Effects of Soil Properties Uncertainty on Reliability Index of Slope

2011 ◽  
Vol 250-253 ◽  
pp. 1947-1950
Author(s):  
Bo Han ◽  
Hong Jian Liao ◽  
Hang Zhou Li ◽  
Zheng Hua Xiao
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Slope Stability ◽  
Soil Properties ◽  
Normal Distribution ◽  
Reliability Index ◽  
Random Variables ◽  
Simulation Method ◽  
Soil Parameters ◽  
Monte Carlo Simulation Method

A probabilistic analysis procedure and related algorithms were based on the Monte Carlo simulation method that considers the variability of soil properties in this paper. A homogenous slope example provide insight into the effects of uncertainty due to the variability of soil properties on slope stability .Taking soil parameters cohesion c, friction angle, gravity γ as the basic random variables, the reliability index are calculated using Monte Carlo simulation method taking into account the uncertainties of these basic random variables. The calculated results are compared for four recognized methods of slope stability, which are Ordinary method, simplified Bishop method, simplified Janbu method and Morgenstern Price method. And the influence of soil parameters’ probability distribution model (i.e. the normal distribution and the log–normal distribution), variation coefficient, mean value, correlation between parameters on the reliability index of slope is discussed. The study shows that different soil properties have different influence degree on the reliability index with regard to the slope reliability analysis.

scholarly journals Applying probabilistic method base on Monte Carlo simulation to analyze slope stability on route Nha Trang - Da Lat (within Khanh Vinh district, Khanh Hoa province)

2014 ◽  
Vol 17 (3) ◽  
pp. 76-85
Author(s):  
Danh Thanh Nguyen ◽  
Ngo Van Dau ◽  
Dung Quoc Ta
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Slope Stability ◽  
Soil Properties ◽  
Reliability Index ◽  
Slope Failure ◽  
Probabilistic Method ◽  
Optimal Designs ◽  
Engineering Practice ◽  
Method Base

In this paper, a Monte Carlo simulation used to analyze probabilistic slope stability. The results including: probabilistic slope failure and reliability index with respect to factor of safety under the effects of uncertainties in the parameters of soil properties. Base on this informations, geotechnical engineers how to get optimal designs to prevent slope failure. In addition, the purpose of this paper is to show that standard deviation of soil properties can be applied in simple ways, without more data, time, or effort than are commonly available in geotechnical engineering practice. Applying Monte Carlo simulation to evaluate probabilistic slope stability on route Nha Trang - Da Lat.

Study on Effect of Neutral Grounding Mode on Reliability of Distribution Network

2012 ◽  
Vol 614-615 ◽  
pp. 719-723 ◽  
Author(s):  
Lei Dong ◽  
Lin He ◽  
Wei Di Li ◽  
Xiao Ao
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Index ◽  
Optimization Problem ◽  
Development Process ◽  
Distribution Network ◽  
Simulation Method ◽  
Monte Carlo Simulation Method ◽  
Cable Lines ◽  
Matlab Programming

There exists an optimization problem of neutral grounding mode in distribution network with a large number of cable lines. In order to choose the best grounding mode for distribution network, factors of effect of neutral grounding mode on reliability of distribution network are analyzed. The development process of distribution line's fault under each neutral grounding mode is simulated with Monte Carlo simulation method by MATLAB programming. At the same time, the reliability index is got to evaluate and compare this effect quantitatively. An example is used to prove this method’s rationality and effectiveness.

scholarly journals Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2885
Author(s):  
Daniel Losada ◽  
Ameena Al-Sumaiti ◽  
Sergio Rivera
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Method ◽  
Electricity Sector ◽  
Cost Functions ◽  
Density Estimator ◽  
Monte Carlo Simulation Method ◽  
Commercial Building ◽  
Complementary Method ◽  
The Cost

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.

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