Selective Laser Melting (SLM) process is an Additive Manufacturing (AM) technique that allows producing metallic parts of any kind of geometry with densities greater than 99.5%. Complex shapes lead however to notches with different radii of curvature that may reduce load bearing capacities. This work is aimed to assess the fatigue strength of Ti-6Al-4V blunt V-notched samples produced by SLM. Results were compared with those of the corresponding smooth samples and Environmental Scanning Electron Microscopy (ESEM) have been used to investigate the fracture surface of the broken samples in order to identify crack initiation points and fracture mechanisms. Finally, the strain energy density approach was used to evaluate the critical radius value. Despite the observed fatigue strength reduction induced by the notch, samples showed a sufficient low notch sensitivity that it was not possible to define a critical radius for the material analysed. © 2017 Elsevier Ltd

Fatigue strength of blunt V-notched specimens produced by selective laser melting of Ti-6Al-4V

Berto Filippo;
2018

Abstract

Selective Laser Melting (SLM) process is an Additive Manufacturing (AM) technique that allows producing metallic parts of any kind of geometry with densities greater than 99.5%. Complex shapes lead however to notches with different radii of curvature that may reduce load bearing capacities. This work is aimed to assess the fatigue strength of Ti-6Al-4V blunt V-notched samples produced by SLM. Results were compared with those of the corresponding smooth samples and Environmental Scanning Electron Microscopy (ESEM) have been used to investigate the fracture surface of the broken samples in order to identify crack initiation points and fracture mechanisms. Finally, the strain energy density approach was used to evaluate the critical radius value. Despite the observed fatigue strength reduction induced by the notch, samples showed a sufficient low notch sensitivity that it was not possible to define a critical radius for the material analysed. © 2017 Elsevier Ltd
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/1654377
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