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

  • S.I.: Reliability Modeling with Applications Based on Big Data
  • Published:
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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.

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Abbreviations

v e :

Elastic Poisson’s ratio

v p :

Plastic Poisson’s ratio

τ max, τ A, max :

Maximum shear stress on the corresponding critical plane

τ B :

Shear stress on the corresponding critical plane

σ n, max, σ max, σ B, max :

Maximum normal stress on the corresponding critical plane

σ A :

Normal stress on the corresponding critical plane

σ a :

Normal stress amplitude

\( \sigma_{f}^{{\prime }} \) :

Fatigue strength coefficient

σ y :

Yield strength

Δγ max, Δγ A, max :

Maximum shear strain range on the corresponding critical plane

Δγ B :

Shear strain range on the corresponding critical plane

\( \Delta \varepsilon_{e} \) :

Elastic strain

\( \Delta \varepsilon_{p} \) :

Plastic strain

Δε A :

Normal strain range on the corresponding critical plane

ε a :

Normal strain amplitude

Δε max, Δε B, max :

Maximum normal strain range on the corresponding critical plane

\( \varepsilon_{f}^{{\prime }} \) :

Fatigue ductility coefficient

b :

Fatigue strength exponent

c :

Fatigue ductility exponent

\( \tau_{f}^{{\prime }} \) :

Shear fatigue strength coefficient

b 1 :

Shear fatigue strength exponent

\( \gamma_{f}^{{\prime }} \) :

Shear fatigue ductility coefficient

c 1 :

Shear fatigue ductility exponent

\( \mu_{{N_{f} }} \) :

Mean value of life cycles

\( \mu_{D} \) :

Mean value of damage

\( \sigma_{{N_{f} }} \) :

Variance of life cycles

\( \sigma_{D} \) :

Variance of damage

D :

Damage

\( a \) :

Damage exponent

E :

Young’s modulus

G :

Shear modulus

ρ :

Density

\( N_{f} ,N_{f1} ,N_{f2} \) :

Number of cycles to failure

\( T_{f} \) :

Total life

\( S \) :

Applied stress

\( k,C,m \) :

Material parameter

\( \omega_{1} ,\omega_{2} ,\omega_{3} \) :

Rotational speed

HP:

High-pressure

FEA:

Finite element analysis

FS:

Fatemi-Socie

SWT:

Smith–Watson–Topper

MECP:

Modified energy-critical plane

MSSRP:

Maximum shear strain range plane

MNSRP:

Maximum normal strain range plane

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Acknowledgements

This research was supported by the National Natural Science Foundation of China under the Contract Number 51875089. The authors would like to express special thanks to Prof. C. G. Soares at Universidade de Lisboa for his considerable help. The authors also appreciate the reviewers for their constructive comments on this paper.

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Authors and Affiliations

  1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, People’s Republic of China

    Jie Zhou, Hong-Zhong Huang, Yan-Feng Li & Junyu Guo

  2. Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, People’s Republic of China

    Jie Zhou, Hong-Zhong Huang, Yan-Feng Li & Junyu Guo

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  1. Jie Zhou
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  2. Hong-Zhong Huang
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Correspondence to Hong-Zhong Huang.

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Zhou, J., Huang, HZ., Li, YF. et al. A framework for fatigue reliability analysis of high-pressure turbine blades. Ann Oper Res 311, 489–505 (2022). https://doi.org/10.1007/s10479-019-03203-4

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