|About this Abstract
||2022 TMS Annual Meeting & Exhibition
||Additive Manufacturing: Advanced Characterization with Synchrotron, Neutron, and In Situ Laboratory-scale Techniques II
||Characterizing Void Morphology in Single-track Builds of Directed Energy Deposition Using New Image Processing Techniques for X-ray Computed Tomography Data Sets
||Newell Moser, Edward Garboczi, Samantha Webster, Jian Cao
|On-Site Speaker (Planned)
Single-track builds of Ti-6Al-4V were manufactured via Directed Energy Deposition (DED) at the Advanced Photon Source (Argonne National Laboratory); high-speed X-ray imaging was performed to capture real-time interactions between the melt pool and the metal particles. Afterwards, at the National Institute of Standards and Technology, the DED samples were characterized using micro X-ray Computed Tomography (X-ray CT), which is the focus of this presentation. The resultant (volume-based) image sequences were carefully segmented using a new, open-source suite of Python scripts that strike a balance between computational speed and memory consumption. Moreover, a variety of techniques, including spherical harmonics, were utilized to characterize the shape, size, orientation, and distribution of the internal voids. By linking these void statistics to the chaotic process of DED, critical insights were revealed that relate process parameters to the mechanisms that drive the formation of voids.
||Additive Manufacturing, Characterization,