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.

An advanced lightweight design in cast aluminium alloys features complexly shaped geometries with strongly varying local casting process conditions. This affects the local microstructure in terms of porosity grade and secondary dendrite arm spacing distribution. Moreover, complex service loads imply changing local load stress vectors within these components, evoking a wide range of highly stressed volumes within different microstructural properties per load sequence. To superimpose the effects of bulk and surface fatigue strength in relation to the operating load sequence for the aluminium alloy EN AC 46200, a layer-based fatigue assessment concept is applied in this paper considering a non-homogeneous distribution of defects within the investigated samples. The bulk fatigue property is now obtained by a probabilistic evaluation of computed tomography results per investigated layer. Moreover, the effect of clustering defects of computed tomography is studied according to recommendations from the literature, leading to a significant impact in sponge-like porosity layers. The highly stressed volume fatigue model is applied to computed tomography results. The validation procedure leads to a scattering of mean fatigue life from −2.6% to 12.9% for the investigated layers, inheriting strongly varying local casting process conditions.

The fatigue strength of structural components is strongly affected by notches and imperfections. Both can be treated similarly, as local notch fatigue strength methods can also be applied to interior defects. Even though Murakami’s √area approach is commonly used in the threshold-based fatigue design of single imperfections, advanced concepts such as the Theory of Critical Distances (TCD), Notch Stress Intensity Factors (N-SIF), or Elastic Strain Energy Density (ESED) methods provide additional insight into the local fatigue strength distribution of irregularly shaped defects under varying uniaxial load vectors. The latter methods are based on the evaluation of the elastic stress field in the vicinity of the notch for each single load vector. Thus, this work provides numerically efficient methods to assess the local fatigue strength by means of TCD, N-SIF, and ESED, targeting the minimization of the required load case count, optimization of stress field evaluation data points, and utilization of multi-processing. Furthermore, the Peak Stress Method (PSM) is adapted for large opening angles, as in the case of globular defects. In detail, two numerical strategies are devised and comprehensively evaluated, either using a sub-case-based stress evaluation of the defect vicinity with an unchanged mesh pattern and varying load vector on the exterior model region with optimized load angle stepping or by the invocation of stress and strain tensor transformation equations to derive load angle-dependent result superposition while leaving the initial mesh unaltered. Both methods provide numerically efficient fatigue post-processing, as the mesh in the evaluated defect region is retained for varying load vectors. The key functions of the fatigue strength assessment, such as the evaluation of appropriate planar notch radius and determination of notch opening angle for the discretized imperfections, are presented. Although the presented numerical methods apply to planar simulation studies, the basic methodology can be easily expanded toward spatial fatigue assessment.

This study investigates the influence of pre-corrosion damage on the fatigue behavior of AlSi10MgMn high-pressure die-cast specimens, using the statistical distribution of corrosion depths. The analysis is conducted on two different surface conditions: an unmachined rough surface ($R_a=5.05$$\mathsf{\mu }\mathrm{m}$) and a machined, polished surface ($R_a=0.25$$\mathsf{\mu }\mathrm{m}$). For the unmachined specimens, the corrosive damage manifests as homogeneously spread localized corrosion, whereas the polished specimens exhibit less uniform but deeper corrosion. The average corrosion depth of the polished specimens is found to be slightly higher (313 $\mathsf{\mu }\mathrm{m}$ compared to 267 $\mathsf{\mu }\mathrm{m}$) with a broader depth distribution. Specimens are tested under a constant bending load amplitude in laboratory conditions at a stress ratio of $R=0$ until fracture. A fracture mechanics-based methodology is developed to assess the remaining fatigue life of corroded specimens, utilizing short and long crack fracture mechanical parameters derived from SENB specimens. This model incorporates a thickness reduction of the critical specimen cross-section based on the corrosion depth distribution and combines it with a small initial crack of the intrinsic defect size ($a_{eff}=14$$\mathsf{\mu }\mathrm{m}$). Regardless of the surface condition, using the most frequent corrosion depth for thickness reduction provides a good estimate of the long-life fatigue strength, while using the 90th percentile depth allows for a conservative assessment.