Reliability analysis and optimisation of subsea compression system facing operational covariate stresses

Ikenna Anthony Okaro, Longbin Tao

Research output: Contribution to journalArticle

13 Citations (Scopus)
272 Downloads (Pure)

Abstract

This paper proposes an enhanced Weibull-Corrosion Covariate model for reliability assessment of a system facing operational stresses. The newly developed model is applied to a Subsea Gas Compression System planned for offshore West Africa to predict its reliability index. System technical failure was modelled by developing a Weibull failure model incorporating a physically tested corrosion profile as stress in order to quantify the survival rate of the system under additional operational covariates including marine pH, temperature and pressure. Using Reliability Block Diagrams and enhanced Fusell-Vesely formulations, the whole system was systematically decomposed to sub-systems to analyse the criticality of each component and optimise them. Human reliability was addressed using an enhanced barrier weighting method. A rapid degradation curve is obtained on a subsea system relative to the base case subjected to a time-dependent corrosion stress factor. It reveals that subsea system components failed faster than their Mean time to failure specifications from Offshore Reliability Database as a result of cumulative marine stresses exertion. The case study demonstrated that the reliability of a subsea system can be systematically optimised by modelling the system under higher technical and organisational stresses, prioritising the critical sub-systems and making befitting provisions for redundancy and tolerances.

Original languageEnglish
Pages (from-to)159-174
Number of pages16
JournalReliability Engineering and System Safety
Volume156
Early online date2 Aug 2016
DOIs
Publication statusPublished - 1 Dec 2016

Keywords

  • human and operational factors
  • reliability analysis
  • risk analysis
  • subsea control system
  • subsea power system
  • subsea process system
  • Weibull analysis

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