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Structural alloys are largely employed in key industrial sectors and their demand is predicted to rise rapidly for the next decades. Most of these materials require a large amount of energy for extraction and manufacturing, which causes the emission of greenhouse gases and other pollutants. Therefore, strategies for improving the sustainability of structural metallic alloys are urgently needed.
Additive Manufacturing (AM), in particular Laser Powder Bed Fusion (PBF-LB/M), aims to be a sustainable manufacturing process, as it allows the build-up of complex geometry in near net-shape from 3D models, while minimizing material waste and the energy required for the process and post-process treatments.
Nevertheless, the application of additively manufactured parts in structural safety-relevant applications is still hindered by the poor fatigue performance. The cause of this has been mainly attributed to the presence of manufacturing defects and surface roughness. Therefore, a huge effort has been made to optimize the process parameters and to introduce post-process treatments to minimize the defect content. However, material flaws cannot be fully eliminated, but these can be considered in a damage tolerance framework for the prediction of the fatigue performance of additively manufactured metallic materials, which is essential for part design and qualification.
This work aims at presenting different modelling strategies for the prediction of the fatigue limit of AM metals. Simple empirical models and more complex models based on fatigue short crack propagation are proposed. The investigated material is an AlSi10Mg alloy fabricated by PBF-LB/M and subjected to two different low-temperature heat-treatments (265°C for 1 h and 300°C for 2h). The results show that the models can provide good approximation of the fatigue limits and help in the interpretation of the scatter of fatigue data.
Damage tolerance counts as one of the most widespread approach to fatigue assessment and surely as one of the most promising in understanding the process-structure-property-performance relationships in additively manufactured metallic materials. Manufacturing defects, surface roughness, microstructural features, short and long crack fatigue propagation, residual stresses and applied loads can be taken into consideration in a fracture mechanics-based fatigue assessment. Many aspects are crucial to the reliable component life prediction. Among those a prominent role is played by an accurate measurement and modelling of the short crack fatigue behavior, and reliable statistical characterization of defects and residual stresses.
This work aims at addressing the issues related to both experimental testing, fatigue and fatigue crack propagation, and fracture mechanics-based modelling of fatigue lives. Examples will be provided on an additively manufactured AISI 316 L.