IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v119y2018icp754-766.html
   My bibliography  Save this article

Assessing progressive failure in long wind turbine blades under quasi-static and cyclic loads

Author

Listed:
  • Zuo, Yangjie
  • Montesano, John
  • Singh, Chandra Veer

Abstract

Predicting progressive failure and consequential loss in the load-bearing capability of large-scale composite wind blades is vital for accurately assessing their service life and maintenance. A physics-based multi-scale damage model describing progressive ply cracking and joint adhesive debonding in blades under both quasi-static and cyclic loading is presented. The complete structure of the blade was considered including the shell-spar adhesive joint and shell-root adhesive joint. For quasi-static loading, the geometrical transition region of the blade was observed as the critical ply crack damage region, which was in agreement with previous experimental results. The matrix micro-cracking damage was mainly caused by high gale wind speeds, and adhesive debonding ultimately initiated at the shell-spar joint. The blade tip deflection increased nonlinearly with increasing wind speeds, reaching 29.0% of the blade length at 19 m/s. For cyclic loading, sub-critical damage grew along the length of the blade with increasing cycles, gradually increasing the normal and shear stresses in the joint adhesive layer as the crack density increased, eventually leading to local shell-spar adhesive debonding. The simulation methodology presented here will be useful for assessing the durability and increasing the safety and accuracy of service life prediction of large-scale blade structures.

Suggested Citation

  • Zuo, Yangjie & Montesano, John & Singh, Chandra Veer, 2018. "Assessing progressive failure in long wind turbine blades under quasi-static and cyclic loads," Renewable Energy, Elsevier, vol. 119(C), pages 754-766.
    • Handle: RePEc:eee:renene:v:119:y:2018:i:c:p:754-766
    DOI: 10.1016/j.renene.2017.10.103
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096014811731073X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2017.10.103?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. Feng, Yi & Lin, Heyun & Ho, S.L. & Yan, Jianhu & Dong, Jianning & Fang, Shuhua & Huang, Yunkai, 2015. "Overview of wind power generation in China: Status and development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 847-858.
    2. Joselin Herbert, G.M. & Iniyan, S. & Sreevalsan, E. & Rajapandian, S., 2007. "A review of wind energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(6), pages 1117-1145, August.
    3. Ji, Y.M. & Han, K.S., 2014. "Fracture mechanics approach for failure of adhesive joints in wind turbine blades," Renewable Energy, Elsevier, vol. 65(C), pages 23-28.
    4. Wang, Jianzhou & Qin, Shanshan & Jin, Shiqiang & Wu, Jie, 2015. "Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 26-42.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Murray, Robynne E. & Roadman, Jason & Beach, Ryan, 2019. "Fusion joining of thermoplastic composite wind turbine blades: Lap-shear bond characterization," Renewable Energy, Elsevier, vol. 140(C), pages 501-512.
    2. Jiménez, Alfredo Arcos & García Márquez, Fausto Pedro & Moraleda, Victoria Borja & Gómez Muñoz, Carlos Quiterio, 2019. "Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis," Renewable Energy, Elsevier, vol. 132(C), pages 1034-1048.

    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. Yuyang Gao & Chao Qu & Kequan Zhang, 2016. "A Hybrid Method Based on Singular Spectrum Analysis, Firefly Algorithm, and BP Neural Network for Short-Term Wind Speed Forecasting," Energies, MDPI, vol. 9(10), pages 1-28, September.
    2. Moura Carneiro, F.O. & Barbosa Rocha, H.H. & Costa Rocha, P.A., 2013. "Investigation of possible societal risk associated with wind power generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 30-36.
    3. Dixon, Christopher & Reynolds, Steve & Rodley, David, 2016. "Micro/small wind turbine power control for electrolysis applications," Renewable Energy, Elsevier, vol. 87(P1), pages 182-192.
    4. Chandel, S.S. & Ramasamy, P. & Murthy, K.S.R, 2014. "Wind power potential assessment of 12 locations in western Himalayan region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 530-545.
    5. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
    6. Eissa (SIEEE), M.M., 2015. "Protection techniques with renewable resources and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1645-1667.
    7. K. Padmanathan & N. Kamalakannan & P. Sanjeevikumar & F. Blaabjerg & J. B. Holm-Nielsen & G. Uma & R. Arul & R. Rajesh & A. Srinivasan & J. Baskaran, 2019. "Conceptual Framework of Antecedents to Trends on Permanent Magnet Synchronous Generators for Wind Energy Conversion Systems," Energies, MDPI, vol. 12(13), pages 1-39, July.
    8. Breen, Benjamin & Vega, Amaya & Feo-Valero, Maria, 2015. "An empirical analysis of mode and route choice for international freight transport in Ireland," Working Papers 262587, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    9. Burgaç, Alper & Yavuz, Hakan, 2019. "Fuzzy Logic based hybrid type control implementation of a heaving wave energy converter," Energy, Elsevier, vol. 170(C), pages 1202-1214.
    10. Defne, Zafer & Haas, Kevin A. & Fritz, Hermann M., 2011. "GIS based multi-criteria assessment of tidal stream power potential: A case study for Georgia, USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2310-2321, June.
    11. Aliyu, Abubakar Sadiq & Dada, Joseph O. & Adam, Ibrahim Khalil, 2015. "Current status and future prospects of renewable energy in Nigeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 336-346.
    12. Motasemi, F. & Afzal, Muhammad T., 2013. "A review on the microwave-assisted pyrolysis technique," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 317-330.
    13. Ye, Lin & Zhang, Cihang & Xue, Hui & Li, Jiachen & Lu, Peng & Zhao, Yongning, 2019. "Study of assessment on capability of wind power accommodation in regional power grids," Renewable Energy, Elsevier, vol. 133(C), pages 647-662.
    14. Kaldellis, John K. & Zafirakis, D., 2011. "The wind energy (r)evolution: A short review of a long history," Renewable Energy, Elsevier, vol. 36(7), pages 1887-1901.
    15. Luo, Shihua & Hu, Weihao & Liu, Wen & Zhang, Zhenyuan & Bai, Chunguang & Huang, Qi & Chen, Zhe, 2022. "Study on the decarbonization in China's power sector under the background of carbon neutrality by 2060," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    16. Yang, Jinshui & Peng, Chaoyi & Xiao, Jiayu & Zeng, Jingcheng & Yuan, Yun, 2012. "Application of videometric technique to deformation measurement for large-scale composite wind turbine blade," Applied Energy, Elsevier, vol. 98(C), pages 292-300.
    17. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    18. Hocaoglu, Fatih Onur & Serttas, Fatih, 2017. "A novel hybrid (Mycielski-Markov) model for hourly solar radiation forecasting," Renewable Energy, Elsevier, vol. 108(C), pages 635-643.
    19. Han, Wanlong & Yan, Peigang & Han, Wanjin & He, Yurong, 2015. "Design of wind turbines with shroud and lobed ejectors for efficient utilization of low-grade wind energy," Energy, Elsevier, vol. 89(C), pages 687-701.
    20. Shah, Owaisur Rahman & Tarfaoui, Mostapha, 2016. "The identification of structurally sensitive zones subject to failure in a wind turbine blade using nodal displacement based finite element sub-modeling," Renewable Energy, Elsevier, vol. 87(P1), pages 168-181.

    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:renene:v:119:y:2018:i:c:p:754-766. 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: http://www.journals.elsevier.com/renewable-energy .

    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.