Residual strength assessment of wind turbine rotor blade composites under combined effects of natural aging and fatigue loads

• Autorzy: Gao Jian-Xiong , An Zong-Wen , Ma Qiang , Bai Xue-Zong

Identyfikatory

DOI

10.17531/ein.2020.4.3

• Języki publikacji: EN

Abstrakty

EN

In this paper, the combined effects of natural aging and fatigue loads are considered to assess the residual strength of wind turbine rotor blade composites under actual service environments. Firstly, a comprehensive environmental factor (CEF) methodology is adopted to quantify the combined effects of environmental factors on residual strength. Meanwhile, the artificial accelerated aging test data are used to determine the weight coefficients of the CEF. Subsequently, a two-variable function is presented to characterize the relationship among residual strength, aging time and the CEF. The natural aging test data are utilized to estimate the unknown parameters of the two-variable function. Finally, the combined effects of natural aging and fatigue loads are considered, and a residual strength model is proposed to analyze the strength degradation behaviors of the wind turbine rotor blade composites. The results indicate that fatigue loads have negative effect on the residual strength, while natural aging has both positive and negative effects on the residual strength.

Słowa kluczowe

EN

wind turbine rotor blade; natural aging; fatigue loads; residual strength; composite material

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2020
• Tom: Vol. 22, no. 4
• Strony: 601--609
• Opis fizyczny: Bibliogr. 39 poz., rys., tab.

Twórcy

autor

Gao Jian-Xiong

• School of Mechanical Engineering, Post-Doctoral Research Station of Electrical Engineering, Xinjiang University, Urumqi, 830046, P. R. China

autor

An Zong-Wen

• School of Mechanical and Electronical Engineering, Lanzhou University of Technology, Lanzhou, 730050, P. R. China

autor

Ma Qiang

• School of Mechanical and Electronical Engineering, Lanzhou University of Technology, Lanzhou, 730050, P. R. China

autor

Bai Xue-Zong

• School of Mechanical and Electronical Engineering, Lanzhou University of Technology, Lanzhou, 730050, P. R. China

Bibliografia

• 1. Beauson J, Lilholt H, Brondsted P. Recycling solid residues recovered from glass fibre-reinforced composites—A review applied to wind turbine blade materials. Journal of Reinforced Plastics and Composites 2014; 33 (16): 1542-1556, https://doi.org/10.1177/0731684414537131.
• 2. Byon E, Ntaimo L, Ding Y. Optimal maintenance strategies for wind turbine systems under stochastic weather conditions. IEEE Transactions on Reliability 2010; 59 (2): 393-404, https://doi.org/10.1109/TR.2010.2046804.
• 3. Chen C Y. Fatigue and Fracture. Wuhan: Huazhong University of Science and Technology Press, 2002.
• 4. Cheng H C, Hwu F S. Fatigue reliability analysis of composites based on residual strength. Advanced Composite Materials 2006; 15 (4):385-402, https://doi.org/10.1163/156855106778835212.
• 5. D’Amore A, Giorgio M, Grassia L. Modeling the residual strength of carbon fiber reinforced composites subjected to cyclic loading. International Journal of Fatigue 2015; 78: 31-37, https://doi.org/10.1016/j.ijfatigue.2015.03.012.
• 6. Gao J X, Yuan Y P. Small sample test approach for obtaining P-S-N curves based on a unified mathematical model. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 2020, https://doi.org/10.1177/0954406220925845.
• 7. Jiang X, Kolstein H, Bijlaard F, Qiang X. Effects of hygrothermal aging on glass-fibre reinforced polymer laminates and adhesive of FRP composite bridge: Moisture diffusion characteristics. Composites, Part A: Applied Science and Manufacturing 2014; 57 (1): 49-58, https://doi.org/10.1016/j.compositesa.2013.11.002.
• 8. Ji Q H, Zhu P, Lu J H, Liu Z. Carbon fiber reinforced plastic fatigue performance prediction and application based on Kriging surrogate model. IEEE Transactions on Reliability 2017; 51 (2): 129-135, https://doi.org/10.16183/j.cnki.jsjtu.2017.02.001.
• 9. Kollia E, Loutas T, Fiamegkou E, Vavouliotis A, Kostopoulos V. Degradation behavior of glass fiber reinforced cyanate ester composites under hydrothermal ageing. Polymer Degradation and Stability 2015; 121: 200-207, https://doi.org/10.1016/j.polymdegradstab.2015.08.015.
• 10. Lambert J, Chambers A R, Sinclair I, Spearing S M. 3D damage characterisation and the role of voids in the fatigue of wind turbine blade materials. Composites Science and Technology 2012; 72 (2): 337-343, https://doi.org/10.1016/j.compscitech.2011.11.023.
• 11. Lee H G, Park J. Static test until structural collapse after fatigue testing of a full-scale wind turbine blade. Composite Structures 2016; 136:251-257, https://doi.org/10.1016/j.compstruct.2015.10.007.
• 12. Li H, Guedes Soares C. Reliability analysis of floating offshore wind turbines support structure using hierarchical Bayesian network. In M. Beer and E. Zio (Eds.), Proceedings of the 29th European Safety and Reliability Conference 2019; 2489-2495, https://doi.org /10.3850/978-981-11-2724-3 0610-cd.
• 13. Li H, Huang H Z, Li Y F, Zhou J, Mi J, Physics of failure-based reliability prediction of turbine blades using multi-source information fusion. Applied Soft Computing 2018; 72: 624-635, https://doi.org/10.1016/j.asoc.2018.05.015.
• 14. Li H, Zhang L, Sun Y, Liu Y P, Wang S L, Zhang Y Z. Prediction of service life of the glass fibre reinforced composite. Engineering Plastics Application 2011; 39 (1): 68-73, https://doi.org/10.3969/j.issn.1001-3539.2011.01.017. Li X, Huang H Z, Li
• 15. F, Ren L. Remaining useful life prediction model of the space station. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21 (3): 501-510, http://doi.org/10.17531/ein.2019.3.17.
• 16. Li X, Huang H Z, Li Y F, Li Y F. Reliability evaluation for VHF and UHF bands under different scenarios via propagation loss model. Eksploatacja i Niezawodnosc-Maintenance and Reliability 2019; 21 (3): 375-383, http://doi.org/10.17531/ein.2019.3.3.
• 17. Li Y F, Huang H Z, Mi J, Peng W, Han X. Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability. Annals of Operations Research 2019; DOI: https://doi.org/10.1007/s10479-019-03247-6.
• 18. Mandell J, Samborsky D, Wang L, Wahl N K. New fatigue data for wind turbine blade materials. Journal of Solar Energy Engineering 2003; 125 (4): 167-179, https://doi.org/10.1115/1.1624089.
• 19. Ma Q, An Z W, Gao J X, Kou H X, Bai X Z. A method of determining test load for full-scale wind turbine blade fatigue tests. Journal of Mechanical Science and Technology 2018; 32 (11): 5097-5104, https://doi.org/10.1007/s12206-018-1006-y.
• 20. Marouani S, Curtil L, Hamelin P. Ageing of carbon/epoxy and carbon/vinylester composites used in the reinforcement and/or the repair of civil engineering structures. Composites, Part B: Engineering 2012; 43 (4): 2020-2030, https://doi.org/10.1016/j.compositesb.2012.01.001.
• 21. Mi J, Beer M, Li Y F, Broggi M, Cheng Y. Reliability and importance analysis of uncertain system with common cause failures based on survival signature. Reliability Engineering & System Safety 2020; 106988, https://doi.org/10.1016/j.ress.2020.106988.
• 22. Mi J, Li Y F, Peng W, Huang H Z. Reliability analysis of complex multi-state system with common cause failure based on evidential networks. Reliability Engineering & System Safety 2018; 174: 71-81.
• 23. Mouzakis D E, Dimogianopoulos D G, Zaoutsos S. Damage assessment of carbon fiber reinforced composites under accelerated aging and validation via stochastic model-based analysis. International Journal of Damage Mechanics 2014; 23 (5): 702-726, https://doi.org/10.1177/1056789513508798.
• 24. Mu P G, Wan X P, Zhao X Y. A new pair of cumulative fatigue damage models for composite materials. Advanced Materials Research 2010;160: 226-230, https://doi.org/10.4028/www.scientific.net/AMR.160-162.226.
• 25. Paramonov Y, Cimanis V, Varickis S, Kleinhofs M. Modeling the residual strength of a fibrous composite using the residual Daniels function. Mechanics of Composite Materials 2016; 52 (4): 497-506, https://doi.org/10.1007/s11029-016-9600-5.
• 26. Ratnaparkhi M V, Park W J. Lognormal distribution-model for fatigue life and residual strength of composite materials. IEEE Transactions on Reliability 1986; 35 (3): 312-315, https://doi.org/10.1109/TR.1986.4335440.
• 27. Romanski L, Bieniek J, Komarnicki P, Debowski M, Detyna J. Operational tests of a dual-rotor mini wind turbine. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2016; 18 (2): 201-209, http://doi.org/10.17531/ein.2016.2.7.
• 28. Shafiee M, Finkelstein M, Bérenguer C. An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks. Reliability Engineering and System Safety 2015; 142: 463-471, https://doi.org/10.1016/j.ress.2015.05.001.
• 29. Shuai L, Zhencai Z, Hao L, Gang S. A system reliability-based design optimization for the scraper chain of scraper conveyors with dependent failure modes. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21 (3): 392-402, http://doi.org/10.17531/ein.2019.3.5.
• 30. Topic D, Sljivac D, Stojkov M. Reliability model of different wind power plant configuration using sequential Monte Carlo simulation. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2016; 18 (2): 237-244, http://doi.org/10.17531/ein.2016.2.11.
• 31. Vassilopoulos A P. Fatigue Life Prediction of Composites and Composite Structures. Woodhead Publishing, 2010.
• 32. Vu D Q, Gigliotti M, Lafarie-Frenot M C. Experimental characterization of thermo-oxidation-induced shrinkage and damage in polymer–matrix composites. Composites, Part A: Applied Science and Manufacturing 2012; 43 (4): 577-586, https://doi.org/10.1016/j.compositesa.2011.12.018.
• 33. Wang Y, Meng J, Zhao Q, Qi S H. Accelerated ageing tests for evaluations of a durability performance of glass-fiber reinforcement polyester composites. Journal of Materials Science and Technology 2010; 26 (6): 572-576, https://doi.org/10.1016/S1005-0302(10)60087-4.
• 34. Wu F Q, Yao W X. A fatigue damage model of composite materials. International Journal of Fatigue 2010; 32 (1): 134-138, https://doi.org/10.1016/j.ijfatigue.2009.02.027.
• 35. Yao W X, Himmel N. A new cumulative fatigue damage model for fibre-reinforced plastics. Composites Science and Technology 2000; 60 (1): 59-64, https://doi.org/10.1016/S0266-3538(99)00100-1.
• 36. Zhang Y, Vassilopoulos A P, Keller T. Fracture of adhesively-bonded pultruded GFRP joints under constant amplitude fatigue loading. International Journal of Fatigue 2010; 32 (7): 979-987, https://doi.org/10.1016/j.ijfatigue.2009.11.004.
• 37. Zhou H F, Dou H Y, Qin L Z, Chen Y, Ni Y Q, Ko J M. A review of full-scale structural testing of wind turbine blades. Renewable and Sustainable Energy Reviews 2014; 33 (2): 177-187, http://doi.org/10.1016/j.rser.2014.01.087.
• 38. Zhu S P, Foletti S, Beretta S. Probabilistic framework for multiaxial LCF assessment under material variability. International Journal of Fatigue 2017; 103: 371-385, https://doi.org/10.1016/j.ijfatigue.2017.06.019.
• 39. Zhu S P, Huang H Z, Peng W W, Wang H K, Mahadevan S. Probabilistic physics of failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty. Reliability Engineering & System Safety 2016; 146: 1-12, https://doi.org/10.1016/j.ress.2015.10.002.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).