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.

Imperfections due to the manufacturing process can significantly affect the local fatigue strength of the bulk material in cast aluminium alloys. Most components possess several sections of varying microstructure, whereat each of them may inherit a different highly-stressed volume (HSV). Even in cases of homogeneous local casting conditions, the statistical distribution parameters of failure causing defect sizes change significantly, since for a larger highly-stressed volume the probability for enlarged critical defects gets elevated. This impact of differing highly-stressed volume is commonly referred as statistical size effect. In this paper, the study of the statistical size effect on cast material considering partial highly-stressed volumes is based on the comparison of a reference volume $V_0$ and an arbitrary enlarged, but disconnected volume $V_{\alpha }$ utilizing another specimen geometry. Thus, the behaviour of disconnected highly-stressed volumes within one component in terms of fatigue strength and resulting defect distributions can be assessed. The experimental results show that doubling of the highly-stressed volume leads to a decrease in fatigue strength of 5% and shifts the defect distribution towards larger defect sizes. The highly-stressed volume is numerically determined whereat the applicable element size is gained by a parametric study. Finally, the validation with a prior developed fatigue strength assessment model by R. Aigner et al. leads to a conservative fatigue design with a deviation of only about 0.3% for cast aluminium alloy.

Cast steel components are affected by manufacturing process-based imperfections, which severely limit their fatigue strength. In this work, the linear-elastic strain energy density concept is applied to assess the fatigue behaviour of bulk defect-afflicted components made of high-strength cast steel alloy G12MnMo7-4+QT. Based on analytical calculations, an energy-based design limit curve is derived which merges experimental results of notched and unnotched small–scale specimens into a statistically proven scatter band. The stress ratio dependency is also investigated. Moreover, a numerical methodology is introduced, which facilitates the energy-based fatigue assessment of complex spatial imperfections on the basis of radiographs. Validation of the established framework utilizing experimental results of defect-afflicted large–scale specimens leads to sound accordance of numerically and experimentally derived fatigue strength values, showing an average deviation of about only eight percent.

The fatigue strength of cast steel components is severely affected by manufacturing process-based bulk and surface imperfections. As these defect structures possess an arbitrary spatial shape, the utilization of local assessment methods is encouraged to design for service strength. This work applies the elastic–plastic strain energy density concept to study the fatigue strength properties of a high-strength cast steel alloy G12MnMo7-4+QT. A fatigue design limit curve is derived based on non-linear finite element analyses which merges experimental high-cycle fatigue results of unnotched and notched small-scale specimens tested at three different stress ratios into a unique narrow scatter band characterized by a scatter index of $1:T_{\Delta {\overline{W}}^{\left(t\right)}}=2.43$. A comparison to the linear–elastic assessment conducted in a preceding study reveals a significant improvement in prediction accuracy which is assigned to the consideration of the elastic–plastic material behaviour. In order to reduce computational effort, a novel approximation is presented which facilitates the calculation of the elastic–plastic strain energy density based on linear–elastic finite element results and Neuber’s concept. Validation of the assessment framework reveals a satisfying agreement to non-linear simulation results, showing an average root mean square deviation of only approximately eight percent in terms of total strain energy density. In order to study the effect of bulk and surface imperfections on the fatigue strength of cast steel components, defect-afflicted large-scale specimens are assessed by the presented elastic–plastic framework, yielding fatigue strength results which merge into the scatter band of the derived design limit curve. As the conducted fatigue assessment is based solely on linear–elastic two-dimensional simulations, the computational effort is substantially decreased. Within the present study, a reduction of approximately 400 times in computation time is observed. Hence, the established assessment framework presents an engineering-feasible method to evaluate the fatigue life of imperfective cast steel components based on rapid total strain energy density calculations.