| About this Abstract |
| Meeting |
2022 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing Fatigue and Fracture: Developing Predictive Capabilities
|
| Presentation Title |
Information-rich Fatigue Fracture Surface to Evaluate Additive Manufacturing Parameters |
| Author(s) |
David S. Scannapieco, Austin Ngo, Collin Sharpe, Hunter Taylor, Joseph Pauza, Enrique Garibay, Evan Diewald, Christian Gobert, Ryan Wicker, Anthony Rollett, Jack Beuth, John Lewandowski |
| On-Site Speaker (Planned) |
David S. Scannapieco |
| Abstract Scope |
Evaluation and optimization of parameters for additive manufacturing (AM) has grown more sophisticated as the industry has expanded. Parameter maps, metallurgical analysis, and predictive formulas are just some of the tools employed in this process. This study introduces a new tool: mechanical and fractographical analysis via 4-point bend fatigue (4PB). The fracture surface of a fatigued AM component provides numerous sources of insight into the details of the AM process for said component. From initiation points, KQ estimates, quantitative and qualitative defect analysis this method creates a roadmap to optimize parameters. Fatigue analysis of AM components is shown to be just as effective on irregularly sized specimens as on ASTM standard specimens. A series of case studies (e.g. Ti-6Al-4V, GRCop-42) are presented demonstrating the process, the information extracted, and the application of identified solutions into a new build to show the method’s success. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Titanium, Other |