SBIR/STTR Award attributes
Additive manufacturing (AM) technology is becoming more popular for the fabrication of 3D metal products as it offers rapid prototyping and large design freedom. However, fatigue performance of components fabricated by current AM technology is not comparable to that produced by traditional methods. Post-build processing techniques, such as heat treatment (HT) and Hot Iso-static Pressing (HIP), have been developed to improve microstructure and remove internal flaws that are detrimental to fatigue resistance. In this effort, we develop a novel method for simulating the HT and HIP process and optimizing the post-build process. An Integrated Computational Materials Engineering approach is utilized to link the process parameters with material’s structures, properties and fatigue performance. We propose a unified computational package to (1) simulate the HT/HIP process including the physics of fluid flow, heat transfer, microstructure evolution and residual stress formation, and (2) predict the probabilistic distribution of fatigue life of AM components. Furthermore, a state-of-the-art hybrid optimization approach, combining response surface method and genetic algorithm, is proposed to optimize process parameters to minimize defects and maximize fatigue performance. Ultimately, the software developed will optimize the HT/HIP process for an AM part CAD/CAE model provided by the user.
