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Review of corrosion fatigue in offshore structures: Present status and challenges in the offshore wind sector

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  • Adedipe, Oyewole
  • Brennan, Feargal
  • Kolios, Athanasios

Abstract

Offshore wind has been identified as one of the emerging sustainable energy sources in the United Kingdom. Offshore wind turbine support structures are mainly fabricated of welded tubular members, similar to structures used for oil and gas applications, and are exposed to highly dynamic, harsh marine environments. However, their structural details and design requirements are significantly different due to the magnitude and frequency of operational and environmental loadings acting on the support structures. These conditions would significantly affect their structural dynamic response characteristics due to the magnitude of the applied load. This may therefore have some significant effects on the crack growth behaviour and the extent to which corrosion can be associated with damage to the support structures. However, the magnitude of the applied load might depend on turbine size, water depth, soil conditions and type of support structures. It is therefore essential to design wind turbine support structures against prescribed limit states to ensure economical and safe operation. This paper presents a review of corrosion fatigue in offshore structures as regards the effects of seawater, environment and mechanical loading. Existing literature which documents results from previous campaigns is presented, including works referring to oil and gas structures, highlighting the significant difference in the aspects of loading and use of modern fabrication processes, with a view to illustrating the requirements for an update to the existing corrosion fatigue database that will suit offshore wind structures׳ design requirements.

Suggested Citation

  • Adedipe, Oyewole & Brennan, Feargal & Kolios, Athanasios, 2016. "Review of corrosion fatigue in offshore structures: Present status and challenges in the offshore wind sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 141-154.
    • Handle: RePEc:eee:rensus:v:61:y:2016:i:c:p:141-154
    DOI: 10.1016/j.rser.2016.02.017
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    References listed on IDEAS

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    1. Zhixin, Wang & Chuanwen, Jiang & Qian, Ai & Chengmin, Wang, 2009. "The key technology of offshore wind farm and its new development in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(1), pages 216-222, January.
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    3. Ochieng, E.G. & Melaine, Y. & Potts, S.J. & Zuofa, T. & Egbu, C.O. & Price, A.D.F. & Ruan, X., 2014. "Future for offshore wind energy in the United Kingdom: The way forward," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 655-666.
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    Cited by:

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    3. Zou, Guang & Kolios, Athanasios, 2022. "Quantifying the value of negative inspection outcomes in fatigue maintenance planning: Cost reduction, risk mitigation and reliability growth," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Maria Martinez-Luengo & Mahmood Shafiee, 2019. "Guidelines and Cost-Benefit Analysis of the Structural Health Monitoring Implementation in Offshore Wind Turbine Support Structures," Energies, MDPI, vol. 12(6), pages 1-26, March.
    5. Shittu, Abdulhakim Adeoye & Mehmanparast, Ali & Hart, Phil & Kolios, Athanasios, 2021. "Comparative study between S-N and fracture mechanics approach on reliability assessment of offshore wind turbine jacket foundations," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Wang, L. & Kolios, A. & Liu, X. & Venetsanos, D. & Rui, C., 2022. "Reliability of offshore wind turbine support structures: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    7. Waseem Khodabux & Feargal Brennan, 2021. "Objective Analysis of Corrosion Pits in Offshore Wind Structures Using Image Processing," Energies, MDPI, vol. 14(17), pages 1-17, August.
    8. Martinez-Luengo, Maria & Kolios, Athanasios & Wang, Lin, 2016. "Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 91-105.

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