Probabilistic Modeling and Bayesian Inference of Metalloss Corrosion with Application in Reliability Analysis for Energy Pipelines PDF Download
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Author: Hao Qin
Publisher:
ISBN:
Category :
Languages : en
Pages : 152
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Book Description
The stochastic process-based models are developed to characterize the generation and growth of metal-loss corrosion defects on oil and gas steel pipelines. The generation of corrosion defects over time is characterized by the non-homogenous Poisson process, and the growth of depths of individual defects is modeled by the non-homogenous gamma process (NHGP). The defect generation and growth models are formulated in a hierarchical Bayesian framework, whereby the parameters of the models are evaluated from the in-line inspection (ILI) data through the Bayesian updating by accounting for the probability of detection (POD) and measurement errors associated with the ILI data. The Markov chain Monte Carlo (MCMC) simulation in conjunction with the data augmentation (DA) technique is employed to carry out the Bayesian updating. Numerical examples that involve both the simulated and actual ILI data are used to validate the proposed Bayesian formulation and illustrate the application of the methodology. A simple Monte Carlo simulation-based methodology is further developed to evaluate the time-dependent system reliability of corroding pipelines in terms of three distinctive failure modes, namely small leak, large leak and rupture, by incorporating the corrosion models evaluated from the Bayesian updating methodology. An example that involves three sets of ILI data for a pipe joint in a natural gas pipeline located in Alberta is used to illustrate the proposed methodology. The results of the reliability analysis indicate that ignoring generation of new defects in the reliability analysis leads to underestimations of the probabilities of small leak, large leak and rupture. The generation of new defects has the largest impact on the probability of small leak.
Author: Hao Qin
Publisher:
ISBN:
Category :
Languages : en
Pages : 152
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Book Description
The stochastic process-based models are developed to characterize the generation and growth of metal-loss corrosion defects on oil and gas steel pipelines. The generation of corrosion defects over time is characterized by the non-homogenous Poisson process, and the growth of depths of individual defects is modeled by the non-homogenous gamma process (NHGP). The defect generation and growth models are formulated in a hierarchical Bayesian framework, whereby the parameters of the models are evaluated from the in-line inspection (ILI) data through the Bayesian updating by accounting for the probability of detection (POD) and measurement errors associated with the ILI data. The Markov chain Monte Carlo (MCMC) simulation in conjunction with the data augmentation (DA) technique is employed to carry out the Bayesian updating. Numerical examples that involve both the simulated and actual ILI data are used to validate the proposed Bayesian formulation and illustrate the application of the methodology. A simple Monte Carlo simulation-based methodology is further developed to evaluate the time-dependent system reliability of corroding pipelines in terms of three distinctive failure modes, namely small leak, large leak and rupture, by incorporating the corrosion models evaluated from the Bayesian updating methodology. An example that involves three sets of ILI data for a pipe joint in a natural gas pipeline located in Alberta is used to illustrate the proposed methodology. The results of the reliability analysis indicate that ignoring generation of new defects in the reliability analysis leads to underestimations of the probabilities of small leak, large leak and rupture. The generation of new defects has the largest impact on the probability of small leak.
Author: Rafael Amaya-Gómez
Publisher: Springer Nature
ISBN: 303143532X
Category : Science
Languages : en
Pages : 296
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Book Description
This book provides the most up-to-date, advanced methods and tools for risk assessment of onshore pipelines. These methods and tools are based primarily on information collected from ILI measurements and additional information about the soil surrounding the pipeline. The book provides a better understanding how the defects grow and interact (repulsion or attraction) and their spatial variability. In addition, the authors contemplate new defects that evolve between inspections and how they could affect the pipeline's reliability. A real-world case is presented to reinforce the concepts presented in the book. The book is structured into three parts: i) an introduction to onshore pipelines and the problem of corrosion, ii) a framework that deals with uncertainty for integrity programs for corroded pipelines, and iii) the applications of the methods presented in the book. The book is ideal for researchers and field engineers in oil and gas transportation and graduate and undergraduate engineering students interested in pipeline reliability assessments, spatial variability, and risk-based inspections.
Author: Shenwei Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 448
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Book Description
Metal-loss corrosion is a major threat to the structural integrity and safe operation of underground oil and gas pipelines worldwide. The reliability-based corrosion management program has been increasingly used in the pipeline industry, which typically includes three tasks, namely periodic high-resolution inline inspections (ILIs) to detect and size corrosion defects on a given pipeline, engineering critical assessment of the corrosion defects reported by the inspection tool and mitigation of defects. This study addresses the core involved in the reliability-based corrosion management program. First, the stochastic process in conjunction with the hierarchical Bayesian methodology is used to characterize the growth of defect depth using imperfect ILI data. The biases, random scattering errors as well as the correlations between the random scattering errors associated with the ILI tools are accounted for in the Bayesian inference. The Markov Chain Monte Carlo (MCMC) simulation techniques are employed to carry out the Bayesian updating and numerically evaluate the posterior distributions of the parameters in the growth model. Second, a simulation-based methodology is presented to evaluate the time-dependent system reliability of pressurized energy pipelines containing multiple active metal-loss corrosion defects using the developed growth models. Lastly, a probabilistic investigation is carried out to determine the optimal inspection interval for the newly-built onshore underground natural gas pipelines with respect to external metal-loss corrosion by considering the generation of corrosion defects over time and time-dependent growth of individual defects. The proposed methodology will facilitate the reliability-based corrosion management for corroding pipelines.
Author: Mojtaba Mahmoodian
Publisher: Gulf Professional Publishing
ISBN: 0128135794
Category : Science
Languages : en
Pages : 188
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Book Description
Reliability and Maintainability of In-Service Pipelines helps engineers understand the best structural analysis methods and more accurately predict the life of their pipeline assets. Expanded to cover real case studies from oil and gas, sewer and water pipes, this reference also explains inline inspection and how the practice influences reliability analysis, along with various reliability models beyond the well-known Monte Carlo method. Encompassing both numerical and analytical methods in structural reliability analysis, this book gives engineers a stronger point of reference covering both pipeline maintenance and monitoring techniques in a single resource. - Provides tactics on cost-effective pipeline integrity management decisions and strategy for a variety of different pipes - Presents readers with rational tools for strengthening and rehabing existing pipelines - Teaches how to optimize materials selection and design parameters for designing future pipelines with a longer service life
Author: Mohammad Al-Amin
Publisher:
ISBN:
Category :
Languages : en
Pages : 352
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Book Description
Bayesian models are developed to calibrate the accuracies of high-resolution in-line inspection (ILI) tools for sizing metal-loss corrosion defects and to characterize the growth of individual defects on energy pipelines. Moreover, a methodology is proposed to evaluate the time-dependent system reliability of a segment of a pressurized pipeline containing multiple active corrosion defects. The calibration of ILI tools is carried out by comparing the field-measured depths and ILI-reported depths for a set of static defects. The measurement error associated with the field-measuring tool is found to be negligibly small; therefore, the field-measured depth is assumed to equal the actual depth of the defect. The depth of a corrosion defect reported by an ILI tool is assumed to be a linear function of the corresponding field-measured depth subjected to a random scattering error. The probabilistic characteristics of the intercept and slope in the linear function, i.e. the constant and non-constant biases of the measurement error, as well as the standard deviation of the random scattering error are then quantified using the Bayesian methodology. The proposed methodology is able to calibrate the accuracies of multiple ILI tools simultaneously and quantify the potential correlations between the random scattering errors associated with different ILI tools. The corrosion growth model is developed in a hierarchical Bayesian framework. The depth of the corrosion defects is assumed to be a power-law function of time characterized by two power-law coefficients and the corrosion initiation time, and the probabilistic characteristics of the parameters involved in the growth model are evaluated using Markov Chain Monte Carlo (MCMC) simulation technique based on ILI data iv collected at different times for a given pipeline. The model accounts for the constant and non-constant biases and random scattering errors of the ILI data, as well as the potential correlation between the random scattering errors associated with different ILI tools. The model is validated by comparing the predicted depths with the field-measured depths of two sets of external corrosion defects identified on two in-service natural gas pipelines. A simulation-based methodology is proposed to evaluate the time-dependent system reliability of a segment of a pressurized pipeline containing multiple active metal-loss corrosion defects. The methodology considers three distinctive failure modes, namely small leak, large leak and rupture, and incorporates the hierarchical Bayesian power-law growth model for the depth of individual corrosion defect. Both the conventional Monte Carlo simulation and MCMC simulation techniques are employed in the methodology to evaluate the failure probability. The methodology is illustrated using a joint of an underground natural gas pipeline that is currently in service.
Author: Mohammad Al-Amin
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659203473
Category :
Languages : en
Pages : 200
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Book Description
This book describes the models of calibrating the high-resolution in-line inspection (ILI) tools for sizing metal-loss corrosion defects and to characterize the growth of individual defects on energy pipelines. The models are developed in a Bayesian Framework. The calibration of ILI tools is carried out by comparing the field-measured depths and ILI-reported depths for a set of static defects. And the probabilistic characteristics of the parameters involved in the growth model are evaluated using Markov Chain Monte Carlo (MCMC) simulation technique based on ILI data collected at different times for a given pipeline. Moreover, a methodology is described to evaluate the time-dependent system reliability of a segment of a pressurized pipeline containing multiple active corrosion defects based on ILI data. Both the conventional Monte Carlo simulation and MCMC simulation techniques are employed in the methodology to evaluate the failure probability of the pipeline. The methodology considers three distinctive failure modes, namely small leak, large leak and rupture, and incorporates the hierarchical Bayesian power-law growth model for the depth of individual corrosion defect.
Author: Shenwei Zhang
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659542985
Category :
Languages : en
Pages : 268
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Book Description
Metal-loss corrosion is a major threat to the structural integrity and safe operation of underground oil and gas pipelines worldwide. The reliability-based corrosion management program has been increasingly used in the pipeline industry, which typically includes three tasks, namely periodic high-resolution inline inspections to detect and size corrosion defects on a given pipeline, engineering critical assessment of corrosion defects reported by the inspection tool and mitigation of defects. The work reported in this book addresses the engineering challenges involved in the reliability-based corrosion management program, including the probabilistic corrosion growth modeling based on imperfect inspection data, time-dependent reliability evaluation, and optimal inspection interval determination for corroding pipelines.
Author: Narasi Sridhar
Publisher: Springer
ISBN: 9783031561276
Category : Science
Languages : en
Pages : 0
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Book Description
This book represents a compilation of experience from a slate of experts involved in developing and deploying Bayesian Networks (BN) for corrosion management. The contributors describe how probability distributions can be developed for corroding systems and BN can be applied as an ideal framework to deal with corrosion risk. Corrosion can develop suddenly and grow rapidly after a long incubation period and take many non-uniform aspects, including pitting and stress corrosion cracking, that cannot be mitigated by simply bulking up the system. They also describe how complex engineering structures and systems are influenced by many natural and engineering factors that come together in myriad ways. It provides a broad perspective to the reader on the potential of BN as an artificial intelligence tool for corrosion risk management and the challenges for implementing it.
Author: Reza Javaherdashti
Publisher: Springer Nature
ISBN: 3031603583
Category :
Languages : en
Pages : 239
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Book Description
Author: Zahiraniza Mustaffa
Publisher: LAP Lambert Academic Publishing
ISBN: 9783847316947
Category :
Languages : en
Pages : 212
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Book Description
'System Reliability Assessment of Offshore Pipelines' portrays the application of probabilistic methods in assessing the reliability of these structures subjected to corrosion. The analysis interprets corrosion data as random variables and probabilistic functions, through which uncertainties of corrosion inspection tool can be taken into account. The reliability of the pipeline is studied by treating the structure as an independent unit. The analysis is further elaborated for pipelines arrayed as a series system of units, with the consideration of length effects. A framework for the reliability-based maintenance model is also developed, aiming at optimizing the pipeline system operations. Herein, the analysis is mainly focused on improving the practice of releasing corrosion inhibitors into the pipeline. The use of inhibitors is considered to be the most applied maintenance practice among pipeline industries because of its simple mechanism to fight against corrosion. Last but not least, the research also looks into interpreting corrosion in space using theories on hydrodynamics.
