Reliability Estimation of Buried Pipeline Using FORM, SORM and Monte Carlo Simulation

2006 ◽  
Vol 326-328 ◽  
pp. 597-600 ◽  
Author(s):  
Ouk Sub Lee ◽  
Dong Hyeok Kim
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Exposure Time ◽  
Failure Probability ◽  
Reliability Estimation ◽  
Buried Pipeline ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Method ◽  
The Difference

In this paper, the failure probability is estimated by using the FORM (first order reliability method), the SORM (second order reliability method) and the Monte Carlo simulation to evaluate the reliability of the corroded pipeline. It is found that the FORM technique is more effective in estimating the failure probability than the SORM technique for B31G and MB31G models with three different corrosion models. Furthermore, it is noted that the difference between the results of the FORM, the SORM and the Monte Carlo simulation decreases with the increase of the exposure time.

Reliability of Buried Pipeline Using FORM and Monte Carlo Simulation

2006 ◽  
Vol 321-323 ◽  
pp. 1543-1547 ◽  
Author(s):  
Ouk Sub Lee ◽  
Dong Hyeok Kim
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Failure Probability ◽  
Probabilistic Method ◽  
Reliability Estimation ◽  
Buried Pipeline ◽  
Two Phase ◽  
Surface Corrosion ◽  
Reliability Method ◽  
Power Models

The reliability estimation of pipelines is performed with help of the probabilistic method which considers the uncertainties included in the load and resistance parameters. The FORM (first order reliability method) is carried out to calculate the failure probability of corroded pipeline for the classified six distribution types of random variables. And the reliability of pipelines is assessed by using the failure probability. Furthermore, the MCS (Monte Carlo Simulation) is used to verify the results of the FORM. It is noted that the failure probabilities of the linear and the power models for surface corrosion are similar and those of the two-phase model for surface corrosion are somewhat different for six cases of two failure pressure models such as ASME B31G and MB31G models. And it is also found that the FORM and the MCS give similar results for varying exposure time.

Reliability of Buried Pipeline Using a Theory of Probability of Failure

2006 ◽  
Vol 110 ◽  
pp. 221-230 ◽  
Author(s):  
Ouk Sub Lee ◽  
Dong Hyeok Kim ◽  
Seon Soon Choi
Keyword(s):  
Failure Probability ◽  
Probability Of Failure ◽  
Operating Conditions ◽  
Reliability Estimation ◽  
Design Parameters ◽  
Buried Pipeline ◽  
Safety Level ◽  
First Order ◽  
Reliability Method ◽  
Corrosion Defects

The reliability estimation of buried pipeline with corrosion defects is presented. The reliability of corroded pipeline has been estimated by using a theory of probability of failure. And the reliability has been analyzed in accordance with a target safety level. The probability of failure is calculated using the FORM (first order reliability method). The changes in probability of failure corresponding to three corrosion models and eight failure pressure models are systematically investigated in detail. It is highly suggested that the plant designer should select appropriate operating conditions and design parameters and analyze the reliability of buried pipeline with corrosion defects according to the probability of failure and a required target safety level. The normalized margin is defined and estimated accordingly. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

Determination of Failure Probabilities and Sensitivity Factors Based on First Order Reliability Method

1994 ◽  
Author(s):  
Nataraj Parameswaran ◽  
Lidvin Kjerengtroen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Transfer Problem ◽  
First Order Reliability Method ◽  
First Order ◽  
Advantages And Disadvantages ◽  
Distributed Parameters ◽  
Reliability Method ◽  
Sensitivity Factors ◽  
Failure Probabilities

Abstract Traditionally, most engineering problems are modeled in such a manner that all the variables involved in the design equations are deterministic. By nature, however, seldom does such a phenomenon exist. Most of the variables involved are randomly distributed with a certain mean and standard deviation and follow a certain type of statistical distribution. This investigation compares two such statistical based design processes to evaluate failure probabilities of a one dimensional heat transfer problem with various statistically distributed parameters in its performance function. The methods developed are the Monte Carlo simulation and First Order Reliability Method (FORM). Comparison is made between the Monte Carlo simulation and FORM based upon the investigated problem and the relative advantages and disadvantages of both methods are noted at the end of the investigation. The investigation demonstrates that FORM can be used effectively to determine failure probabilities and sensitivity factors in a manner better than Monte Carlo simulation.

Numerical Simulations of the Rolling of a Ship in a Stochastic Sea: Evaluations by Use of MCS and FORM

2009 ◽  
Author(s):  
Ulrik D. Nielsen ◽  
Jo̸rgen J. Jensen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Numerical Simulations ◽  
Simplified Model ◽  
Probabilistic Assessment ◽  
Parametric Roll ◽  
First Order Reliability Method ◽  
Efficient Approach ◽  
First Order ◽  
Reliability Method

The paper elaborates on the probabilistic assessment of a simplified model for the rolling of a ship in a stochastic seaway. The model can be easily integrated with a probabilistic tool which enables evaluations of numerical simulations by the first order reliability method (FORM) and by Monte Carlo simulation (MCS). Results are presented for synchronous roll as well as parametric roll, where e.g. mean outcrossing rates have been calculated. FORM offers an efficient approach for the computations, although the approach should be applied with care in cases of parametric roll. The paper also touches on issues such as ergodicity and transient versus stationary stages in the roll realisations.

Reliability Estimation of Solder Joint by Using the Failure Probability Models

2006 ◽  
Vol 326-328 ◽  
pp. 621-624 ◽  
Author(s):  
Ouk Sub Lee ◽  
Man Jae Hur ◽  
Jai Sug Hawong ◽  
No Hoon Myoung ◽  
Dong Hyeok Kim
Keyword(s):  
Solder Joint ◽  
Boundary Conditions ◽  
Failure Probability ◽  
Coefficient Of Thermal Expansion ◽  
Bending Moment ◽  
Fatigue Loading ◽  
Reliability Estimation ◽  
Probability Models ◽  
Reliability Method ◽  
The Difference

The differences in the coefficient of thermal expansion (CTE) between the chip and the FR-4 board generate the shear strains and the bending moment in the solder joint. It seems to be a main cause of failure in the solder joint when the chip and the FR-4 board are heated repeatedly. Thus, the fatigue loading induced by thermal cycling is a major concern in the reliability of the solder joint. The magnitude of shear strain and the final failure are known to be influenced by varying boundary conditions such as the difference of CTE, the height of solder, the distance of the solder joint from the neutral point (DNP) and the temperature variation. In this paper, the effects of boundary conditions on the failure probability of the solder joint are studied by using the failure probability models such as the First Order Reliability Method (FORM) and the Monte Carlo Simulation (MCS). Furthermore, the stiffness of the solder joint is considered to investigate the influence at the failure probability.

Improving the first-order structural reliability estimation by Monte Carlo simulation

2017 ◽  
Vol 170 (7) ◽  
pp. 532-540 ◽  
Author(s):  
Mohsen Ali Shayanfar ◽  
Mohammad Ali Barkhordari ◽  
Moien Barkhori ◽  
Mohammad Barkhori
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Structural Reliability ◽  
Reliability Estimation ◽  
First Order
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