Effect of Boundary Conditions of Failure Pressure Models on Reliability Estimation of Buried Pipelines

2004 ◽  
Vol 261-263 ◽  
pp. 803-808
Author(s):  
Ouk Sub Lee ◽  
Jang Sik Pyun ◽  
Si Won Hwang ◽  
Kyoo Sung Cho
Keyword(s):  
Boundary Conditions ◽  
Failure Probability ◽  
Probability Model ◽  
Limit State ◽  
Fluid Pressure ◽  
Taylor Series Expansion ◽  
Reliability Estimation ◽  
State Function ◽  
Buried Pipelines ◽  
Failure Pressure

This paper presents the effect of boundary conditions of various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the help of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure periods with unit of years. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

Effect of Boundary Conditions of Failure Pressure Models on Reliability Estimation of Buried Pipelines

2003 ◽  
Author(s):  
Ouk Sub Lee ◽  
Jang Sik Pyun ◽  
Dong Hyeok Kim
Keyword(s):  
Boundary Conditions ◽  
Failure Probability ◽  
Probability Model ◽  
Limit State ◽  
Fluid Pressure ◽  
Random Variables ◽  
Reliability Estimation ◽  
State Function ◽  
Buried Pipelines ◽  
Failure Pressure

This paper presents the effect of boundary conditions of various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the help of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

Reliability Estimation of Solder Joint Utilizing Thermal Fatigue Models

2005 ◽  
Vol 297-300 ◽  
pp. 1816-1821
Author(s):  
Ouk Sub Lee ◽  
No Hoon Myoung ◽  
Dong Hyeok Kim
Keyword(s):  
Solder Joint ◽  
Thermal Fatigue ◽  
Failure Probability ◽  
Coefficient Of Thermal Expansion ◽  
Probability Model ◽  
Limit State ◽  
Reliability Estimation ◽  
State Function ◽  
First Order ◽  
Reliability Method

The differences of coefficient of thermal expansion (CTE) of component and FR-4 board connected by solder joint generally cause the dissimilarity in shear strain and failure in solder joint when they are heated. The first order Taylor series expansion of the limit state function (LSF) incorporating with thermal fatigue models is used in order to estimate the failure probability of solder joints under heated condition. Various thermal fatigue models, classified into five categories: categories four such as plastic strain-based, creep strain-based, energy-based, and damage-based except stress-based, are utilized in this study. The effects of random variables such as CTE, distance of the solder joint from neutral point (DNP), temperature variation and height of solder on the failure probability of the solder joint are systematically investigated by using a failure probability model with the first order reliability method (FORM) and thermal fatigue models.

Effects of Various Types of Distribution on Probabilistic Method and FAD

2007 ◽  
Vol 353-358 ◽  
pp. 2561-2564
Author(s):  
Ouk Sub Lee ◽  
Dong Hyeok Kim
Keyword(s):  
Failure Probability ◽  
Probabilistic Method ◽  
Limit State ◽  
Random Variables ◽  
Reliability Estimation ◽  
Probabilistic Methods ◽  
State Function ◽  
Operating Pressure ◽  
Lognormal Distributions ◽  
Reliability Method

The reliability estimation of pipeline is performed in accordance with the probabilistic methods such as the FORM (first order reliability method) and the SORM (second order reliability method). A limit state function has been formulated with help of the FAD (failure assessment diagram). Various types of distribution of random variables are assumed to investigate its effect on the failure probability. It is noted that the failure probability increases with the increase of the dent depth, the operating pressure and the outside radius, and the decrease of the wall thickness. Furthermore it is found that the failure probability for the random variables having the Weibull distribution is larger than those of the normal and the lognormal distributions.

Reliability and reliability-based sensitivity analysis of self-centering buckling restrained braces using meta-models

2021 ◽  
pp. 1045389X2110263
Author(s):  
Seyede Vahide Hashemi ◽  
Mahmoud Miri ◽  
Mohsen Rashki ◽  
Sadegh Etedali
Keyword(s):  
Failure Probability ◽  
Limit State ◽  
Computational Cost ◽  
Sensitivity Analyses ◽  
State Function ◽  
Reliability Indices ◽  
Buckling Restrained Brace ◽  
Polynomial Response Surface ◽  
Nonlinear Dynamic Analyses ◽  
High Computational Cost

This paper aims to carry out sensitivity analyses to study how the effect of each design variable on the performance of self-centering buckling restrained brace (SC-BRB) and the corresponding buckling restrained brace (BRB) without shape memory alloy (SMA) rods. Furthermore, the reliability analyses of BRB and SC-BRB are performed in this study. Considering the high computational cost of the simulation methods, three Meta-models including the Kriging, radial basis function (RBF), and polynomial response surface (PRSM) are utilized to construct the surrogate models. For this aim, the nonlinear dynamic analyses are conducted on both BRB and SC-BRB by using OpenSees software. The results showed that the SMA area, SMA length ratio, and BRB core area have the most effect on the failure probability of SC-BRB. It is concluded that Kriging-based Monte Carlo Simulation (MCS) gives the best performance to estimate the limit state function (LSF) of BRB and SC-BRB in the reliability analysis procedures. Considering the effects of changing the maximum cyclic loading on the failure probability computation and comparison of the failure probability for different LSFs, it is also found that the reliability indices of SC-BRB were always higher than the corresponding reliability indices determined for BRB which confirms the performance superiority of SC-BRB than BRB.

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.

Reliability Estimation for PVC Pipe Using Probability Theory and Stress Intensity Factor

2008 ◽  
Author(s):  
O. S. Lee ◽  
D. H. Kim ◽  
H. M. Kim ◽  
H. B. Choi
Keyword(s):  
Stress Intensity Factor ◽  
Stress Intensity ◽  
Intensity Factor ◽  
Wall Thickness ◽  
Failure Probability ◽  
Probabilistic Method ◽  
Reliability Estimation ◽  
State Function ◽  
Operating Pressure ◽  
Reliability Method

In this paper, the reliability estimation of Polyvinyl chloride (PVC) pipelines is performed by utilizing the probabilistic method, which accounts for the uncertainties in the load and resistance parameters in the limit state function (LSF). The LSF is formulated with the help of fracture control concept including the stress intensity factor (SIF) for the pipeline having crack or crack like defects. The common cracks found at pipeline can be assumed as semi-elliptical shape and the main load is hoop stress due to the internal pressure. The FORM (first order reliability method) and the SORM (second order reliability method) are carried out to estimate the failure probability of pipeline utilizing the SIF for semi-elliptical crack. The reliability is assessed using this failure probability. It is found that the failure probability increases with the operating pressure, and the decrease of the pipeline wall thickness, and the increase of the crack depth, the crack length, the outside diameter of pipeline. The failure probability increases when the initial crack approaches to a semi-circle shape of crack and the failure probability steeply increases at the ratios of larger than 0.5 of a/t and larger than 30 of D/t. Moreover, it is recognized that the effects of the fracture toughness and the pipe wall thickness on the failure probability are the significant one.

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.

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.

scholarly journals Reliability Estimation for Highway Bridges

2020 ◽  
Author(s):  
Nafiseh Kiani
Keyword(s):  
Reliability Index ◽  
Structural Reliability ◽  
Limit State ◽  
Highway Bridges ◽  
Reliability Estimation ◽  
State Function ◽  
Limit States ◽  
Resistance Factors ◽  
Load And Resistance Factors ◽  
Reliability Methods

Structural reliability analysis is necessary to predict the uncertainties which may endanger the safety of structures during their lifetime. Structural uncertainties are associated with design, construction and operation stages. In design of structures, different limit states or failure functions are suggested to be considered by design specifications. Load and resistance factors are two essential parameters which have significant impact on evaluating the uncertainties. These load and resistance factors are commonly determined using structural reliability methods. The purpose of this study is to determine the reliability index for a typical highway bridge by considering the maximum moment generated by vehicle live loads on the bridge as a random variable. The limit state function was formulated and reliability index was determined using the First Order Reliability Methods (FORM) method.

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