Computational prediction of the fatigue behavior of additively manufactured porous metallic biomaterials

The mechanical behavior of additively manufactured porous biomaterials has recently received increasing attention. While there is a relatively large body of data available on the static mechanical properties of such biomaterials, their fatigue behavior is not yet well-understood. That is partly because systematic study of the fatigue behavior of these porous biomaterials is time-consuming and expensive due to the large number of involved factors. In the current study, we propose a computational approach based on finite element method that could be used to predict the fatigue behavior of porous biomaterials given their type of repeating unit cell, dimensions of the unit cell, and S-N curve of the parent material. We applied the proposed approach to predict the fatigue behavior of porous titanium alloy (Ti-6Al-4V) biomaterials manufactured using selective laser melting based on the rhombic dodecahedron unit cell and compared our computational results with experimental observations from one of our recent studies. The evolution of the displacement, elastic modulus, and number of failed struts vs. the number of loading cycle followed a two-stage pattern. In the first stage, there was a relatively slow rate of change in the above-mentioned variables, while they changed very rapidly in the second stage. That compares to the behavior observed in our experimental study. The computationally predicted S-N curve well matched the experimental observations for stress levels not exceeding 60% of the yield stress of the porous structures. For higher stress levels, the presented approach substantially underestimated the fatigue life of the porous structures. The effects of the irregularities caused by the additive manufacturing process on the fatigue behavior of the porous structures were also studied. It was found that those irregularities substantially decrease the fatigue life particularly for lower stress levels.