IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v262y2025ics0951832025003758.html
   My bibliography  Save this article

Failure analysis of corroded hydrogen-blended natural gas pipelines based on finite element analysis and genetic algorithm-back propagation neural network

Author

Listed:
  • Xie, Mingjiang
  • Wei, Ziqi
  • Zhao, Jianli
  • Chen, Yuejian

Abstract

Blending hydrogen into the existing natural gas pipelines is an effective way to reduce hydrogen transportation costs and facilitate the rapid adoption of hydrogen energy. However, the impact of hydrogen embrittlement on the burst pressure and remaining life of corroded pipelines is not well understood, which poses a significant challenge to pipeline integrity management. To overcome this challenge, this study examines the impact of hydrogen embrittlement on the mechanical properties of pipeline steel and utilizes finite element analysis to calculate the burst pressure of pipelines under varying corrosion geometrical parameters and hydrogen partial pressures. The results obtained are used to train a genetic algorithm-backpropagation (GA-BP) neural network model that predicts burst pressure for hydrogen-blended natural gas pipelines. Additionally, the corrosion maximum depth that can lead to pipeline failure is determined and the prediction of the remaining useful life is realized by integrating corrosion growth models. The findings indicate that the impact of hydrogen embrittlement on the burst pressure of corroded X52 pipelines is negligible. However, for corroded X80 pipelines, hydrogen embrittlement results in a reduction in the burst pressure of approximately 6 %, leading to a remaining useful life loss of around 0.24 years.

Suggested Citation

  • Xie, Mingjiang & Wei, Ziqi & Zhao, Jianli & Chen, Yuejian, 2025. "Failure analysis of corroded hydrogen-blended natural gas pipelines based on finite element analysis and genetic algorithm-back propagation neural network," Reliability Engineering and System Safety, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:reensy:v:262:y:2025:i:c:s0951832025003758
    DOI: 10.1016/j.ress.2025.111174
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832025003758
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2025.111174?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:262:y:2025:i:c:s0951832025003758. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.