2004
DOI: 10.1016/j.ijfatigue.2003.08.017
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Fatigue life under non-Gaussian random loading from various models

Abstract: is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. AbstractFatigue test results on the 10HNAP steel under constant amplitude and random loading with non-Gaussian probability distribution function, zero mean value and wide-band frequency spectrum have been used to compare the life time estimation of the models proposed by Bannantine, Fatemi-Socie, Socie, Wang-Brown, Morel and Łagoda-Macha. Except the Morel prop… Show more

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Cited by 59 publications
(42 citation statements)
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References 13 publications
(37 reference statements)
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“…, non-proportional(Lagoda et al, 1999;Lagoda 2001;Banvillet et al, 2004;Itoh et alCritical plane is defined as the plane experiencing the maximum damage.…”
mentioning
confidence: 99%
“…, non-proportional(Lagoda et al, 1999;Lagoda 2001;Banvillet et al, 2004;Itoh et alCritical plane is defined as the plane experiencing the maximum damage.…”
mentioning
confidence: 99%
“…However as illustrated in Fig. 5, the shear stress may be out-of-phase with all the three normal components and this warrants special attention when changes in the history of stress components are to be analysed [37][38][39]. Fig.…”
Section: Fatigue Analysismentioning
confidence: 99%
“…Thus, appropriate treatment of uncertainty in fatigue design has become a significant topic with widespread interest [17]- [24]. Prior work on statistical or probabilistic aspects of fatigue includes modeling of the variability in material properties (e.g., elastic modulus, fracture toughness, yield strength) [6], [17], [25]- [27], equivalent initial flaw size (EIFS) [21], [28]- [30], microstructures as well as defects [31]- [35], stress-life data [36]- [39], and under multiaxial conditions [40]- [45]. Generally, two aspects need to be addressed for probabilistic fatigue design: a valid PoF-based fatigue model and a probabilistic framework for treating both the random material variables and the uncertainty on model parameters in the fatigue model [46], which has been reviewed in detail recently by Pineau et al [47].…”
Section: Introductionmentioning
confidence: 99%