Structural reliability of corroded pipeline using the so-called Separable Monte Carlo method

2018 ◽  
Vol 53 (8) ◽  
pp. 730-737 ◽  
Author(s):  
Mohamed el Amine Ben Seghier ◽  
Mourad Bettayeb ◽  
José Correia ◽  
Abílio De Jesus ◽  
Rui Calçada
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Structural Reliability ◽  
Computational Cost ◽  
Simulation Method ◽  
Computational Method ◽  
Time Dependent ◽  
Monte Carlo Simulation Method ◽  
Corrosion Defects ◽  
Separable Monte Carlo

The evaluation of the failure probability of corroded pipelines is an important calculation to quantify the risk assessment and integrity of pipelines. Traditional Monte Carlo simulation method has been widely used to solve this type of problems, where it generates a very large number of simulations and takes longer time in computing. In this study, enhanced computational method called Separable Monte Carlo is employed to evaluate the time-dependent reliability of pipeline segments containing active corrosion defects, where a practical example was used. The results show that the Separable Monte Carlo simulation method not only minimizes the computational cost strongly but also improves the calculation precision.

Local Monte Carlo Simulation for the Reliability Sensitivity Analysis

2011 ◽  
Vol 291-294 ◽  
pp. 2183-2188 ◽  
Author(s):  
Da Wei Li ◽  
Zhen Zhou Lu ◽  
Zhang Chun Tang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Numerical Technique ◽  
Limit State ◽  
Computational Cost ◽  
Simulation Method ◽  
State Function ◽  
Local Domain ◽  
Monte Carlo Simulation Method ◽  
Reliability Sensitivity

An efficient numerical technique, namely the Local Monte Carlo Simulation method, is presented to assess the reliability sensitivity in this paper. Firstly some samples are obtained by the random sampling, then the local domain with a constant probability content corresponding to each sample point can be defined, finally the conditional reliability and reliability sensitivity corresponding to every local region can be calculated by using linear approximation of the limit state function. The reliability and reliability sensitivity can be estimated by the expectation of all the conditional reliability and reliability sensitivity. Three examples testify the applicability, validity and accuracy of the proposed method. The results computed by the Local Monte Carlo Simulation method and the Monte Carlo method are compared, which demonstrates that, without losing precision, the computational cost by the former method is much less than the later.

scholarly journals Overview of Calculation Methods of Structural Time-Dependent Reliability

2022 ◽  
Vol 2148 (1) ◽  
pp. 012063
Author(s):  
Lisheng Luo ◽  
Xinran Xie ◽  
Yongqiang Zhang ◽  
Wenyuan He
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Method ◽  
Safety Performance ◽  
Time Dependent ◽  
Structural Performance ◽  
Monte Carlo Simulation Method ◽  
Calculation Methods ◽  
New Methods ◽  
Reliability Method

Abstract Under the action of natural erosion, the strength, durability and other safety performance of structures and elements gradually decrease with time, which has a great impact. To solve the above problem, a series of time-dependent reliability analysis methods were proposed. Based on different structural performance functions, this paper analyzes and discusses different time-dependent reliability theories, including outcrossing-based reliability method, Monte Carlo simulation method, extremum method and other new methods proposed in recent years, which provides reference for later research.

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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