Decision Making for Long-Term Pipeline System Repair or Replacement
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 4, Issue 2
Abstract
Corrosion is one of the main causes of pipeline failure, which can have large social, economic, and environmental consequences. To mitigate this risk, pipeline operators perform regular inspections and repairs. The results of the inspections aid decision makers in determining the optimal maintenance strategy. However, there are many possible maintenance strategies, and a large degree of uncertainty, leading to difficult decision making. This paper develops a framework to inform the decision of whether it is better over the long term to continuously repair defects as they become critical or to just replace entire segments of the pipeline. The method uses a probabilistic analysis to determine the expected number of failures for each pipeline segment. The expected number of failures informs the optimal decision. The proposed framework is tailored toward mass amounts of in-line inspection data and multiple pipeline segments. A numerical example of a corroding upstream pipeline illustrates the method.
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Acknowledgments
The authors are grateful for funding support from the NSERC PGS-D scholarship, the Queen Elizabeth II Graduate Scholarship, and the Dr. Mo Mohitpour Graduate Scholarship in Pipeline Engineering.
References
ASME. (1991). “Manual for determining the remaining strength of corroded pipelines.” ASME B31G-1991, New York.
ASME. (2012). “Pipeline transportation systems for liquids and slurries.” ASME B31.4-2012, New York.
Brazán, F. A. V., and Beck, A. T. (2013). “Stochastic growth models for pipeline reliability.” Corros. Sci., 74, 50–58.
CSA (Canadian Standards Association). (2012). “Oil and gas pipeline systems.” CAN/CSA-Z662-11, Etobicoke, ON, Canada.
Dann, M. R., and Maes, M. A. (2015a). “Population-based approach to estimate corrosion growth in pipelines.” Proc., 12th Int. Conf. on Applications of Statistics and Probability in Civil Engineering, Civil Engineering Risk and Reliability Association, San Francisco.
Dann, M. R., and Maes, M. A. (2015b). “Probabilistic mass ILI data analysis using a population-based approach.” Rio Pipeline Conf., Rio de Janeiro, Brazil.
de Jonge, B., Klingenberg, W., Teunter, R., and Tinga, T. (2015). “Optimum maintenance strategy under uncertainty in the lifetime distribution.” Reliab. Eng. Syst. Saf., 133, 59–67.
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubi, D. B. (2014). Bayesian data analysis, 3rd Ed., CRC Press, Boca Raton, FL.
Gomes, W. J. S., and Beck, A. T. (2014). “Optimal inspection and design of onshore pipelines under external corrosion process.” Struct. Saf., 47, 48–58.
Gomes, W. J. S., Beck, A. T., and Haukaas, T. (2013). “Optimal inspection planning for onshore pipelines subject to external corrosion.” Reliab. Eng. Syst. Saf., 118, 18–27.
Hellevik, S. G., Langen, I., and Sørensen, J. D. (1999). “Cost optimal reliability based inspection and replacement planning of piping subjected to corrosion.” Int. J. Press. Vessels Pip., 76(8), 527–538.
Hong, H. P. (1997). “Reliability based optimal inspection and maintenance for pipeline under corrosion.” Civil Eng. Syst., 14(4), 313–334.
Hong, H. P. (1999). “Inspection and maintenance planning of pipeline under external corrosion considering generation of new defects.” Struct. Saf., 21(3), 203–222.
JCSS (Joint Committee on Structural Safety). (2008). Risk assessment in engineering: Principles, system representation & risk criteria, M. H. Faber, ed., Technical Univ. of Denmark, Lyngby, Denmark.
Kahn, F. I., and Haddara, M. M. (2003). “Risk-based maintenance (RBM): A quantitative approach for maintenance/inspection scheduling and planning.” J. Loss Prevent. Process Ind., 16(6), 561–573.
Koller, D., and Friedman, N. (2009). Probabilistic graphical models: Principles and techniques, MIT Press, Cambridge, MA.
Leira, B. J., Naess, A., and Naess, O. E. B. (2016). “Reliability analysis of corroding pipelines by enhanced Monte Carlo simulation.” Int. J. Press. Vessels Pip., 144, 11–17.
Luce, R. D., and Raiffa, H. (1957). Games and decisions, Wiley, New York.
Nessim, M. A., Stephens, M. J., and Zimmerman, T. J. E. (2000). “Risk-based maintenance planning for offshore pipelines.” Proc., Offshore Technology Conf., Vol. 2, Offshore Technology Conference, Houston.
Pandey, M. D. (1998). “Probabilistic models for condition assessment of oil and gas pipelines.” NDT & E Int., 31(5), 349–358.
Pandey, M. D., and Van Noortwijk, J. M. (2004). “Gamma process model for time-dependent structural reliability analysis.” Proc., 2nd Int. Conf. on Bridge Maintenance, Safety, and Management, CRC Press, London.
Pandey, M. D., Yuan, X. X., and van Noortwijk, J. M. (2009). “The influence of temporal uncertainty of deterioration on life-cycle management of structures.” Struct. Infrastruct. Eng., 5(2), 145–156.
POF (Pipeline Operators Forum). (2009). “Specifications and requirements for intelligent pig inspection of pipelines.” ⟨https://www.pipelineoperators.org/⟩ (Feb. 18, 2016).
Sahraoui, Y., Khelif, R., and Chateauneuf, A. (2013). “Maintenance planning under imperfect inspections of corroded pipelines.” Int. J. Press. Vessels Pip., 104, 76–82.
van Noortwijk, J. M. (2009). “A survey of the application of gamma processes in maintenance.” Reliab. Eng. Syst. Saf., 94(1), 2–21.
Von Neumann, J., and Morgenstern, O. (1947). Theory of games and economical behaviour, 2nd Ed., Princeton University Press, Princeton, NJ.
Xu, Z. (2015). Uncertain multi-attribute decision making: Methods and applications, Springer, Berlin.
Zhang, S., and Zhou, W. (2014). “Cost-based optimal maintenance decisions for corroding natural gas pipelines based on stochastic degradation models.” Eng. Struct., 74, 74–85.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 4 • Issue 2 • June 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: May 19, 2016
Accepted: Oct 17, 2017
Published online: Feb 9, 2018
Published in print: Jun 1, 2018
Discussion open until: Jul 9, 2018
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