EL KHOUKHI, Driss; MOREL, Franck; SAINTIER, Nicolas; BELLETT, Daniel; OSMOND, Pierre; LE, Viet-Duc

doi:10.1016/j.ijfatigue.2021.106177

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EL KHOUKHI, Driss
Institut de Mécanique et d'Ingénierie [I2M]

MOREL, Franck

SAINTIER, Nicolas
Institut de Mécanique et d'Ingénierie [I2M]

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International Journal of Fatigue. 2021-02-01p. 106177

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In this study, a probabilistic model based on Monte-Carlo theory is applied to predict the fatigue behavior of cast aluminum alloys. The objective of the proposed approach is to investigate the effect of porosity (i.e. the defect size distribution and spatial density) on the fatigue strength and its associated scatter for uniaxial fatigue loads with the load ratio R = 0.1. The proposed model is applied to two cast aluminum alloys with very different defect characteristics. The results for these two alloys confirm that the model can be used to predict the average fatigue strength with a relative error <5%. It also accurately reproduces the experimentally observed trends concerning the scatter in fatigue strength. The scatter is underestimated but is of the same order of magnitude as the experimental values. It is believed that this is because the proposed model considers that the porosity is the only source of scatter. It is demonstrated that the model is well adapted for the prediction of the volume or scale effect in fatigue. This approach can also be used to estimate the Representative Volume Element in Fatigue for cast aluminum alloys.< Réduire

Mots clés en anglais

High cycle fatigue

Cast aluminum alloys

Probabilistic model

Representative Volume Element (RVE)

Size effect in fatigue

Highly stressed volume

Scatter in fatigue strength

Casting defect population

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Probabilistic modeling of the size effect and scatter in High Cycle Fatigue using a Monte-Carlo approach: role of the defect population in cast aluminum alloys

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