Effect of local microstructure on fatigue and related failure mechanisms in AlSi-castings

Oberreiterr, Matthias; Stoschka, Michael; Horvath, Michael; Fladischer, Stefan

doi:10.1016/j.prostr.2022.12.265

Cited by 1 publication

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“…Table 3 gives an overview of the high cycle fatigue tests with the related manufacturing and post-treatment coding. It should be mentioned that a part of these summarized results was obtained in preceding work by the authors [ 115 , 120 , 121 ].…”

Section: Methodsmentioning

confidence: 76%

Effect of Surface Finishing State on Fatigue Strength of Cast Aluminium and Steel Alloys

et al. 2023

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The endurance limit of structural mechanical components is affected by the residual stress state, which depends strongly on the manufacturing process. In general, compressive residual stresses tend to result in an increased fatigue strength. Post-manufacturing processes such as shot peening or vibratory finishing may achieve such a compressive residual stress state. But within complex components, manufacturing-process-based imperfections severely limit the fatigue strength. Thus, the interactions of imperfections, residual stress state and material strength are key aspects in fatigue design. In this work, cast steel and aluminium alloys are investigated, each of them in vibratory finished and polished surface condition. A layer-based fatigue assessment concept is extended towards stable effective mean stress state considering the elastic–plastic material behaviour. Murakami’s concept was applied to incorporate the effect of hardness change and residual stress state. Residual stress relaxation is determined by elastic–plastic simulations invoking a combined hardening model. If the effective stress ratio within the local layer-based fatigue strength is evaluated as critical distance value, a sound calculation of fatigue strength can be achieved. Summing up, the layer-based fatigue strength design is extended and features an enhanced understanding of the effective stabilized mean stress state during cyclic loading.

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Section: Methodsmentioning

confidence: 76%