2016
DOI: 10.1016/j.msea.2016.05.117
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Creep-fatigue behavior of turbine disc of superalloy GH720Li at 650 °C and probabilistic creep-fatigue modeling

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Cited by 59 publications
(29 citation statements)
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“…That is the fatigue contribution of hold-time cycle. Apart from this geometrical mechanism, creep-fatigue interaction may occur [40][41][42]. Indeed, it was evidenced in other Ni based superalloys [40,41] that the fatigue behaviour is strongly influenced by the prior application of a creep loading, revealing a load history effect.…”
Section: Crack Growth Mechanism Under Hold-time Conditions Considerinmentioning
confidence: 99%
See 1 more Smart Citation
“…That is the fatigue contribution of hold-time cycle. Apart from this geometrical mechanism, creep-fatigue interaction may occur [40][41][42]. Indeed, it was evidenced in other Ni based superalloys [40,41] that the fatigue behaviour is strongly influenced by the prior application of a creep loading, revealing a load history effect.…”
Section: Crack Growth Mechanism Under Hold-time Conditions Considerinmentioning
confidence: 99%
“…Apart from this geometrical mechanism, creep-fatigue interaction may occur [40][41][42]. Indeed, it was evidenced in other Ni based superalloys [40,41] that the fatigue behaviour is strongly influenced by the prior application of a creep loading, revealing a load history effect. On the opposite, a prior fatigue loading does not influence the creep behaviour [41], which is supported by the observed steady creep crack growth behaviour (see Fig.…”
Section: Crack Growth Mechanism Under Hold-time Conditions Considerinmentioning
confidence: 99%
“…This combined effect often leads to a significant scatter of HPT disc performance . According to this, methods for fatigue reliability analysis have been developed to take into account different sources of uncertainty resulting from material properties, microstructures, and loads . Among them, Zhao et al introduced a strain load‐strength interference model, in which the fatigue strength coefficient σf and ductility coefficient εf are quantified by using normal/Weibull distributions.…”
Section: Introductionmentioning
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%