The Randomness of Fatigue and Fracture Behaviour in Metallic Materials and Mechanical Structures

Pineau, A.

doi:10.1007/978-3-7091-2780-3_4

Cited by 4 publications

(2 citation statements)

References 58 publications

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“…Here, β is a set of parameters which define the loading conditions, such as the applied strain range, strain ratio, temperature; w From traditional fatigue experiments, it is well known that scatter in fatigue life is dependent on the applied strain range showing an increasing trend with decreasing applied strain range [57]. Therefore, it is more appropriate to use a subset of the experimental fatigue life dataset at a higher applied strain range to calibrate W p critical to result in less uncertainty.…”

Section: Bayesian Calibration Of the Critical Plastic Strain Energy D...mentioning

confidence: 99%

“…First, it has not been investigated whether a single critical stored energy density value can reasonably predict fatigue lives at multiple loading regimes, including low and high cycle fatigue and different stress/strain ratios. Second, experimental fatigue life data at a given stress/strain amplitude show a scatter which is typically observed to be (i) lognormally distributed [57] and (ii) increasing with decreasing applied stress/strain amplitude. A microstructure-sensitive framework should be able to capture both trends in the scatter; however, this has not been verified systematically.…”

Section: Introductionmentioning

confidence: 99%

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Microstructure-sensitive critical plastic strain energy density criterion for fatigue life prediction across various loading regimes

et al. 2020

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In the present work, we postulate that a critical value of the stored plastic strain energy density (SPSED) is associated with fatigue failure in metals and is independent of the applied load. Unlike the classical approach of estimating the (homogenized) SPSED as the cumulative area enclosed within the macroscopic stress–strain hysteresis loops, we use crystal plasticity finite element simulations to compute the (local) SPSED at each material point within polycrystalline aggregates of a nickel-based superalloy. A Bayesian inference method is used to calibrate the critical SPSED, which is subsequently used to predict fatigue lives at nine different strain ranges, including strain ratios of 0.05 and −1, using nine statistically equivalent microstructures. For each strain range, the predicted lives from all simulated microstructures follow a lognormal distribution. Moreover, for a given strain ratio, the predicted scatter is seen to be increasing with decreasing strain amplitude; this is indicative of the scatter observed in the fatigue experiments. Finally, the lognormal mean lives at each strain range are in good agreement with the experimental evidence. Since the critical SPSED captures the experimental data with reasonable accuracy across various loading regimes, it is hypothesized to be a material property and sufficient to predict the fatigue life.

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Section: Bayesian Calibration Of the Critical Plastic Strain Energy D...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Microstructure-sensitive critical plastic strain energy density criterion for fatigue life prediction across various loading regimes

et al. 2020

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Creep–fatigue–oxidation interactions in a 9Cr–1Mo martensitic steel. Part III: Lifetime prediction

Fournier

Sauzay

Caës

et al. 2008

International Journal of Fatigue

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Nonlinear differential equation for fatigue damage evolution, using a micromechanical model

Altus

2002

Mechanics of Materials

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The Randomness of Fatigue and Fracture Behaviour in Metallic Materials and Mechanical Structures

Cited by 4 publications

References 58 publications

Microstructure-sensitive critical plastic strain energy density criterion for fatigue life prediction across various loading regimes

Microstructure-sensitive critical plastic strain energy density criterion for fatigue life prediction across various loading regimes

Creep–fatigue–oxidation interactions in a 9Cr–1Mo martensitic steel. Part III: Lifetime prediction

Nonlinear differential equation for fatigue damage evolution, using a micromechanical model

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