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Repair of wind turbine blades: Review of methods and related computational mechanics problems

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  • Mishnaevsky, Leon

Abstract

A short overview of main repair techniques for wind turbine blades and the related problems of computational mechanics is presented. Computational models of the leading edge erosion of wind turbine blades, injection repair and viscous flow, patch/scarf repair as well as curing and adhesive development are reviewed. Both the degradation of wind turbine blades during service (caused by surface erosion, surface cracking, delamination, fiber failure) and the repair procedures (coating, patch and scarf attachment, injection and curing of adhesives) represent the multiscale processes, controlled by geometrical., blade, patch, scarf geometries), mechanical (strength of composite, strength of adhesive, coating, stress distribution) and physical/chemical effects (curing, viscous flow, humidity, temperature and UV effects). For the further optimization of repair technology and efficiency, multi-physical, multiscale computational models should be employed.

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  • 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.
    • Handle: RePEc:eee:renene:v:140:y:2019:i:c:p:828-839
    DOI: 10.1016/j.renene.2019.03.113
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    References listed on IDEAS

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    1. Slot, H.M. & Gelinck, E.R.M. & Rentrop, C. & van der Heide, E., 2015. "Leading edge erosion of coated wind turbine blades: Review of coating life models," Renewable Energy, Elsevier, vol. 80(C), pages 837-848.
    2. Fraisse, Anthony & Bech, Jakob Ilsted & Borum, Kaj Kvisgaard & Fedorov, Vladimir & Frost-Jensen Johansen, Nicolai & McGugan, Malcolm & Mishnaevsky, Leon & Kusano, Yukihiro, 2018. "Impact fatigue damage of coated glass fibre reinforced polymer laminate," Renewable Energy, Elsevier, vol. 126(C), pages 1102-1112.
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    1. Charlotte Bay Hasager & Flemming Vejen & Witold Robert Skrzypiński & Anna-Maria Tilg, 2021. "Rain Erosion Load and Its Effect on Leading-Edge Lifetime and Potential of Erosion-Safe Mode at Wind Turbines in the North Sea and Baltic Sea," Energies, MDPI, vol. 14(7), pages 1-24, April.
    2. Amrit Shankar Verma & Sandro Di Noi & Zhengru Ren & Zhiyu Jiang & Julie J. E. Teuwen, 2021. "Minimum Leading Edge Protection Application Length to Combat Rain-Induced Erosion of Wind Turbine Blades," Energies, MDPI, vol. 14(6), pages 1-26, March.
    3. Muhammad Abdullah Sheeraz & Muhammad Sohail Malik & Khalid Rehman & Hassan Elahi & Zubair Butt & Iftikhar Ahmad & Marco Eugeni & Paolo Gaudenzi, 2021. "Numerical Assessment and Parametric Optimization of a Piezoelectric Wind Energy Harvester for IoT-Based Applications," Energies, MDPI, vol. 14(9), pages 1-19, April.
    4. 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.
    5. Antoine Chrétien & Antoine Tahan & Philippe Cambron & Adaiton Oliveira-Filho, 2023. "Operational Wind Turbine Blade Damage Evaluation Based on 10-min SCADA and 1 Hz Data," Energies, MDPI, vol. 16(7), pages 1-18, March.
    6. Leon Mishnaevsky & Nicolai Frost-Jensen Johansen & Anthony Fraisse & Søren Fæster & Thomas Jensen & Brian Bendixen, 2022. "Technologies of Wind Turbine Blade Repair: Practical Comparison," Energies, MDPI, vol. 15(5), pages 1-17, February.
    7. Mishnaevsky, Leon & Tempelis, Antonios & Kuthe, Nikesh & Mahajan, Puneet, 2023. "Recent developments in the protection of wind turbine blades against leading edge erosion: Materials solutions and predictive modelling," Renewable Energy, Elsevier, vol. 215(C).
    8. Xiaoxun, Zhu & Xinyu, Hang & Xiaoxia, Gao & Xing, Yang & Zixu, Xu & Yu, Wang & Huaxin, Liu, 2022. "Research on crack detection method of wind turbine blade based on a deep learning method," Applied Energy, Elsevier, vol. 328(C).
    9. 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.
    10. Yang, Cong & Liu, Xun & Zhou, Hua & Ke, Yan & See, John, 2023. "Towards accurate image stitching for drone-based wind turbine blade inspection," Renewable Energy, Elsevier, vol. 203(C), pages 267-279.
    11. 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.
    12. Fang, Jianhao & Hu, Weifei & Liu, Zhenyu & Chen, Weiyi & Tan, Jianrong & Jiang, Zhiyu & Verma, Amrit Shankar, 2022. "Wind turbine rotor speed design optimization considering rain erosion based on deep reinforcement learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    13. 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.

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