Prediction of Corroded Pipeline Performance Based on Dynamic Reliability Models

Reza Aulia* (Corresponding Author), Henry Tan, Srinivas Sriramula

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

10 Citations (Scopus)
26 Downloads (Pure)


This paper focusses on developing an initial model for dynamic reliability analysis to predict the aging pipeline performance due to corrosion. The corrosion failure mechanism and the associated data requirements are identified by combining outputs from the literature and project experiences. Bayesian networks (BN) are developed to manage and overcome data uncertainties and the dynamic consideration is utilized to introduce time function into the model to accommodate the time-dependent variables. Several parameters are considered in the model development, such as pipeline content, size and material grade, environmental conditions, operational conditions, internal and external corrosion rates mitigation methods and in-line inspection data on corrosion rates. The application of the proposed model to an industrial case study is presented in this paper, along with the basic event prioritization analysis using the sensitivity approach. The proposed dynamic Bayesian model provides an efficient option for reliability assessment, to predict the future condition of the corroded pipeline based on the current and historical data, leading to rational risk assessment.

Original languageEnglish
Pages (from-to)518-523
Number of pages6
JournalProcedia CIRP
Early online date4 May 2019
Publication statusPublished - 2019
Event26th CIRP Conference on Life Cycle Engineering, LCE 2019 - West Lafayette, United States
Duration: 7 May 20199 May 2019

Bibliographical note

This research is sponsored by the Ministry of Finance of the Republic of Indonesia through the Indonesia Endowment Fund for Education (LPDP)(grant number: PRJ-4202 /LPDP.3/2016).


  • Bayesian network
  • Life extension
  • Reliability analysis
  • Subsea pipeline


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