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A framework for fatigue reliability analysis of high-pressure turbine blades

Author

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  • Jie Zhou

    (University of Electronic Science and Technology of China
    University of Electronic Science and Technology of China)

  • Hong-Zhong Huang

    (University of Electronic Science and Technology of China
    University of Electronic Science and Technology of China)

  • Yan-Feng Li

    (University of Electronic Science and Technology of China
    University of Electronic Science and Technology of China)

  • Junyu Guo

    (University of Electronic Science and Technology of China
    University of Electronic Science and Technology of China)

Abstract

Fatigue evolution under continued stresses is a process of degradation of material performance with many uncertainties. In order to quantify the uncertainties of materials and working conditions, a probabilistic method is utilized to estimate the reliability of structures by considering scatter of the fatigue life prediction model, in which improvements are provided to model the accumulation of the damage. Firstly, the fatigue parameters are modeled by the Bayesian theory and the finite element analysis. Secondly, the distributions of parameters are transformed by the probabilistic method into the distribution of fatigue life by using the fatigue life prediction model, and a damage accumulation model is chosen to characterize regulation evolution of properties. Finally, the probability distribution function transformation approach is employed to expound distribution of fatigue damage by the known distribution of fatigue life, and a general probabilistic method is then used to estimate the reliability. By combining the above methods, the framework for reliability analysis is established and then is used to calculate the reliability for high-pressure turbine blades in a low cycle fatigue region under variable amplitude loadings.

Suggested Citation

  • Jie Zhou & Hong-Zhong Huang & Yan-Feng Li & Junyu Guo, 2022. "A framework for fatigue reliability analysis of high-pressure turbine blades," Annals of Operations Research, Springer, vol. 311(1), pages 489-505, April.
    • Handle: RePEc:spr:annopr:v:311:y:2022:i:1:d:10.1007_s10479-019-03203-4
    DOI: 10.1007/s10479-019-03203-4
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    References listed on IDEAS

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