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Reliability-based temporal and spatial maintenance strategy for integrity management of corroded underground pipelines
- Source :
- Structure and Infrastructure Engineering. 12:1281-1294
- Publication Year :
- 2015
- Publisher :
- Informa UK Limited, 2015.
-
Abstract
- In this work, a novel stochastic model framework for predicting the external corrosion growth in buried pipeline structures has been developed, and a reliability-based temporal and spatial maintenance strategy is presented. The spatial correlation of soil properties is modelled via hidden Markov random field. The temporal correlation of the corrosion rate is characterised by the geometric Brownian bridge process. A Bayesian inferential framework is employed to estimate the model parameters of the corrosion growth model using in-line inspection data. The proposed corrosion growth model was validated with actual inspection data. In the reliability analysis, the impact of device detectability is considered and hence the estimated failure probability is more realistic. The proposed maintenance strategy is directly based on the time-specific and location-specific failure probability. The application of the proposed model and maintenance strategy is illustrated through a real-life pipeline system. The r...
- Subjects :
- Engineering
Stochastic modelling
Stochastic process
business.industry
020209 energy
Mechanical Engineering
Markov process
020101 civil engineering
Ocean Engineering
02 engineering and technology
Building and Construction
Brownian bridge
Geotechnical Engineering and Engineering Geology
Pipeline (software)
0201 civil engineering
Reliability engineering
Pipeline transport
symbols.namesake
0202 electrical engineering, electronic engineering, information engineering
symbols
Safety, Risk, Reliability and Quality
Hidden Markov random field
business
Reliability (statistics)
Civil and Structural Engineering
Subjects
Details
- ISSN :
- 17448980 and 15732479
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- Structure and Infrastructure Engineering
- Accession number :
- edsair.doi...........ceab36275e557f2b5ef6080b4104762f