Influence of natural defects on the fatigue limit of a cast Al-Si alloy

Fatigue properties of AlSi10Mg produced by Additive Layer Manufacturing

“…The fatigue limit is then calculated by considering a threshold value =2 MPa × m 1/2 obtained from da-dN/ΔK experimental curves test on a P2-Z-MA sample. Figure 15 exhibits the fatigue limit as a function of the defect size and compared to conventional cast alloy [18,24,25,27,28,42,43]. Figure 15 suggests that the deviation from LEFM predictions is larger at smaller defect sizes, meaning that small natural defects such as those encountered in this study cannot be considered as a crack propagating in mode I with a long crack threshold of of 2 MPa × m 1/2 .…”

“…Arm Spacing (DAS) was observed to be between 0.5 and 2 µm, which is significantly smaller than the characteristic SDAS parameter in cast Al-Si alloys (30 to 100 µm depending on the cooling rate). Previous studies have shown that this parameter has a large influence on the fatigue behavior [25,[27][28][29][30][31]. According to Wang et al [31], in the absence of defects a refined SDAS leads to the high fatigue life.…”

Effect of build orientation on the fatigue properties of as-built Electron Beam Melted Ti-6Al-4V alloy

“…It has been shown above that, for the material studied here, the cracks leading to failure initiate from notch-like surface defects with a crack-like shape. Several approaches can be considered 205 for building the Kitagawa-Takahashi diagram (see for example [53]). The formulation based on the El Haddad's empirical parameter a 0 [54] is being used here:…”

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

“…It should be noted that the proposed probabilistic model assumes that the porosity controls the fatigue behavior of the material. This assumption is based on many experimental studies that showed that usually the fatigue failures were initiated from a pore close to the surface (El Khoukhi et al 2019 ;Le et al 2016 ;Rotella et al 2017 ;Murakami 1991). The proposed method presents many advantages and some drawbacks.…”

“…In terms of fatigue behavior, experience shows that the most critical defect in a structure or specimen is usually the largest defect that exists close to the surface (Le et al 2016;Iben Houria et al 2015;Serrano-Munoz et al 2017;Boromei et al 2010;Mu et al 2014;Rotella et al 2017). To take this into account, only the subsurface volume that we called FAV should be considered.…”