Statistical model and structural reliability analysis for onshore gas transmission pipelines. (December 2017)
- Record Type:
- Journal Article
- Title:
- Statistical model and structural reliability analysis for onshore gas transmission pipelines. (December 2017)
- Main Title:
- Statistical model and structural reliability analysis for onshore gas transmission pipelines
- Authors:
- Pesinis, Konstantinos
Tee, Kong Fah - Abstract:
- Abstract: The reliability of gas pipelines against rupture can be estimated based on historical failure data and theory of structural reliability. In this study, an integrated model for reliability analysis of failure data is presented jointly with a robust structural reliability model for the purpose of comparison and cross-verification. The statistical model adopts a parametric hybrid empirical hazard model complemented with a robust data processing technique known as the nonlinear quantile regression for reliability analysis and prediction. This model provides inferences on the complete lifecycle reliability of the average pipe segment in the region under study. The structural reliability model is segment based and estimates rupture probabilities due to external metal loss corrosion. The non-homogeneous Poisson process is used to model the generation of new defects and the Poisson square wave process is used to model the growth of defects. The internal pressure load is modelled as a discrete Ferry-Borges stochastic process. Then, an inspection and maintenance plan is incorporated based on ASME B31.8S code of practice, for the service life considered. The probability of detection and measurement error of the inspection tools is also incorporated in the model. A numerical example of these models in an industrial context is presented. Onshore gas transmission pipeline rupture data for the period from 2002 to 2014, was obtained from the United States Department ofAbstract: The reliability of gas pipelines against rupture can be estimated based on historical failure data and theory of structural reliability. In this study, an integrated model for reliability analysis of failure data is presented jointly with a robust structural reliability model for the purpose of comparison and cross-verification. The statistical model adopts a parametric hybrid empirical hazard model complemented with a robust data processing technique known as the nonlinear quantile regression for reliability analysis and prediction. This model provides inferences on the complete lifecycle reliability of the average pipe segment in the region under study. The structural reliability model is segment based and estimates rupture probabilities due to external metal loss corrosion. The non-homogeneous Poisson process is used to model the generation of new defects and the Poisson square wave process is used to model the growth of defects. The internal pressure load is modelled as a discrete Ferry-Borges stochastic process. Then, an inspection and maintenance plan is incorporated based on ASME B31.8S code of practice, for the service life considered. The probability of detection and measurement error of the inspection tools is also incorporated in the model. A numerical example of these models in an industrial context is presented. Onshore gas transmission pipeline rupture data for the period from 2002 to 2014, was obtained from the United States Department of Transportation Pipeline and Hazardous Materials Safety Administration (PHMSA) database and analysed. The comparative study of the proposed methodologies can assist gas pipeline operators in the informed implementation of optimal maintenance strategies based on risk prioritization. Highlights: An integrated model for reliability analysis of failure data is presented jointly with a robust structural reliability model. The statistical model adopts a parametric hybrid empirical hazard model complemented with nonlinear quantile regression. The non-homogeneous Poisson process is used to model the generation of new defects. An inspection and maintenance plan is incorporated based on ASME B31.8S code of practice. The probability of detection and measurement error of the inspection tools is also incorporated in the model. … (more)
- Is Part Of:
- Engineering failure analysis. Volume 82(2017)
- Journal:
- Engineering failure analysis
- Issue:
- Volume 82(2017)
- Issue Display:
- Volume 82, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 82
- Issue:
- 2017
- Issue Sort Value:
- 2017-0082-2017-0000
- Page Start:
- 1
- Page End:
- 15
- Publication Date:
- 2017-12
- Subjects:
- Statistical analysis -- Gas pipelines -- Reliability -- External corrosion -- Rupture
System failures (Engineering) -- Periodicals
Fracture mechanics -- Periodicals
Reliability (Engineering) -- Periodicals
Pannes -- Périodiques
Rupture, Mécanique de la -- Périodiques
Fiabilité -- Périodiques
Fracture mechanics
Reliability (Engineering)
System failures (Engineering)
Periodicals
Electronic journals
620.112 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13506307 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.engfailanal.2017.08.008 ↗
- Languages:
- English
- ISSNs:
- 1350-6307
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3760.991000
British Library DSC - BLDSS-3PM
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