Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Fuzzy Inference based Reliability Method for Underground Gas Pipelines in the Presence of Corrosion Defects

  • Kim, Seong-Jun (Department of Industrial Engineering and Management Science, Gangneung-Wonju National University (GWNU)) ;
  • Choe, Byung Hak (Department of Metal and Advanced Materials Engineering, Gangneung-Wonju National University (GWNU)) ;
  • Kim, Woosik (Research Institute, Korea Gas Corporation (KOGAS)) ;
  • Ki, Ikjoong (Research Institute, Korea Gas Corporation (KOGAS))
  • Received : 2016.09.20
  • Accepted : 2016.10.18
  • Published : 2016.10.25
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Abstract

Remaining lifetime prediction of the underground gas pipeline plays a key role in maintenance planning and public safety. One of main causes in the pipeline failure is metal corrosion. This paper deals with estimating the pipeline reliability in the presence of corrosion defects. Because a pipeline has uncertainty and variability in its operation, probabilistic approximation approaches such as first order second moment (FOSM), first order reliability method (FORM), second order reliability method (SORM), and Monte Carlo simulation (MCS) are widely employed for pipeline reliability predictions. This paper presents a fuzzy inference based reliability method (FIRM). Compared with existing methods, a distinction of our method is to incorporate a fuzzy inference into quantifying degrees of variability in corrosion defects. As metal corrosion depends on the service environment, this feature makes it easier to obtain practical predictions. Numerical experiments are conducted by using a field dataset. The result indicates that the proposed method works well and, in particular, it provides more advisory estimations of the remaining lifetime of the gas pipeline.

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References

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