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Influence of fatigue–life data modelling on the estimated reliability of a structure subjected to a constant-amplitude loading

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  • Klemenc, Jernej

Abstract

This article describes how a selected material’s fatigue–life-curve model influences the calculated reliability of a structure subjected to a dynamic loading. A uni-axially loaded structural beam with a fully-reversal constant loading amplitude was considered. The reliability for a certain number of cycles-to-failure was calculated as a cross-section of the probability distributions representing the load–amplitude scatter and the scatter of the material’s fatigue–life curve. The probability density function (PDF) of the loading amplitude was modelled by a uniform and a Gaussian PDF. The scattered fatigue–life curve was modelled by a conditional two-parametric Weibull’s PDF. Its parameters were estimated using two procedures: (i) a two-phase procedure and (ii) a direct procedure. Following the two-phase procedure a conditional PDF of the number of cycles-to-failure was estimated first and then converted into a corresponding conditional PDF of the stress amplitudes. In the direct procedure the conditional PDF of the stress amplitudes was modelled directly from the fatigue–life data. The two procedures were tested on 12 sets of simulated fatigue–life data and a set of experimental fatigue–life data. The two fatigue–life-curve models for the experimental data set were applied for calculating the reliability for the selected structural beam.

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  • Klemenc, Jernej, 2015. "Influence of fatigue–life data modelling on the estimated reliability of a structure subjected to a constant-amplitude loading," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 238-247.
    • Handle: RePEc:eee:reensy:v:142:y:2015:i:c:p:238-247
    DOI: 10.1016/j.ress.2015.05.026
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    References listed on IDEAS

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    1. Sankararaman, S. & Mahadevan, S., 2013. "Separating the contributions of variability and parameter uncertainty in probability distributions," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 187-199.
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    Cited by:

    1. Khakifirooz, Marzieh & Fathi, Michel & Lee, I-Chen & Tseng, Sheng-Tsaing, 2023. "Neural ordinary differential equation for sequential optimal design of fatigue test under accelerated life test analysis," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    2. Gao, Haifeng & Wang, Anjenq & Zio, Enrico & Bai, Guangchen, 2020. "An integrated reliability approach with improved importance sampling for low-cycle fatigue damage prediction of turbine disks," Reliability Engineering and System Safety, Elsevier, vol. 199(C).

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