Process-specific Microstructure-sensitive Modeling of Fatigue in Additively Manufactured Ti-6Al-4V Alloys

Thanks to its high strength-to-weight ratio and corrosion resistance, Ti-6Al-4V has gained a lot of attention in additive manufacturing (AM) of complex parts with aerospace and medical applications. The realistic loading condition in these applications is mostly cyclic, thus fatigue failure is the main mode of failure. On the other hand, due to presence of local defects in the current state of AM materials, the main challenge with AM of metallic parts is their fatigue resistance and durability, being much lower than the conventional counterparts. In this study, a simplified microstructure-sensitive fatigue (MSF) approach was developed to model the fatigue life of AM Ti-6Al-4V specimens by incorporating microstructural features and defect properties, such as grain size, pore size and pores nearest neighbors. The studied AM methods include Laser Engineered Net Shaping (LENS), Electron Beam Melting (EBM), and Selective Laser Melting (SLM). Each of these processes use different approaches in constructing the three-dimensional object, yielding in different microstructure of the final part. For this work, microstructural data were collected from previous experimental studies. Scanning Electron Microscopy (SEM) images were used to examine the fracture surfaces of the AM specimens and determine the defects responsible for fatigue failure. With an emphasis on the microstructurally small crack growth, model parameters were calibrated for fatigue data for different AM processes, while keeping process-independent parameters as constant. The results showed that a simplified MSD fatigue model with limited number of process-dependent governing parameters can be calibrated for each set of data.