| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing Fatigue and Fracture: Towards Accurate Prediction
|
| Presentation Title |
Microanalysis of Defects, Grain Structure, Surface Treatment and Its Correlation to Fatigue Behavior of Additively-Manufactured 316L Stainless Steel |
| Author(s) |
Jackelin Amorin, Can Uysalel, Maziar Ghazinejad |
| On-Site Speaker (Planned) |
Jackelin Amorin |
| Abstract Scope |
Recent progress in additive manufacturing (AM) has allowed for developing parts with highly intricate geometries, but less predictable fatigue behavior. This study seeks to provide insight into the effects of structural defects, grain morphology, surface processing, and residual stresses on the fatigue behavior of stainless steel samples manufactured by direct metal laser sintering (DMLS) technique. Electron microscopy and electron backscatter diffraction (EBSD) techniques allowed us to characterize microstructural properties of metal samples, including grain size, grain morphology, and crystallographic orientation within and between grains of 316L samples. Furthermore, we carry out standard fatigue tests to determine fatigue characteristics of 316L samples subjected to different surface treatments and residual stresses. Machine vision is used to classify microstructural features across several micrographs acquired from surface and core areas of samples. Lastly, we performed fractography through SEM imaging to analyze crack initiation sites in relation to present defects. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Characterization, Additive Manufacturing, Machine Learning |