Articles | Volume 10, issue 12
https://doi.org/10.5194/wes-10-2947-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-10-2947-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Dec 2025
Research article |
| 10 Dec 2025
| 10 Dec 2025
Probability assessment of static overload in wind turbine blade bearings considering turbulence, design, and manufacturing variability
Department of Marine Technology, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
Amir Rasekhi Nejad
Department of Marine Technology, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
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Cited articles
Alavi, O., Mohammadi, K., and Mostafaeipour, A.: Evaluating the suitability of wind speed probability distribution models: A case of study of east and southeast parts of Iran, Energy Conversion and Management, 119, 101–108, https://doi.org/10.1016/j.enconman.2016.04.039, 2016. a, b
Andreasen, D. K., Rodenas-Soler, C., Oertel, U., Krugel, K., Reinares, I., Mendia, I. S., Nielsen, J. H., Olsen, A., Tinni, A., Vizireanu, D., Cheaytani, J., Kratz, M., and Bousseau, P.: Portability of failure mode detection/prognosis orientations 2.0, Tech. rep., ROMEO, https://www.romeoproject.eu/wp-content/uploads/2022/10/D2_4_Portability_2_3_final.pdf (last access: 14 August 2024), 2022. a
Bain, L. J. and Antle, C. E.: Estimation of Parameters in the Weibull Distribution, Technometrics, 9, 621–627, 1967. a
Cheng, H., Zhang, Y., Lu, W., and Yang, Z.: Reliability sensitivity analysis based on stress–strength model of bearing with random parameters, Review of Scientific Instruments, 91, 073908, https://doi.org/10.1063/1.5143405, 2020. a, b, c, d
Daidié, A., Chaib, Z., and Ghosn, A.: 3D Simplified Finite Elements Analysis of Load and Contact Angle in a Slewing Ball Bearing, Journal of Mechanical Design, 130, 082601, https://doi.org/10.1115/1.2918915, 2008. a
Dawson, C., Abrahart, R., and See, L.: HydroTest: a web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts, Environmental Modelling & Software, 22, 1034–1052, https://doi.org/10.1016/j.envsoft.2006.06.008, 2007. a
DNV-ST-0361: Machinery for wind turbines, https://www.dnv.com/energy/standards-guidelines/dnv-st-0361-machinery-for-wind-turbines/ (last access: 6 November 2025), 2016. a
Germanischer Lloyd: Guideline for the Certification of Wind Turbines, Germanischer Lloyd, Hamburg, Germany, 2010. a
GIZ: Vietnam – Wind Measurement Data, https://energydata.info/dataset/vietnam-wind-measurements-giz, last access: 20 January 2023. a
Graßmann, M., Schleich, F., and Stammler, M.: Validation of a finite-element model of a wind turbine blade bearing, Finite Elements in Analysis and Design, 221, 103957, https://doi.org/10.1016/j.finel.2023.103957, 2023. a
Harris, T. A. and Kotzalas, M. N.: Rolling bearing analysis-2 volume set, CRC Press, https://doi.org/10.1201/9781482275148, 2006. a
Haus, L., Sheng, S., and Pulikollu, R. V.: Wind Turbine Major Systems Reliability Trends and Mitigation Strategies, https://app.box.com/s/ktjzjdxn77omu1cjoy9znymbrynlsw0d (last access: 24 September 2024), 2024. a
He, H., Chen, Y., Jin, X., Liu, H., and Wang, C.: Study on predicting rolling contact fatigue of pitch bearing raceway in offshore wind turbine, International Journal of Fatigue, 184, 108284, https://doi.org/10.1016/j.ijfatigue.2024.108284, 2024. a
IEA: Renewable Energy Market Update Outlook for 2023 and 2024, Tech. rep., International Energy Agency (IEA), https://www.iea.org/reports/renewable-energy-market-update-june-2023 (last access: 14 August 2024), 2023. a
IEC 61400-4: Wind energy generation systems, Part 4: Design requirements for wind turbine gearboxes, https://webstore.iec.ch/en/publication/63497 (last access: 17 July 2025), 2025. a
Imdad, A., Arniella, V., Zafra, A., and Belzunce, J.: Tensile behaviour of 42CrMo4 steel submitted to annealed, normalized, and quench and tempering heat treatments with in-situ hydrogen charging, International Journal of Hydrogen Energy, 50, 270–280, https://doi.org/10.1016/j.ijhydene.2023.10.082, 2024. a
Jager, D. and Andreas, A.: NREL National Wind Technology Center (NWTC): M2 Tower, Boulder, Colorado [data], Tech. rep., NREL Report No. DA-5500-56489, https://doi.org/10.5439/1052222, 1996. a
Jonkman, B.: TurbSim User's Guide: Version 1.50, Tech. rep., NREL/TP-500-46198, National Renewable Energy Lab.(NREL), Golden, CO (United States), https://doi.org/10.2172/965520, 2009. a, b
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW reference wind turbine for offshore system development, Tech. rep., National Renewable Energy Lab.(NREL), Golden, CO (United States), https://doi.org/10.2172/947422, 2009. a, b
Keller, J. and Guo, Y.: Rating of a Pitch Bearing for a 1.5-MW Wind Turbine, Tech. rep., NREL/TP-5000-82462, National Renewable Energy Lab.(NREL), Golden, CO (United States), https://doi.org/10.2172/1902646, 2022. a, b, c
Lai, J.: A new model for the static load rating of surface induction-hardened bearings, Evolution, 2, 27–32, 2011. a
Lai, J., Ovize, P., Kuijpers, H., Bacchettto, A., and Ioannides, S.: Case Depth and Static Capacity of Surface Induction-Hardened Rings, Journal of ASTM International, 6, 1–16, https://doi.org/10.1520/JAI102630, 2009. a, b
Leupold, S., Schelenz, R., and Jacobs, G.: Method to determine the local load cycles of a blade bearing using flexible multi-body simulation, Forsch. Ingenieurwes., 85, 211–218, https://doi.org/10.1007/s10010-021-00457-y, 2021. a
Lewis, S., Gaillard, L., Seiler, R., Parzianello, G., and LeLetty, R.: Recent Steps Towards a Common Understanding of Ball Bearing Load Capacity, 16th European Space Mechanisms and Tribology Symposium 2015, Bilbao, Spain, 23–25 September 2015, 2015. a
Melchers, R. E. and Beck, A. T.: Structural reliability analysis and prediction, John Wiley & Sons, https://doi.org/10.1002/9781119266105, 2018. a
Menck, O., Stammler, M., and Schleich, F.: Fatigue lifetime calculation of wind turbine blade bearings considering blade-dependent load distribution, Wind Energ. Sci., 5, 1743–1754, https://doi.org/10.5194/wes-5-1743-2020, 2020. a, b, c, d
Mishnaevsky Jr., L. and Thomsen, K.: Costs of repair of wind turbine blades: Influence of technology aspects, Wind Energy, 23, 2247–2255, 2020. a
Nejad, A. R.: Modelling and analysis of drivetrains in offshore wind turbines, Offshore wind energy technology, 37, https://doi.org/10.1002/9781119097808, 2018. a
Ørsted: Green solutions: Offshore wind data, https://orsted.com/en/our-business/offshore-wind/wind-data, last access: 4 June 2022. a
Rezaei, A. and Nejad, A. R.: Effect of wind speed distribution and site assessment on pitch bearing loads and life, Journal of Physics: Conference Series, 2507, 012021, https://doi.org/10.1088/1742-6596/2507/1/012021, 2023. a, b
Rezaei, A., Schleich, F., Menck, O., Grassmann, M., Bartschat, A., and Nejad, A. R.: Comparative analysis of rolling contact fatigue life in a wind turbine pitch bearing with different modeling approaches, Journal of Physics: Conference Series, 2767, 052036, https://doi.org/10.1088/1742-6596/2767/5/052036, 2024. a, b, c
Renewable Energy and Energy Efficiency Organization (SATBA): https://www.satba.gov.ir/, last access: 24 May 2022. a
Schwack, F., Stammler, M., Poll, G., and Reuter, A.: Comparison of life calculations for oscillating bearings considering individual pitch control in wind turbines, Journal of Physics: Conference Series, 753, 112013, https://doi.org/10.1088/1742-6596/753/11/112013, 2016. a
Shi, H., Z. Dong, N. X., and Huang, Q.: Wind Speed Distributions Used in Wind Energy Assessment: A Review, Frontiers in Energy Research, 9, 769920, https://doi.org/10.3389/fenrg.2021.769920, 2021. a, b
Shimizu, S., Tosha, K., and Tsuchiya, K.: New data analysis of probabilistic stress-life (P–S–N) curve and its application for structural materials, International Journal of Fatigue, 32, 565–575, https://doi.org/10.1016/j.ijfatigue.2009.07.017, 2010. a
Solano-Alvarez, W.: Microstructural degradation of bearing steels, PhD thesis, University of Cambridge, https://doi.org/10.17863/CAM.14283, 2015. a
Stehly, T., Duffy, P., and Hernando, D. M.: Cost of Wind Energy Review: 2024 Edition, Tech. rep., NREL/PR-5000-91775, National Renewable Energy Lab.(NREL), Golden, CO (United States), https://doi.org/10.2172/2479271, 2024. a
Wang, X., Wang, B., Chang, M., and Li, L.: Reliability and sensitivity analysis for bearings considering the correlation of multiple failure modes by mixed Copula function, Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability, 234, 15–26, https://doi.org/10.1177/1748006X19876137, 2020. a, b
Wang, Y., Wang, W., and Zhao, Z.: Effect of race conformities in angular contact ball bearing, Tribology International, 104, 109–120, https://doi.org/10.1016/j.triboint.2016.08.034, 2016. a
World Bank Group: Ethiopia – Wind Measurement Data, https://energydata.info/dataset/ethiopia-wind-measurement-data, last access: 20 January 2023a. a
World Bank Group: Pakistan – Wind Measurement Data, https://energydata.info/dataset/pakistan-wind-measurement-data, last access: 20 January 2023b. a
Yu, J., Fu, Y., Yu, Y., Wu, S., Wu, Y., You, M., Guo, S., and Li, M.: Assessment of Offshore Wind Characteristics and Wind Energy Potential in Bohai Bay, China, Energies, 12, https://doi.org/10.3390/en12152879, 2019. a, b
Short summary
We analyzed the reliability of wind turbine blade bearings under extreme turbulence wind conditions to improve their safety and performance. Using simulations, we studied how factors like turbulence and design variations affect failure probability. Our findings show that current standards may underestimate these risks and highlight the need for stricter controls on critical design parameters.
We analyzed the reliability of wind turbine blade bearings under extreme turbulence wind...
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