| About this Abstract |
| Meeting |
2022 TMS Annual Meeting & Exhibition
|
| Symposium
|
Advanced Characterization Techniques for Quantifying and Modeling Deformation
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| Presentation Title |
Capturing Deformation Mechanisms in Additively Manufactured Parts through High-fidelity Modeling and In Situ Computed Tomography |
| Author(s) |
Kyle L. Johnson, Thomas Ivanoff, Philip Noell, Nathan Heckman, John M. Emery |
| On-Site Speaker (Planned) |
Kyle L. Johnson |
| Abstract Scope |
Improvements in characterization methods have occurred at a rapid pace in recent years. In situ, sub-micron resolution computed tomography (CT) systems at the lab-scale are one such improvement. In parallel, high performance computing power has vastly increased. We are now reaching a point in both computational capability and temporal and spatial characterization fidelity where limits of homogenization theory are being approached, and scale separation is no longer a necessary assumption for structural components. This intersection presents exciting opportunities for both experimentation and computational modeling. This talk will discuss ongoing work to fuse high resolution in situ CT with high-fidelity modeling in order to predict deformation and failure mechanisms in structural metals. As an example, a recent effort will be presented focusing on characterizing and modeling regional property effects on deformation and localization behavior in additively manufactured parts. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Modeling and Simulation, Characterization |