Performance of In-Line Inspection Tools and Their Influence on the Structural Reliability of Corroded Pipeline

2006 ◽  
Author(s):  
Jose´ de Jesu´s Leal Carvajalino ◽  
Fa´bio de Castro Marangone ◽  
Jose´ Luiz de Franc¸a Freire
Keyword(s):  
Sequential Analysis ◽  
Structural Reliability ◽  
Field Measurements ◽  
Visual Basic ◽  
Probability Of Failure ◽  
First Order ◽  
Reliability Method ◽  
Minimum Number ◽  
Corrosion Defects ◽  
Reference Tool

This paper presents: i) the assessment of in-line inspection (ILI) tools’ performance in the measurement of defects caused by corrosion; ii) different methods for calculating the probability of failure (POF) of corroded pipeline based on the ILI report. The ILI report is compared to the geometry of defects measured by a reference tool (field measurements) and the errors associated with each measurement system are analyzed and assessed through different statistical methods. The minimum number of field measurements necessary to verify the performance of the ILI in sizing the corrosion defects is determined by implementing a test based on sequential analysis. The POF of a pipeline is calculated using two methods: i) first order reliability method (FORM) and ii) propagation of uncertainties. The comparison between calculated and acceptable POF enables the determining of the next reinspection period. When the calculated POF exceeds the acceptable POF before completing the amount of time desired for the next inspection, the developed procedure enables determining the number of repairs that must be made to reach the desired time when the next ILI will be performed. Finally, a software in Visual Basic® language was developed to implement this work.

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.

System Reliability of Existing Jacket Platform in Malaysian Water (Failure Path and System Reliability Index)

2014 ◽  
Vol 567 ◽  
pp. 307-312 ◽  
Author(s):  
V. John Kurian ◽  
Mohamed Mubarak Abdul Wahab ◽  
T.S. Kheang ◽  
Mohd Shahir Liew
Keyword(s):  
System Reliability ◽  
Reliability Index ◽  
Structural Reliability ◽  
Pushover Analysis ◽  
Probability Of Failure ◽  
Jacket Platform ◽  
First Order ◽  
Failure Path ◽  
Reliability Method ◽  
Two Parameters

The objective of this work is to determine the structural reliability of an existing jacket platform in Malaysia, by determining the system probability of failure and its corresponding reliability index. These two parameters are important indicators for assessing the integrity and reliability of the platform, and will point out whether the platform is suitable for continued operation. In this study, pushover analysis is used to determine possible failure paths of the structure, while First Order Reliability Method (FORM) and Simple Bound Formula are used to determine the failure probability and reliability index. Three failure paths of the platform are established. The reliability index of these paths is found with the highest Reliability Indexto be 18.82 from the 315-degree path, while the system reliability index is 9.23. This illustrates that the platform is robust and the chances of collapse is very small.

Effects of Varying Boundary Conditions on the Buried Pipelines

2006 ◽  
Vol 110 ◽  
pp. 183-192 ◽  
Author(s):  
Ouk Sub Lee ◽  
Dong Hyeok Kim
Keyword(s):  
Boundary Conditions ◽  
Probability Of Failure ◽  
Internal Boundary ◽  
Buried Pipeline ◽  
Buried Pipelines ◽  
Safety Level ◽  
First Order ◽  
Reliability Method ◽  
Margin Of Safety ◽  
Corrosion Defects

In this paper, the FORM (first order reliability method) has been employed to estimate the probability of failure for the buried pipeline degraded by corrosion defects. The estimated results are used to assess the reliability of buried pipeline exposed to varying external and internal boundary conditions corresponding to a required target safety level. Furthermore, the effects of distribution types of random variables affecting the strength of buried pipelines on the probability of failure and the reliability of the buried pipeline are systematically investigated. The plant-engineers should be informed about the margin of safety level of existing pipelines corresponding to the target safety level to assess the integrity of the corroded pipeline under operation.

An accuracy analysis method for first-order reliability method

2018 ◽  
Vol 233 (12) ◽  
pp. 4319-4327 ◽  
Author(s):  
Zhenzhong Chen ◽  
Zihao Wu ◽  
Xiaoke Li ◽  
Ge Chen ◽  
Guangfeng Chen ◽  
...  
Keyword(s):  
Structural Reliability ◽  
Nonlinear Problems ◽  
Accuracy Analysis ◽  
Analysis Method ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Level ◽  
Reliability Method ◽  
Value Range ◽  
Crashworthiness Design

The first-order reliability method is widely used for structural reliability analysis; however, its accuracy would become worse for nonlinear problems. This paper proposes the accuracy analysis method of the first-order reliability method, which considers the worst cases when using the first-order reliability method and gives the possible value range of the probability of safety. The accuracy analysis method can evaluate the reliability level of the first-order reliability method when the failure surfaces are nonlinear. The calculation formula for the possible value range of the probability of safety is proposed, and its trend as the dimensions and reliability rise is also discussed in this paper. A numerical example and a honeycomb crashworthiness design are presented to validate the accuracy of the first-order reliability method, and the results show that they are located within the possible value range proposed in this paper.

Efficient Reliability Assessment With the Conditional Probability Method

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Rami Mansour ◽  
Mårten Olsson
Keyword(s):  
Conditional Probability ◽  
Structural Reliability ◽  
A Priori ◽  
Reliability Assessment ◽  
Probability Of Failure ◽  
Assessment Method ◽  
Probability Method ◽  
Probability Of Survival ◽  
Design Variables ◽  
Reliability Method

Reliability assessment is an important procedure in engineering design in which the probability of failure or equivalently the probability of survival is computed based on appropriate design criteria and model behavior. In this paper, a new approximate and efficient reliability assessment method is proposed: the conditional probability method (CPM). Focus is set on computational efficiency and the proposed method is applied to classical load-strength structural reliability problems. The core of the approach is in the computation of the probability of failure starting from the conditional probability of failure given the load. The number of function evaluations to compute the probability of failure is a priori known to be 3n + 2 in CPM, where n is the number of stochastic design variables excluding the strength. The necessary number of function evaluations for the reliability assessment, which may correspond to expensive computations, is therefore substantially lower in CPM than in the existing structural reliability methods such as the widely used first-order reliability method (FORM).

Analysis of the Partial Safety Factor Method Using Probabilistic Techniques

2010 ◽  
Author(s):  
B. A. Lindley ◽  
P. M. James
Keyword(s):  
Probabilistic Method ◽  
Probability Of Failure ◽  
Safety Factors ◽  
First Order Reliability Method ◽  
First Order ◽  
Target Probability ◽  
Reliability Method ◽  
Input Parameters ◽  
Partial Safety Factors ◽  
Hand Calculation

Partial Safety Factors (PSFs) are scaling factors which are used to modify the input parameters to a deterministic fracture mechanics assessment in order to consider the effects of variability or uncertainty in the values of the input parameters. BS7910 and SINTAP have adopted the technique, both of which use the First Order Reliability Method (FORM) to derive values for PSFs. The PSFs are tabulated, varying with the target probability of failure, p(F), and the Coefficient of Variance (COV) of the variable. An accurate assessment of p(F) requires a probabilistic method with enough simulations. This has previously been found to be time consuming, due to the large number of simulations required. The PSF method has been seen as a quick way of calculating an approximate, conservative value of p(F). This paper contains a review of the PSF method, conducted using an efficient probabilistic method called the Hybrid probabilistic method. The Hybrid probabilistic method is used to find p(F) at a large number of assessment points, for a range of different PSFs. These p(F) values are compared to those obtained using the PSF method. It is found that the PSF method was usually, and often extremely, conservative. However there are also cases where the PSF method was non-conservative. This result is verified by a hand calculation. Modifications to the PSF method are suggested, including the establishment of a minimum PSF on each variable to reduce non-conservatisms. In light of the existence of efficient probabilistic techniques, the non-conservatisms that have been found in the PSF method, coupled with the impracticality of completely removing these non-conservatisms, it is recommended that a full probabilistic assessment should generally be performed.

First-Order Reliability Method for Structural Reliability Analysis in the Presence of Random and Interval Variables

2015 ◽  
Vol 1 (4) ◽  
Author(s):  
Umberto Alibrandi ◽  
C. G. Koh
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Limit State ◽  
Computational Cost ◽  
Computational Effort ◽  
Stochastic Dynamic ◽  
First Order Reliability Method ◽  
First Order ◽  
Structural Reliability Analysis ◽  
Reliability Method

This paper presents a novel procedure based on first-order reliability method (FORM) for structural reliability analysis in the presence of random parameters and interval uncertain parameters. In the proposed formulation, the hybrid problem is reduced to standard reliability problems, where the limit state functions are defined only in terms of the random variables. Monte Carlo simulation (MCS) for hybrid reliability analysis (HRA) is presented, and it is shown that it requires a tremendous computational effort; FORM for HRA is more efficient but still demanding. The computational cost is significantly reduced through a simplified procedure, which gives good approximations of the design points, by requiring only three classical FORMs and one interval analysis (IA), developed herein through an optimization procedure. FORM for HRA and its simplified formulation achieve a much improved efficiency than MCS by several orders of magnitude, and it can thus be applied to real-world engineering problems. Representative examples of stochastic dynamic analysis and performance-based engineering are presented.

Neural network approach to model the limit state surface for reliability analysis

2003 ◽  
Vol 40 (6) ◽  
pp. 1235-1244 ◽  
Author(s):  
Anthony TC Goh ◽  
Fred H Kulhawy
Keyword(s):  
Neural Network ◽  
Reliability Index ◽  
Structural Reliability ◽  
Limit State ◽  
Random Variables ◽  
First Order Reliability Method ◽  
First Order ◽  
The Neural Network ◽  
Reliability Method ◽  
Geotechnical Structures

Structural reliability methods are often used to evaluate the failure performance of geotechnical structures. A common approach is to use the first-order reliability method. Its popularity results from the mathematical simplicity of the method, since only second moment information (mean and coefficient of variation) on the random variables is required. The probability of failure is then assessed by an index known commonly as the reliability index. One critical aspect in determining the reliability index is the explicit definition of the limit state surface of the system. In a problem involving multi-dimensional random variables, the limit state surface is the boundary separating the safe domain from the "failure" (or lack of serviceability) domain. In many complicated and nonlinear problems where the analyses involve the use of numerical procedures such as the finite element method, this surface may be difficult to determine explicitly in terms of the random variables, and therefore the limit state can only be expressed implicitly rather than in a closed-form solution. It is proposed in this paper to use an artificial intelligence technique known as the back-propagation neural network algorithm to model the limit state surface. First, the failure domain is found through repeated point-by-point numerical analyses with different input values. The neural network is then trained on this set of data. Using the optimal weights of the neural network connections, it is possible to develop a mathematical expression relating the input and output variables that approximates the limit state surface. Some examples are given to illustrate the application and accuracy of the proposed approach.Key words: first-order reliability method, geotechnical structures, limit state surface, neural networks, reliability.

Computational Models to Predict the Structural Reliability of Aerospace Systems

2013 ◽  
Author(s):  
Robert G. Tryon ◽  
Animesh Dey ◽  
Richard A. Holmes ◽  
Ganapathi Krishnan
Keyword(s):  
Structural Reliability ◽  
Computational Models ◽  
Probability Of Failure ◽  
Performance Function ◽  
Auxiliary Power Unit ◽  
Auxiliary Power ◽  
Statistical Variation ◽  
Commercial Airline ◽  
Reliability Method ◽  
Turbine Disks

Three case studies are presented in which computational-based methodologies have been used to assess structural reliability in the aerospace industry. The studies involve hot section turbine disks of a helicopter engine, fan blades of a commercial airline engine and bearings in an auxiliary power unit. In all cases, the results of the computational models were used to support the certification process for design and application changes. The statistical variation in design and usage parameters including geometry, materials, speed, temperature and other environmental factors are considered. The response surface approach was used to construct a durability performance function. This performance function is used with the first order reliability method (FORM) to determine the probability of failure and the sensitivity of the failure to the design and usage parameters. A hybrid combination of perturbation analysis and Monte Carlo simulation is used to incorporate time dependent random variables. System reliability is used to determine the system probability of failure, and the sensitivity of the system durability to the design and usage parameters.

Pipeline Remaining Life Estimation Based on Concepts of Structural Reliability and Bayesian Inference

2014 ◽  
Author(s):  
Helio da Cunha Bisaggio ◽  
Theodoro Antoun Netto
Keyword(s):  
Structural Reliability ◽  
Limit State ◽  
Probability Of Failure ◽  
Operational Parameters ◽  
Simple Method ◽  
Life Estimation ◽  
Predicted Probability ◽  
Operational Life ◽  
Corrosion Defects ◽  
State Functions

In this paper, structural reliability concepts are used in conjunction with DNV Recommended Practice RP-F101 [1] formulation to establish the limit state functions of corroded pipes. The model takes into account the natural spread of material properties, geometric and operational parameters, and the uncertainties associated with the sizing of eventual corrosion defects to determine the probability of failure at a given time. Bayesian and reliability concepts are used to estimate the evolution of a pre-defined distribution of defects obtained, for instance, from an inspection campaign. By comparing the predicted probability of failure with the reliability acceptance criteria the operator can schedule defect repairs and establish inspection intervals with more confidence. Thus, a simple method to predict the probability of failure of a corroded pipeline along its operational life is proposed to provide the basis to develop a risk based maintenance strategy.

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