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• Post-heat treated LPBF 316L steel exhibits a cyclic hardening followed by non-saturated cyclic softening stage. • The cyclic deformation is primarily influenced by the evolution of dislocation density and dislocation patterns. • Anisotropy in fatigue life is attributed to the anisotropic microstructure, defects and yield strength. • Ratchetting strain and ratchetting strain rate are highly dependent on the applied stress levels. This study has investigated the cyclic deformation and ratchetting-fatigue interaction of 316L stainless steel fabricated by laser powder bed fusion (LPBF) and subjected to a 900 °C/2 h post-heat treatment, considering both the vertical and horizontal orientations. Strain- and stress-controlled low cycle fatigue (LCF) tests are conducted to explore the cyclic deformation and the effects of the mean stress and stress amplitude on the fatigue life and ratchetting deformation. A detailed analysis of the cyclic deformation mechanism is conducted through X-ray microtomography and transmission electron microscope (TEM) observations. The results show that post-heat treated LPBF 316L steel exhibits cyclic hardening followed by a non-saturated cyclic softening stage. This behavior is attributed to the evolution of dislocation density and dislocation patterns, and the formation of surface cracks. The ratchetting strain and its rate are sensitive to the mean stress and stress amplitude. The fatigue lives of vertically built specimens are slightly higher under strain-controlled loading conditions, but significantly lower under stress-controlled loading conditions than those of horizontally built ones. Furthermore, ratchetting deformation can promote fatigue damage, resulting in a reduction in fatigue life. [ABSTRACT FROM AUTHOR]

Electron beam melting (EBM) is a promising three‐dimensional printing technology for the fabrication of components with high complexity and freedom of structural design. However, the major limit for its wider industrial applications is to preclude manufacturing the large‐scale part in one piece. It is because the part size is largely limited by the enclosed vacuum chamber. An alternative option is the use of welding to join EBM‐processed subparts together. In this study, fatigue crack growth (FCG) rate and high‐cycle fatigue (HCF) performance were measured for both EBM‐processed Ti–6Al–4V alloy and its welded joints. An X‐parameter model was then proposed to correlate stress amplitude and geometric parameters (location, size, and shape) of the critical defects at the crack origins with fatigue life. Research framework and result from this work are expected to serve a reference for the defect‐based fatigue life evaluation of welded parts individually manufactured using additive manufacturing. [ABSTRACT FROM AUTHOR]

• Gradient microstructure and mechanical properties were observed in S38C axles. • Compressive residual stress was rebuilt by a proportional integral iterative method. • Crack arrest happens due to compressive residual stresses to enhance the fatigue life. • The critical non-propagating crack depth at the axle body is 4 mm. The remaining life assessment of damaged railway axles is an important topic primarily because of extending the maintenance interval. However, the fatigue resistance of surface-strengthened materials is extremely challenging due to the gradient-distributed microstructure, tensile properties, and residual stresses across the axle. To elucidate the fatigue cracking behaviors of induction-hardened S38C railway axles, the residual stress field ranging from −400 MPa to zero near the axle surface were rebuilt using a new unit pressure and proportional-integral approach (UPA) instead of complicated heat simulation. The fatigue life of full-scale S38C railway axles was then predicted by employing a real vertical load spectrum. The results show that in the presence of a 4.0-mm-deep crack, the remaining life of a damaged axle with compressive residual stresses is more than three times that of an axle without compressive residual stresses. In addition, the crack front is surrounded by a compressive stress field when the crack depth does not exceed 4.0 mm, which is the probable detection limit for the maximum crack depth extension. The present work is expected to serve a basic reference for the optimization and extension of the inspection intervals for induction-hardened S38C railway axles. [ABSTRACT FROM AUTHOR]

• Based on the critical defects data measured by SEM, a machine learning model is established to predict the fatigue life, and the model is in good agreement with the experimental data. • Use the trained machine learning model to quantitatively analyze the importance of critical defects characteristics on fatigue life and analyze the effect of aspect ratio on fatigue life. • The ML model suggests that circular defects of the same area to be less potent than elongated defects of the same area in terms of the HCF lifetime. Given their preponderance and propensity to initiate fatigue cracks, understanding the effect of processing defects on fatigue life is a significant step towards the wider application of additively manufactured (AM) parts. Here a novel machine learning (ML) based approach has been developed to predict the fatigue life of laser powder bed fused AlSi10Mg alloy. The four most important parameters, treferred to here as the Wu-Withers parameters, were found to be the applied stress and the projected area, location and morphology of the critical defects. It was found that an Extreme Gradient Boosting model was able to predict the fatigue lives with high accuracy with the importance of these characteristics in limiting fatigue life ranked in the order given above. The model was able to predict the very different lives of samples tested parallel and perpendicular to the build direction in terms of these four W-W parameters indicating that microstructure was of minor importance. In particular the large projected area of the defects on the crack plane when testing parallel to the build direction was found to be primarily responsible for the shorter lives observed for this testing orientation. The fatigue lives were adequately predicted by the more general two variable (stress and projected area) Murakami model, and even more closely predicted by an empirical model (using essentially the same four W-W parameters) for which the ML model corroborated the empirical dependences. [Display omitted] [ABSTRACT FROM AUTHOR]

Modern railway axles frequently experience external damages, which results in deteriorated fatigue performance and a need for careful maintenance. Herein, the shot peening (SP)-induced strengthening of high-speed railway axle EA4T alloy or 25CrMo4 steel subjected to foreign object damage (FOD) and the effect of this strengthening on fatigue strength were elucidated using the electron backscattered diffraction, transmission electron microscopy, X-ray diffraction and nanoindentation techniques. An improved backward statistical inference method was employed to construct probabilistic fatigue S-N curves based on the results of high cycle fatigue test and thus derive reliable endurance limits for unFODed and FODed specimens subjected or not subjected to SP treatment. Eventually, El-Haddad model and the Wöhler curve were combined with the modified Miner damage accumulation theory to develop a three-dimensional Kitagawa-Takahashi diagram in the nominal stress framework. The above diagram was shown to well correlate the fatigue damage accumulation and the critical FOD defect size of externally impacted railway axles with knee-point life and fatigue S-N curve slope. Unlabelled Image • Foreign object damages lead to considerable decrease in the fatigue performance of railway axle EA4T steel. • The shot peening induces the increased fatigue crack resistance of railway axle subjected to external damages. • The probabilistic fatigue S N curve was gained by the newly-developed improved backward statistical method. • The 3D model (damage-defect-life) for the fatigue damage assessment of damaged axle was developed. [ABSTRACT FROM AUTHOR]