability Analysis ◽  
Equilibrium Method ◽  
The Stability

The traditional limit equilibrium method in the analysis of slope stability not only exists some subjective empirical hypothesis that can not meet the equilibrium of force and moment, but also ignores the effects of internal stress and strain on the slope stability. Furthermore, in the stability of the slope evaluation, limit equilibrium method relies too much on experience when hypothesizing the slope slip surface. So that it makes deviation on slope analysis and stability evaluation. This paper is based on simplified Bishop method used to establish the model of slope stability analysis. And it used genetic algorithms to solve the minimum safety factor and the most dangerous slip surface of slope. It was the arithmetic which simulates organisms genetic evolutionary process and it avoided the traditional methods falling into the local extreme value point easily and error propagation leading to convergence. The algorithm had advantages of higher accuracy, quick convergence and applicability. It showed that the genetic algorithm is accurate and reliable in the analysis of slope stability.

scholarly journals A Genetic Algorithm for Locating the Multiscale Critical Slip Surface in Jointed Rock Mass Slopes

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Qiang Xu ◽  
Jian-yun Chen ◽  
Jing Li ◽  
Hong-yuan Yue
Keyword(s):  
Genetic Algorithm ◽  
Rock Mass ◽  
Stress Field ◽  
Factor Of Safety ◽  
Optimization Problems ◽  
Slip Surface ◽  
Fitness Function ◽  
Jointed Rock ◽  
Jointed Rock Mass ◽  
Critical Slip Surface

The joints have great influence on the strength of jointed rock mass and lead to the multiscale, nonhomogeneous, and anisotropic characteristics. In order to consider these effects, a new model based on a genetic algorithm is proposed for locating the critical slip surface (CSS) in jointed rock mass slope (JRMS) from its stress field. A finite element method (FEM) was employed to analyze the stress field. A method of calculating the mechanical persistence ratio (MPR) was used. The calculated multiscale and anisotropic characteristics of the MPR were used in the fitness function of genetic algorithm (GA) to calculate the factor of safety. The GA was used to solve optimization problems of JRMS stability. Some numerical examples were given. The results show that the multiscale and anisotropic characteristics of the MPR played an important role in locating the CSS in JRMS. The proposed model calculated the CSS and the factor of safety of the slope with satisfactory precision.

A method for locating critical slip surfaces in slope stability analysis

2001 ◽  
Vol 38 (2) ◽  
pp. 328-337 ◽  
Author(s):  
Da-Yong Zhu
Keyword(s):  
Stability Analysis ◽  
Slope Stability ◽  
Factor Of Safety ◽  
High Efficiency ◽  
Slip Surface ◽  
Numerical Procedure ◽  
Slope Stability Analysis ◽  
Case Examples ◽  
Slip Surfaces ◽  
Global And Local

This paper presents a new method for locating critical slip surfaces of general shapes in slope stability analysis. On the basis of the principle of optimality, along with the method of slices, a critical slip field (CSF) in a slope is postulated which consists of a family of slip surfaces having maximum values of unbalanced thrust forces at exit points on the slope face. A numerical procedure is developed for constructing the CSF. The critical slip surface having minimum factor of safety is included in the CSF. All the critical slip surfaces corresponding to all of the exit points are thus determined consecutively, resulting in a global critical slip field (GCSF) which exhibits both global and local slope stability. Comparisons with other methods are made which indicate the high efficiency and accuracy of the proposed approach. Applications of the proposed method to two case examples are given, the results of which demonstrate its applicability to practical engineering.Key words: slope, stability, analysis, factor of safety, critical slip field.

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