About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
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Symposium
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Additive Manufacturing Fatigue and Fracture: Effects of Surface Roughness, Residual Stress, and Environment
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Presentation Title |
A-8: Parameterizing Surface Defects and Internal Porosity to Predict Fracture Location in As-built AM Tensile Specimens Using a Modified Void Descriptor Function |
Author(s) |
Elliott Marsden, Dillon Watring, John Erickson, Laura Ziegler, Andrew Chihpin Chuang, Ashley Spear |
On-Site Speaker (Planned) |
Elliott Marsden |
Abstract Scope |
Predicting fracture location (FL) in as-built AM metal components is difficult given the complex interaction between surface defects and internal voids. Previously, a Void Descriptor Function (VDF) was derived to provide an analytical approach to estimate FL in a uniaxially loaded specimen given its internal pore network (PN). Although the VDF has been shown to perform well in predicting FL in both simulated and experimental specimens, its prediction performance is expected to decrease in cases for which surface roughness influences fracture behavior. This work aims to extend the VDF to account for surface defects while retaining current mechanical-property correlation and predictive capabilities. A screening strategy is proposed to locate and parameterize critical surface defects in X-ray computed tomography image stacks. Proper surface-pore characterization and parametric representation in the VDF could potentially lead to efficient, accurate predictions of fracture in as-built components where both surface roughness and internal PNs are critical. |
Proceedings Inclusion? |
Planned: |
Keywords |
Other, |