About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing Fatigue and Fracture
|
| Presentation Title |
Quantifying the Fatigue Criticality of Microstructual Features in L-PBF IN718 |
| Author(s) |
Alexander N. Caputo, Richard Neu, Xiayun Zhao |
| On-Site Speaker (Planned) |
Alexander N. Caputo |
| Abstract Scope |
The microstructure of additively manufactured (AM) metallic materials strongly differs from those made through conventional means. The AM process can introduce porosity, strong crystallographic texturing, and can enlarge or refine grain sizes. Because fatigue properties are dependent on the “weakest link” in a material, the anomalous microstructural features created in AM materials can significantly influence the bulk material properties. This research was conducted to quantitatively deconvolute the complex process-structure-property relationships that govern the fatigue behavior of AM Inconel 718. To this end, high cycle fatigue tests were conducted on 100 dogbone specimens extracted from AM dogbone coupon walls produced using 11 separate process parameter combinations, or pedigrees. The gage region of each pedigree was characterized through SEM and EBSD, while the gage region of each fatigue specimen was characterized by XCT. The comparative influence of the microstructural features on fatigue were interrogated through the use of explainable machine learning algorithms. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, High-Temperature Materials, Machine Learning |