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Fatigue reliability based on residual strength model with hybrid uncertain parameters

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Abstract

The aim of this paper is to evaluate the fatigue reliability with hybrid uncertain parameters based on a residual strength model. By solving the non-probabilistic set-based reliability problem and analyzing the reliability with randomness, the fatigue reliability with hybrid parameters can be obtained. The presented hybrid model can adequately consider all uncertainties affecting the fatigue reliability with hybrid uncertain parameters. A comparison among the presented hybrid model, non-probabilistic set-theoretic model and the conventional random model is made through two typical numerical examples. The results show that the presented hybrid model, which can ensure structural security, is effective and practical.

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References

  1. Gao, Z.T., Xiong, J.J.: The Reliability of Fatigue. Beijing University of Aeronautics and Astronautics Press, Beijing (2000) (in Chinese)

    Google Scholar 

  2. Talreja, R., Weibull, W.: Probability of fatigue failure based on residual strength. In: Proceedings of the Fourth International Conference on Fracture, Waterloo, Ontario, Canada, United States, 1125–1131 (1977)

  3. Kececioglu, D.: Fatigue prevention and reliability. In: Proc. ASME 285–309 (1978)

  4. Talreja, R.: Fatigue reliability under multiple amplitude loads. Eng. Fract. Mech. 11(4), 839–849 (1979)

    Article  Google Scholar 

  5. Lü, H.B., Yao, W.X.: Residual strength model of elements’ fatigue reliability evaluation. Acta Aeronaut. Astronaut. Sin. 21(1), 74–77 (2000) (in Chinese)

    Google Scholar 

  6. Bucher, C.G., Bourgund, U.: A fast and efficient response surface approach for structural reliability problem. Struct. Saf. 7(1), 57–66 (1990)

    Article  Google Scholar 

  7. Yao, W.X., Himmel, N.: Statistical analysis of fatigue data from fatigue life and corresponding truncated residual strength. Int. J. Fatigue 21(6), 581–585 (1999)

    Article  Google Scholar 

  8. Sørensen, J.D., Frandsen, S., Tarp-Johansen, N.J.: Effective turbulence models and fatigue reliability in wind farms. Probabilist. Eng. Mech. 23(4), 531–538 (2008)

    Article  Google Scholar 

  9. Teixeira, A.P., Guedes Soares, C.: Reliability analysis of a tanker subjected to combined sea states. Probabilist. Eng. Mech. 24(4), 493–503 (2009)

    Article  Google Scholar 

  10. Elishakoff, I.: Essay on uncertainties in elastic and viscoelastic structures: from AM Freudenthal’s criticisms to modern convex modeling. Comput. Struct. 56(6), 871–895 (1995)

    Article  MATH  Google Scholar 

  11. Ben-Haim, Y., Elishakoff, I.: Convex Models of Uncertainty in Applied Mechanics. Elsevier Science, Amsterdam (1990)

    MATH  Google Scholar 

  12. Elishakoff, I.: A new safety factor based on convex modeling. In: Ayyub, B.M., Gupta, M.M. eds. Uncertainty Modeling and Analysis: Theory and Applications, North-Holland, Amsterdam, 145–171 (1994)

  13. Ben-Haim, Y.: A non-probabilistic concept of reliability. Struct. Saf. 14(4), 227–245 (1994)

    Article  Google Scholar 

  14. Ben-Haim, Y.: Robust Reliability in the Mechanical Sciences. Springer-Verlag, Berlin (1996)

    Book  MATH  Google Scholar 

  15. Ben-Haim, Y.: Design certification with information-gap uncertain. Struct. Saf. 21(3), 269–289 (1999)

    Article  Google Scholar 

  16. Guo, S.X., Lü, Z.Z., Feng, Y.S.Z: A non-probabilistic model of structural reliability based on interval analysis. Chinese J. Comput. Mech. 18(1), 56–60 (2001) (in Chinese)

    Google Scholar 

  17. Guo, S.X., Lü, Z.Z.: A procedure of the analysis of nonprobabilistic reliability of structural systems. Chinese J. Comput. Mech. 19(3), 332–335 (2002) (in Chinese)

    Google Scholar 

  18. Wang, X.J., Qiu, Z.P.: Robust reliability of structural vibration. J. Beijing Univ. Aeronaut. Astronaut. 29(11), 1006–1010 (2003) (in Chinese)

    MathSciNet  Google Scholar 

  19. Qiu, Z.P., Mueller, P.C.: A. Frommer, The new nonprobabilistic criterion of failure for dynamical systems based on convex models. Math. Comput. Model 40(1–2), 201–215 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  20. Wang, X.J., Qiu, Z.P., Elishakoff, I.: Non-probabilistic settheoretic model for structural safety measure. Acta. Mech. 198(1–2), 51–64 (2008)

    Article  MATH  Google Scholar 

  21. Wang, J., Qiu, Z.P.: The reliability analysis of probabilistic and interval hybrid structural system. Appl. Math. Model. 34(11), 3648–3658 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  22. An, W.G., Cai, Y.L., Chen, W.D.: Reliability Analysis and Optimization Design of Random Structure System. Press of Harbin Engineering University, Harbin (2005) (in Chinese)

    Google Scholar 

  23. Moore, R.E.: Methods and Applications of Interval Analysis. Prentice-Hall, London (1979)

    Book  MATH  Google Scholar 

  24. Alefeld, G., Herzberger, J.: Introductions to Interval Computations. Academic Press, New York (1983)

    Google Scholar 

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Correspondence to Jun Wang.

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The project was supported by the National Natural Science Foundation of China (90816024, 10872017 and 10876100), the 111 Project (B07009) and the Innovation Foundation of Beihang University for PhD Graduates.

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Wang, J., Qiu, ZP. Fatigue reliability based on residual strength model with hybrid uncertain parameters. Acta Mech Sin 28, 112–117 (2012). https://doi.org/10.1007/s10409-011-0536-7

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