Reliability Analysis of Embankment Slope in Yaan-Luku Expressway

2011 ◽  
Vol 71-78 ◽  
pp. 1360-1365
Author(s):  
Jian Quan Ma ◽  
Guang Jie Li ◽  
Shi Bo Li ◽  
Pei Hua Xu
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Reliability Analysis ◽  
Failure Probability ◽  
Latin Hypercube Sampling ◽  
Natural State ◽  
State Function ◽  
Embankment Slope ◽  
The Times ◽  
Distribution Type

Take a typical cross-section of rockfill embankment slope in Yaan-Luku highway as the research object, reliability analysis is studied under the condition of water table of 840.85m, 851.50m, and loading condition of natural state and horizontal seismic acceleration of 0.2g, respectively. Raw data use Kolmogorov-Smirnov test (K-S test) to determine the distribution type of parametric variation. And the parameters were sampling with Latin hypercube sampling (LHS) method and Monte Carlo (MC) method, respectively, to obtain state function and determine safety factors and reliability indexes. A conclusion is drawn that the times of simulation based on LHS method were less than Monte Carlo method. Also the convergence of failure probability is better than the Monte Carlo method. The safety factor is greater than one and the failure probability has reached to 35.45% in condition of earthquake, which indicating that the instability of rockfill embankment slope is still possible.

The Reliability Analysis for Coastal Structure Based on Monte Carlo Method

2008 ◽  
Author(s):  
Yam Huang ◽  
Honda Shi ◽  
Wei Wang ◽  
Yong Fan
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Reliability Analysis ◽  
Failure Probability ◽  
Mathematical Analysis ◽  
Yellow Sea ◽  
Calculation Model ◽  
Coastal Structure ◽  
The Monte Carlo Method ◽  
Deterministic Methods

The Monte Carlo method is often a favorite selection to estimate the reliability of structure since it involves no complex mathematical analysis, especially when systems are so complex or large that deterministic methods are difficult. In this paper, Monte Carlo method is used to analyse the failure probability of a gravity wharf in Yellow Sea. In addition, in view of the uncertainty exited in calculation model or other aspects, the sensitivity of failure probability is calculated.

The Application of Artificial BP Neural Networks and Monte-Carlo Method for the Reliability Analysis on Frame Structure

2012 ◽  
Vol 204-208 ◽  
pp. 3256-3259 ◽  
Author(s):  
Zhi Cheng Xue ◽  
Hai Jun Wang
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Reliability Analysis ◽  
Limit State ◽  
Frame Structure ◽  
State Function ◽  
Range Data ◽  
Limit State Function ◽  
The Monte Carlo Method ◽  
Wide Range

In order to conduct the reliability analysis of frame structure, the limit state function was first fitted by artificial BP neural network. Then considering the orthogonal array method, sample data was arranged. After that an improved network modes was trained for the probabilistic analysis on a wide range data with the Monte-Carlo method. The mean and standard deviation for the limit state function was easily obtained and the reliability index on the structure can be also calculated. Finally, the example indicated that this method used in the reliability analysis for frame structure was feasible.

An Improved FOSM Method for Calculating the Failure Probability of Welded Pipes with Cracks

2004 ◽  
Vol 261-263 ◽  
pp. 561-566
Author(s):  
Li Xing Huo ◽  
Min Liu ◽  
You Feng Zhang ◽  
Fang Juan Qi
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Failure Probability ◽  
Safety Assessment ◽  
Linear Expansion ◽  
Failure Function ◽  
The Monte Carlo Method

To increase the accuracy of R-F method, it is necessary to solve the problems of the linear expansion of failure function and non-normal variables. In this paper, the improved FOSM method was applied to calculate the failure probability of welded pipes with cracks. The examples show that this method is simple, efficient and accurate for reliability safety assessment of welded pipes with cracks. It can save more time than the Monte Carlo method does, so that the improved FOSM method is recommended for general engineering reliability safety assessment of welded pipes with cracks.

scholarly journals Gaussian Process-Based Response Surface Method for Slope Reliability Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Bin Hu ◽  
Guo-shao Su ◽  
Jianqing Jiang ◽  
Yilong Xiao
Keyword(s):  
Gaussian Process ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Failure Probability ◽  
Limit State ◽  
State Function ◽  
Limit State Function ◽  
Surface Method ◽  
Gp Model

A new response surface method (RSM) for slope reliability analysis was proposed based on Gaussian process (GP) machine learning technology. The method involves the approximation of limit state function by the trained GP model and estimation of failure probability using the first-order reliability method (FORM). A small amount of training samples were firstly built by the limited equilibrium method for training the GP model. Then, the implicit limit state function of slope was approximated by the trained GP model. Thus, the implicit limit state function and its derivatives for slope stability analysis were approximated by the GP model with the explicit formulation. Furthermore, an iterative algorithm was presented to improve the precision of approximation of the limit state function at the region near the design point which contributes significantly to the failure probability. Results of four case studies including one nonslope and three slope problems indicate that the proposed method is more efficient to achieve reasonable accuracy for slope reliability analysis than the traditional RSM.

Failure probability estimation of steam turbine blades by enhanced Monte Carlo Method

2015 ◽  
Vol 56 ◽  
pp. 80-88 ◽  
Author(s):  
J.A. Rodríguez ◽  
J.C. Garcia ◽  
E. Alonso ◽  
Y. El Hamzaoui ◽  
J.M. Rodríguez ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Steam Turbine ◽  
Failure Probability ◽  
Turbine Blades ◽  
Probability Estimation ◽  
Steam Turbine Blades

Improved Line Sampling Reliability Analysis Method and its Application

2007 ◽  
Vol 353-358 ◽  
pp. 1001-1004 ◽  
Author(s):  
Shu Fang Song ◽  
Zhen Zhou Lu
Keyword(s):  
Markov Chain ◽  
Reliability Analysis ◽  
Failure Probability ◽  
Low Cycle Fatigue ◽  
Limit State ◽  
Computational Cost ◽  
State Function ◽  
Line Sampling ◽  
Failure Region ◽  
Important Direction

For reliability analysis of implicit limit state function, an improved line sampling method is presented on the basis of sample simulation in failure region. In the presented method, Markov Chain is employed to simulate the samples located at failure region, and the important direction of line sampling is obtained from these simulated samples. Simultaneously, the simulated samples can be used as the samples for line sampling to evaluate the failure probability. Since the Markov Chain samples are recycled for both determination of the important direction and calculation of the failure probability, the computational cost of the line sampling is reduced greatly. The practical application in reliability analysis for low cycle fatigue life of an aeronautical engine turbine disc structure under 0-takeoff-0 cycle load shows that the presented method is rational and feasible.

Reliability Analysis on Yuwangbian Slop Based on Monte-Carlo Simulation

2011 ◽  
Vol 250-253 ◽  
pp. 3934-3940
Author(s):  
Yi Fang Feng ◽  
Hua Zhi Zhang ◽  
Yu Wang ◽  
Qing Jun Zuo
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Reliability Analysis ◽  
Working Condition ◽  
Actual Condition ◽  
Stability Factor ◽  
Analysis Method ◽  
Loess Slope ◽  
The Monte Carlo Method ◽  
The Stability

Based on the Yuwangbian high loess slope, which is located in Xi'an Yanta District, the basic principle of Monte-Carlo method is presented. By means of geotechnical engineering and geotechnical environment emulation software Geostudio-slope/w and based on Morgenstern-Price slope stability analysis method, the reliability and stability of the slope are analyzed under different kinds of working condition. The stability factor, reliability index and failure probability under the corresponding working conditions has been obtained. The results coincide with the actual condition, which makes the Geostudio software combine with the Monte-Carlo method and provides reference for the reliability analysis of loess slope.

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