Dynamic reliability analysis of corroded pipeline using Bayesian Network

Nurul Sa aadah Sulaiman*, Henry Tan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
6 Downloads (Pure)


Maintenance and integrity management of hydrocarbons pipelines face the challenges from uncertainties in the data available. This paper demonstrates a way for pipeline remaining service life prediction that integrates structural reliability analysis, accumulated corrosion knowledge, and inspection data on a sound mathematical foundation. Pipeline defects depth grows with time according to an empirical corrosion power law, and this is checked for leakage and rupture probability. The pipeline operating pressure is checked with the degraded failure pressure given by ASME B31G code for rupture likelihood. As corrosion process evolves with time, Dynamic Bayesian Network (DBN) is employed to model the stochastic corrosion deterioration process. From the results obtained, the proposed DBN model for pipeline reliability is advanced compared with other traditional structural reliability method whereby the updating ability brings in more accurate prediction results of structural reliability. The comparisons show that the DBN model can achieve a realistic result similar to the conventional method, Monte Carlo Simulation with very minor discrepancy.

Original languageEnglish
Pages (from-to)210-215
Number of pages6
JournalInternational Journal of Engineering and Technology(UAE)
Issue number4
Publication statusPublished - 1 Dec 2018

Bibliographical note

Funding Information:
The authors would like to express appreciation for the support of the sponsor Universiti Malaysia Pahang Internal Grant [RDU1703169].


  • Bayesian network
  • Corrosion prediction
  • Dynamic reliability
  • Pipeline integrity
  • Reliability analysis


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