Modeling Fatigue Behavior of 3D Printed Titanium Alloys

Abstract

Repeated loading and unloading cycles lead to the formation of strain in the material which causes initiation of the crack formation this phenomenon is called fatigue. Fatigue properties are critical for structures subject to cyclic load; hence fatigue analysis is used to predict the life of the material. Fatigue analysis plays an important role in optimizing the design of the 3D printed material and predicting the fatigue life of the 3D printed component. The main objective of this thesis is to predict the fatigue behavior of different microstructures of Ti-64 titanium alloy by using the PRISMS-Fatigue open-source framework. To achieve this goal Ti-64 microstructure models were created using programming scripts, then the structures were exported to a finite element visualization software package, with all the required properties embedded in the pipeline. The PRISMS-Fatigue framework is used to conduct a fatigue analysis on 3D printed materials, using the Fatigue Indicator Parameters (FIP), which measure the driving force of fatigue crack formation in the microstructurally small crack growth. Three different microstructures, i.e., cubic equiaxed, random equiaxed, and rolled equiaxed microstructures, are analyzed. The FIP results show that the cubic equiaxed grains have the best fatigue resistance due to their isotropic structural characteristics. Additionally, the grain size effect using 1 and 10 micrometers is investigated. The results show that the 1 micrometer grain size cubic equiaxed microstructure has a better fatigue resistance because as grains are small and they have a higher mechanical strength.