Dynamic reliability analysis for residual life assessment of corroded subsea pipelines

ABSTRACT

Failure threats in subsea pipelines are hard to inspect, but parameters influencing them are easier to observe. Hence, nowadays, Bayesian network models became more relevant, as the model can be updated with the sparse observations while considering the underlying uncertainty. This holds for failure threat assessment of subsea pipelines, specifically for a highly random corrosion mechanism, which has not been captured in the current traditional assessments appropriately. However, a number of researchers stated that it is difficult to build the Conditional Probability Table (CPT) of the Bayesian networks. In such cases, it has been suggested to employ expert knowledge to determine the conditional probability distributions, which involves some uncertainties and high data deviation. This paper focusses on developing a dynamic Bayesian network-based framework to minimise the inputs from the expert domain in the CPT development, while providing an efficient option to analyse the pipeline residual life due to corrosion threat.

KEYWORDS:

• Bayesian network
• subsea pipelines
• dynamic reliability
• life extension

Acknowledgements

The authors would like to acknowledge the support from Arliansyah Abdul Gani, Tri Agusman and Natalie Sukma Dewi for their constructive inputs that enabled the completion of this research study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

ORCID

Reza Aulia http://orcid.org/0000-0002-4452-2631

Additional information

Funding

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