About this Abstract |
Meeting |
MS&T22: Materials Science & Technology
|
Symposium
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Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
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Presentation Title |
Quantitative Analysis of Computed Tomography Characterization of Porosity in AM Ti64 Using Serial Sectioning Ground Truth |
Author(s) |
Bryce Jolley, Michael D. Uchic, Daniel Sparkman, Christine Henry, Michael Chapman, Edwin Schwalbach |
On-Site Speaker (Planned) |
Michael D. Uchic |
Abstract Scope |
X-Ray Computed Tomography is a widely-used method for nondestructive characterization of internal porosity in complex-shaped parts produced by Additive Manufacturing. However, there are a host of factors that can significantly affect the accuracy of computer-based analysis of porosity from XCT data. This presentation will explore a quantitative assessment of XCT porosity-characterization workflows for a 10 mm diameter cylindrical Ti-64 sample. The same sample has been characterized using four different XCT systems to explore the sensitivity to the XCT experimental, reconstruction, and segmentation workflows, after which automated serial sectioning was employed to estimate the true internal porosity distribution within a 2 mm thick subregion of the cylinder with ~2 micrometer spatial resolution. Notably, titanium alloy ball bearings were adhered to the surface of the cylindrical sample to facilitate automated registration of the multi-modal datasets, thus enabling both global and local analysis of the changes in pore measurements. |