2019
DOI: 10.1016/j.ijfatigue.2019.05.005
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Probabilistic modeling of fatigue life distribution and size effect of components with random defects

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Cited by 133 publications
(51 citation statements)
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“…It can be seen that the largest pores have the lowest sphericity and a complex shape. This tendency has also been observed in the previous works [13,29,31]. According to Buffiere classification [29,31], this repartition tend to indicate the presence of shrinkage porosity and gas pores.…”
Section: Porosity Analysessupporting
confidence: 85%
“…It can be seen that the largest pores have the lowest sphericity and a complex shape. This tendency has also been observed in the previous works [13,29,31]. According to Buffiere classification [29,31], this repartition tend to indicate the presence of shrinkage porosity and gas pores.…”
Section: Porosity Analysessupporting
confidence: 85%
“…It is known that the scatter is an intrinsic feature in fatigue . Therefore, the probabilistic fatigue S ‐ N curve has become an important tool to evaluate and predict the fatigue strength of engineering structural materials.…”
Section: Resultsmentioning
confidence: 99%
“…It is known that the scatter is an intrinsic feature in fatigue. [46][47][48] Therefore, the probabilistic fatigue S-N curve has become an important tool to evaluate and predict the fatigue strength of engineering structural materials. Figure 8 shows the lifetime trends from standard specimens made of G20Mn5 cast steel and MAG welded joints.…”
Section: Hcf Life Curvesmentioning
confidence: 99%
“…It is indicated that FEA combined with cyclic plasticity model can yield more accurate results. [17][18][19] The user-defined material subroutine of FEA software (such as UMAT in ABAQUS) provides designers a good choice to establish a sufficiently accurate material model. Various models 20 have been proposed to describe material's nonlinear elastic-plastic behavior under cyclic loading.…”
Section: Cyclic Plasticity Modelmentioning
confidence: 99%