IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i2p712-d1028319.html
   My bibliography  Save this article

Repair Parameter Design of Outer Reinforcement Layers of Offshore Wind Turbine Blade Spar Cap Based on Structural and Aerodynamic Analysis

Author

Listed:
  • Hui Li

    (School of Architecture and Civil Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Xiaolong Lu

    (School of Architecture and Civil Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Wen Xin

    (School of Mechanical Engineering, Shenyang University of Technology, Shenyang 110870, China
    School of Mechanical Engineering, Liaoning Institute of Science and Technology, Benxi 117004, China)

  • Zhihui Guo

    (School of Architecture and Civil Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Bo Zhou

    (School of Architecture and Civil Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Baokuan Ning

    (School of Architecture and Civil Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Hongbing Bao

    (Jiangsu Key Laboratory of Hi-Tech Research for Wind Turbine Design, Wuxi 214174, China)

Abstract

The influence of the outer reinforcement layers on the repair structure and aerodynamic performance was studied. Firstly, a continuous damage mechanics model was established, and the 3D Hashin criterion and cohesive zone material model were used to analyze the damage repair model. The failure load deviation was 5.5%. Secondly, on the basis of the γ − R e θ transition model and SST–ω turbulence model, the aerodynamic analysis model of DU300 airfoil was established. The numerical simulation results showed that the lift coefficient and pressure distribution at the angle of attack of 10° and 15° were deviated from the experimental values by 2%. Furthermore, 27 structural repair models, nine 2D aerodynamic repair models, and a 3D full-scale blade model were designed. It was found that, when the repair length accounted for 60% of the total model length, the failure load increased by 22%, but the aerodynamic power with the repair length of 10 m was decreased by 0.137%. When the repair area was large and the repair height was from 4 mm to 6 mm, the failure load was greatly increased by about 30%, and the aerodynamic pressure distribution and static pressure field fluctuated significantly. The results show that the structural and aerodynamic characteristics were closely related to the repair parameters.

Suggested Citation

  • Hui Li & Xiaolong Lu & Wen Xin & Zhihui Guo & Bo Zhou & Baokuan Ning & Hongbing Bao, 2023. "Repair Parameter Design of Outer Reinforcement Layers of Offshore Wind Turbine Blade Spar Cap Based on Structural and Aerodynamic Analysis," Energies, MDPI, vol. 16(2), pages 1-24, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:712-:d:1028319
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/2/712/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/2/712/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arcos Jiménez, Alfredo & Zhang, Long & Gómez Muñoz, Carlos Quiterio & García Márquez, Fausto Pedro, 2020. "Maintenance management based on Machine Learning and nonlinear features in wind turbines," Renewable Energy, Elsevier, vol. 146(C), pages 316-328.
    2. Mahmood Shafiee & Michael Patriksson & Ann-Brith Strömberg, 2013. "An Optimal Number-Dependent Preventive Maintenance Strategy for Offshore Wind Turbine Blades Considering Logistics," Advances in Operations Research, Hindawi, vol. 2013, pages 1-12, July.
    3. Khazar Hayat & Shafaqat Siddique & Tipu Sultan & Hafiz T. Ali & Fahed A. Aloufi & Riyadh F. Halawani, 2022. "Effect of Spar Design Optimization on the Mass and Cost of a Large-Scale Composite Wind Turbine Blade," Energies, MDPI, vol. 15(15), pages 1-17, August.
    4. Shafiee, Mahmood & Finkelstein, Maxim & Bérenguer, Christophe, 2015. "An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 463-471.
    5. Mishnaevsky, Leon, 2019. "Repair of wind turbine blades: Review of methods and related computational mechanics problems," Renewable Energy, Elsevier, vol. 140(C), pages 828-839.
    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. 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. Ren, Zhengru & Verma, Amrit Shankar & Li, Ye & Teuwen, Julie J.E. & Jiang, Zhiyu, 2021. "Offshore wind turbine operations and maintenance: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    3. KarabaÄŸ, Oktay & Eruguz, Ayse Sena & Basten, Rob, 2020. "Integrated optimization of maintenance interventions and spare part selection for a partially observable multi-component system," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    4. Hasager, C. & Vejen, F. & Bech, J.I. & Skrzypiński, W.R. & Tilg, A.-M. & Nielsen, M., 2020. "Assessment of the rain and wind climate with focus on wind turbine blade leading edge erosion rate and expected lifetime in Danish Seas," Renewable Energy, Elsevier, vol. 149(C), pages 91-102.
    5. García Márquez, Fausto Pedro & Peco Chacón, Ana María, 2020. "A review of non-destructive testing on wind turbines blades," Renewable Energy, Elsevier, vol. 161(C), pages 998-1010.
    6. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    7. Mishnaevsky, Leon & Hasager, Charlotte Bay & Bak, Christian & Tilg, Anna-Maria & Bech, Jakob I. & Doagou Rad, Saeed & Fæster, Søren, 2021. "Leading edge erosion of wind turbine blades: Understanding, prevention and protection," Renewable Energy, Elsevier, vol. 169(C), pages 953-969.
    8. Liu, Xinbao & Yang, Tianji & Pei, Jun & Liao, Haitao & Pohl, Edward A., 2019. "Replacement and inventory control for a multi-customer product service system with decreasing replacement costs," European Journal of Operational Research, Elsevier, vol. 273(2), pages 561-574.
    9. Sun, Shilin & Wang, Tianyang & Yang, Hongxing & Chu, Fulei, 2022. "Damage identification of wind turbine blades using an adaptive method for compressive beamforming based on the generalized minimax-concave penalty function," Renewable Energy, Elsevier, vol. 181(C), pages 59-70.
    10. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    11. 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).
    12. Bismut, Elizabeth & Straub, Daniel, 2021. "Optimal adaptive inspection and maintenance planning for deteriorating structural systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    13. Wang, Jingjing & Zhao, Xian & Guo, Xiaoxin, 2019. "Optimizing wind turbine's maintenance policies under performance-based contract," Renewable Energy, Elsevier, vol. 135(C), pages 626-634.
    14. Tazi, Nacef & Châtelet, Eric & Bouzidi, Youcef, 2018. "How combined performance and propagation of failure dependencies affect the reliability of a MSS," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 531-541.
    15. Wang, Jiantai & Longyan, Tan & Ma, Xiaobing & Gao, Kaiye & Jia, Heping & Yang, Li, 2023. "Prognosis-driven reliability analysis and replacement policy optimization for two-phase continuous degradation," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    16. Zhou, Xiaojun & Wu, Changjie & Li, Yanting & Xi, Lifeng, 2016. "A preventive maintenance model for leased equipment subject to internal degradation and external shock damage," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 1-7.
    17. Li Yang & Yu Zhao & Xiaobing Ma & Qingan Qiu, 2018. "An optimal inspection and replacement policy for a two-unit system," Journal of Risk and Reliability, , vol. 232(6), pages 766-776, December.
    18. Zhang, Xiaohong & Zeng, Jianchao, 2017. "Joint optimization of condition-based opportunistic maintenance and spare parts provisioning policy in multiunit systems," European Journal of Operational Research, Elsevier, vol. 262(2), pages 479-498.
    19. Feng, Qiang & Zhao, Xiujie & Fan, Dongming & Cai, Baoping & Liu, Yiqi & Ren, Yi, 2019. "Resilience design method based on meta-structure: A case study of offshore wind farm," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 232-244.
    20. Suárez-Cetrulo, Andrés L. & Burnham-King, Lauren & Haughton, David & Carbajo, Ricardo Simón, 2022. "Wind power forecasting using ensemble learning for day-ahead energy trading," Renewable Energy, Elsevier, vol. 191(C), pages 685-698.

    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:gam:jeners:v:16:y:2023:i:2:p:712-:d:1028319. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.