Modeling and Prediction of Surface Characteristics Impact on Fatigue Life of Additively Manufactured Ti-6Al-4V

The ability to accurately predict fatigue performance of additively manufactured materials is complex and important for their development and subsequent qualification for safety-critical aerospace applications. Improving predictability of fatigue behavior in AM Ti-6Al-4V as a function of surface condition (e.g. roughness, texture) and microstructure is investigated in this case study. Net shape samples fatigue tested with various surface conditions were used to elucidate structure-property relationships to predict fatigue behavior with low variability. Leveraging fractography and quantifiable descriptors of fatigue initiation sites to describe fatigue data showcases the ability to improve reliability in fatigue property predictions in AM Ti-6Al-4V. Applications to fatigue modeling will be discussed, including QuesTek’s ICME-based process-structure-property approach.