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dc.contributor.authorOssai, C.
dc.contributor.authorBoswell, Brian
dc.contributor.authorDavies, I.
dc.date.accessioned2017-01-30T15:00:29Z
dc.date.available2017-01-30T15:00:29Z
dc.date.created2016-02-02T19:30:23Z
dc.date.issued2016
dc.identifier.citationOssai, C. and Boswell, B. and Davies, I. 2016. Stochastic modelling of perfect inspection and repair actions for leak-failure prone internal corroded pipelines. Engineering Failure Analysis. 60: pp. 40-56.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/42549
dc.identifier.doi10.1016/j.engfailanal.2015.11.030
dc.description.abstract

To enhance the performance of any facility, reduce cost and failure probability involves proper inspection and repair decisions. To be able to establish the cost of repair and inspection of corroded pipelines at different stages of the corrosion defect depth growth, Markov modelling technique was adopted. This model formulated an inspection and repair technique, which has the potentials of aiding policy makers in maintenance management of internally corroded pipelines. The transition states were determined using the Remaining Useful Life (RUL) of the pipelines whilst Weibull distribution was used for calculating the corrosion wastage rates at the lifecycle transition phases. Monte Carlo simulation and degradation models were applied for determining future corrosion defect depth growth, in a bid to establish periodic inspection and repair procedures and their costs. Data from an onshore pipeline inspected with Magnetic Flux Leakage (MFL) in-Line-Inspection (ILI) technique was used to test the validity of the model. The results obtained indicate that the model has practical applications for inspection and repairs of aged-internally corroded pipelines.

dc.titleStochastic modelling of perfect inspection and repair actions for leak-failure prone internal corroded pipelines
dc.typeJournal Article
dcterms.source.volume60
dcterms.source.startPage40
dcterms.source.endPage56
dcterms.source.issn1350-6307
dcterms.source.titleEngineering Failure Analysis
curtin.departmentDepartment of Mechanical Engineering
curtin.accessStatusOpen access


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