Computational investigation on the combined effect of pore attributes on strain concentrators in metal additively manufactured materials
Metal additive manufacturing provides a pathway for creating highly optimized components. However, porosity continues to be a prevalent issue for fatigue performance despite best efforts in optimizing process parameters and postprocessing techniques. This work uses finite element analysis to conduct a parametric study to link various pore attributes (i.e., aspect ratio, orientation, and location) to strain concentration factors (SCF) under elastic/plastic deformation during uniaxial loading. Keyhole and lack-of-fusion pores are idealized by prolate and oblate ellipsoids, respectively. Each simulation of the parametric study assumes a single isolated pore in a Ti-6Al-4V material, modeled with J2-plasticity. A reduced-order model is developed to relate pore attributes to SCF, and then used to quantify the variability in SCF for a given experimentally characterized probability distribution of pore attributes. This reduced-order model can be used in a production environment to provide a first-order evaluation to rapidly screen sub-optimally performing components.