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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Pomberger, Sebastian
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Topics
Publications (8/8 displayed)
- 2020Areal fatigue strength assessment of cast aluminium surface layerscitations
- 2020Validation Study on the Statistical Size Effect in Cast Aluminiumcitations
- 2020Fatigue strength assessment of heterogeneously textured sand-cast aluminium surface layers
- 2019Effect of Post Treatment on the Microstructure, Surface Roughness and Residual Stress Regarding the Fatigue Strength of Selectively Laser Melted AlSi10Mg Structurescitations
- 2019Evaluation of surface roughness parameters and their impact on fatigue strength of Al-Si cast materialcitations
- 2019On the Statistical Size Effect of Cast Aluminiumcitations
- 2019Short and long crack growth of aluminium cast alloyscitations
- 2017Randschichteffekte bei der Ermüdungsfestigkeitsbewertung von Aluminiumgussbauteilen
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article
On the Statistical Size Effect of Cast Aluminium
Abstract
Manufacturing process based imperfections can reduce the theoretical fatigue strength since they can be considered as pre-existent microcracks. The statistical distribution of fatigue fracture initiating defect sizes also varies with the highly-stressed volume, since the probability of a larger highly-stressed volume to inherit a potentially critical defect is elevated. This fact is widely known by the scientific community as the statistical size effect. The assessment of this effect within this paper is based on the statistical distribution of defect sizes in a reference volume V 0 compared to an arbitrary enlarged volume Vα. By implementation of the crack resistance curve in the Kitagawa-Takahashi diagram, a fatigue assessment model, based on the volume-dependent probability of occurrence of inhomogeneities, is set up, leading to a multidimensional fatigue assessment map. It is shown that state-of-the-art methodologies for the evaluation of the statistical size effect can lead to noticeable over-sizing in fatigue design of approximately 10%. On the other hand, the presented approach, which links the statistically based distribution of defect sizes in an arbitrary highly-stressed volume to a crack-resistant dependent Kitagawa-Takahashi diagram leads to a more accurate fatigue design with a maximal conservative deviation of 5% to the experimental validation data. Therefore, the introduced fatigue assessment map improves fatigue design considering the statistical size effect of lightweight aluminium cast alloys.