4.5 Article

Corrosion failure probability analysis of buried gas pipelines based on subset simulation

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jlp.2018.11.008

关键词

Buried gas pipeline; Corrosion failure probability; Failure model; Multiple loads; Subset simulation

资金

  1. National Natural Science Foundation of China [51508110]
  2. Natural Science Foundation of Guangdong Province [2016A030310341]
  3. Science and Technology Planning Project of Guangdong Province [2017A020219006]

向作者/读者索取更多资源

Corrosion is the main reason for the failure of buried gas pipelines. For effective corrosion failure probability analysis, the structural reliability theory was adopted in this study to establish two calculation models for pipeline corrosion failure: the pressure failure model and von Mises stress failure model. Then, two calculation models for the corrosion failure probability were established based on a corrosion depth growth model obtained from actual survey data of soil corrosion characteristics. In an example, Monte Carlo simulation (MCS) and subset simulation (SS) were used to analyze the corrosion failure probability of pipelines, and the results were compared. SS can compensate for the shortcomings of MCS as it has higher computational efficiency and accuracy. Therefore, SS was adopted to simulate variations in the corrosion failure probability of buried pipelines with the service time for the two failure probability calculation models, which were applied to a natural gas pipeline located in a chemical industry park in Zhuhai, China. A sensitivity analysis was carried out on the relevant parameters that affect the failure probability. The results showed that multiple loads caused by the covering soil, residual stress, temperature differential, and bending stress have a non-negligible effect on the pipeline reliability. The corrosion coefficients gradually become the most important factors that affect the failure probability with increased service time. The proposed methodology considers the actual operating conditions of pipelines to provide a reliable theoretical basis for integrity management.

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