IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v202y2020ics095183202030510x.html
   My bibliography  Save this article

Probabilistic inspection planning of offshore welds subject to the transition from protected to corrosive environment

Author

Listed:
  • Ruiz Muñoz, G.A.
  • Sørensen, J.D.

Abstract

In this paper, a novel method is proposed to optimize inspection plans for fatigue accounting for the situations where corrosion-free or protected environments are changed to a corrosive environment, denoted as the Transitional Environmental Protection (TEP) process. Probabilistic fracture mechanics and S-N curve approaches are calibrated to simulate crack propagations and planning of inspections and repairs of offshore welds. The method presented is relatively simple and conservative: The transition between protected and corrosive environments is addressed by shifting the S-N curve parameters during the damage calculations, performing crack size recalibration and modifying the crack growth material parameters. These concepts are incorporated in an algorithm, which is applicable to new designs or existing structures where no data from previous inspections is available. An example illustrates the potential of the algorithm.

Suggested Citation

  • Ruiz Muñoz, G.A. & Sørensen, J.D., 2020. "Probabilistic inspection planning of offshore welds subject to the transition from protected to corrosive environment," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
  • Handle: RePEc:eee:reensy:v:202:y:2020:i:c:s095183202030510x
    DOI: 10.1016/j.ress.2020.107009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183202030510X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2020.107009?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.

    References listed on IDEAS

    as
    1. Shafiee, Mahmood & Sørensen, John Dalsgaard, 2019. "Maintenance optimization and inspection planning of wind energy assets: Models, methods and strategies," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    2. Chen, Thomas Ying-Jeh & Guikema, Seth David & Daly, Craig Michael, 2019. "Optimal pipe inspection paths considering inspection tool limitations," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 156-166.
    3. Yeratapally, Saikumar R. & Glavicic, Michael G. & Argyrakis, Christos & Sangid, Michael D., 2017. "Bayesian uncertainty quantification and propagation for validation of a microstructure sensitive model for prediction of fatigue crack initiation," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 110-123.
    4. Zhang, Chen & Gao, Wei & Guo, Sheng & Li, Youliang & Yang, Tao, 2017. "Opportunistic maintenance for wind turbines considering imperfect, reliability-based maintenance," Renewable Energy, Elsevier, vol. 103(C), pages 606-612.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2022. "A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty," Applied Energy, Elsevier, vol. 321(C).
    2. Pinciroli, Luca & Baraldi, Piero & Ballabio, Guido & Compare, Michele & Zio, Enrico, 2022. "Optimization of the Operation and Maintenance of renewable energy systems by Deep Reinforcement Learning," Renewable Energy, Elsevier, vol. 183(C), pages 752-763.
    3. Dong, Weiwei & Zhao, Guohua & Yüksel, Serhat & Dinçer, Hasan & Ubay, Gözde Gülseven, 2022. "A novel hybrid decision making approach for the strategic selection of wind energy projects," Renewable Energy, Elsevier, vol. 185(C), pages 321-337.
    4. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2023. "A closed-loop maintenance strategy for offshore wind farms: Incorporating dynamic wind farm states and uncertainty-awareness in decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    5. Izquierdo, J. & Márquez, A. Crespo & Uribetxebarria, J. & Erguido, A., 2020. "On the importance of assessing the operational context impact on maintenance management for life cycle cost of wind energy projects," Renewable Energy, Elsevier, vol. 153(C), pages 1100-1110.
    6. Yu-Chung Tsao & Thuy-Linh Vu, 2023. "Electricity pricing, capacity, and predictive maintenance considering reliability," Annals of Operations Research, Springer, vol. 322(2), pages 991-1011, March.
    7. Yeter, B. & Garbatov, Y. & Guedes Soares, C., 2020. "Risk-based maintenance planning of offshore wind turbine farms," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    8. Saleh, Ali & Remenyte-Prescott, Rasa & Prescott, Darren & Chiachío, Manuel, 2024. "Intelligent and adaptive asset management model for railway sections using the iPN method," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    9. Lubing Xie & Xiaoming Rui & Shuai Li & Xin Hu, 2019. "Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy," Energies, MDPI, vol. 12(14), pages 1-26, July.
    10. Adedipe, Tosin & Shafiee, Mahmood & Zio, Enrico, 2020. "Bayesian Network Modelling for the Wind Energy Industry: An Overview," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    11. Jensen, H.A. & Jerez, D.J., 2019. "A Bayesian model updating approach for detection-related problems in water distribution networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 100-112.
    12. Zhang, Chen & Gao, Wei & Yang, Tao & Guo, Sheng, 2019. "Opportunistic maintenance strategy for wind turbines considering weather conditions and spare parts inventory management," Renewable Energy, Elsevier, vol. 133(C), pages 703-711.
    13. Zhang, Ruixing & An, Liqiang & He, Lun & Yang, Xinmeng & Huang, Zenghao, 2024. "Reliability analysis and inverse optimization method for floating wind turbines driven by dual meta-models combining transient-steady responses," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    14. Evrencan Özcan & Rabia Yumuşak & Tamer Eren, 2019. "Risk Based Maintenance in the Hydroelectric Power Plants," Energies, MDPI, vol. 12(8), pages 1-22, April.
    15. Yikai Ma & Wenjuan Zhang & Juergen Branke, 2024. "Genetic programming hyper-heuristic for evolving a maintenance policy for wind farms," Journal of Heuristics, Springer, vol. 30(5), pages 423-451, December.
    16. Chen, Thomas Ying-Jeh & Guikema, Seth David, 2020. "Prediction of water main failures with the spatial clustering of breaks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    17. Nguyen, Thi Anh Tuyet & Chou, Shuo-Yan, 2019. "Improved maintenance optimization of offshore wind systems considering effects of government subsidies, lost production and discounted cost model," Energy, Elsevier, vol. 187(C).
    18. Yang Lu & Liping Sun & Yanzhuo Xue, 2021. "Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm," Energies, MDPI, vol. 14(4), pages 1-22, February.
    19. Nguyen, Thi-Anh-Tuyet & Chou, Shuo-Yan & Yu, Tiffany Hui-Kuang, 2022. "Developing an exhaustive optimal maintenance schedule for offshore wind turbines based on risk-assessment, technical factors and cost-effective evaluation," Energy, Elsevier, vol. 249(C).
    20. Chen, Thomas Ying-Jeh & Riley, Connor Thomas & Van Hentenryck, Pascal & Guikema, Seth David, 2020. "Optimizing inspection routes in pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 195(C).

    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:202:y:2020:i:c:s095183202030510x. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.