Location Specific Fatigue Predictions for Additively Manufactured Aerospace Alloys

Tuesday, October 17, 2023: 11:10 AM
338 (Huntington Convention Center)
Dr. Gary Whelan , QuesTek Innovations LLC, Evanston, IL
Mr. Sam Sorkin , QuesTek Innovations LLC, Evanston, IL
Dr. Kevin Chu , QuesTek Innovations LLC, Evanston, IL
Dr. Jiadong Gong , QuesTek Innovations LLC, Evanston, IL
QuesTek’s ICMD® platform is an integrated digital modeling and simulation workspace that can be used to design and optimize for additive manufacturing. AM provides several key advantages compared with traditional manufacturing for structural aerospace components such as complex achievable geometries enabling features like internal cooling veins to increase the achievable operating temperature, or lattice structures to minimize weight. Additionally, AM can enable supply chain resilience, preventing reliance on legacy casting tooling that may no longer be available, and part reduction by combining several components into one, 3D printed component, to reduce system complexity. A major barrier to the adoption of AM is the unique set of materials challenges associated with this advanced manufacturing technique. The track-by-track fusion of material and associated extreme thermal cycles can result in a highly anisotropic material. Grains tend to solidify directionally resulting in elongated grain morphology with significant crystallographic texture. Grain size, morphology, and texture, directly affect the mechanical properties of polycrystalline metal alloys and can result in anisotropy of key properties such as stiffness, strength, and fatigue life. On the ICMD® platform, QuesTek has developed a modeling and simulation framework linking process, structure, and properties to predict location specific anisotropic material properties resulting from the AM process. There are four key components to this ICME framework; first thermomechanical material properties are predicted using CALPHAD, then those properties are fed into a thermomechanical FEA/CFD simulation to predict location specific thermal history, next the thermal history feeds into a physics-based grain growth model to predict grain size, morphology, and crystallographic orientation, and finally, these microstructure attributes are fed into a CPFEM simulation to predict location specific stiffness, strength, and fatigue performance of the material. This ICME framework can be used to optimize chemistry and processing to achieve targeted mechanical properties for AM alloys in aerospace applications.