| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Additive Manufacturing Fatigue and Fracture: Towards Accurate Prediction
|
| Presentation Title |
As-Printed Surface Roughness Analysis for Predicting Minimum Fatigue Life of Additively Manufactured Parts |
| Author(s) |
Sushant K. Jha, Matthew E Krug, Patrick J Golden, Reji John |
| On-Site Speaker (Planned) |
Sushant K. Jha |
| Abstract Scope |
A method for analyzing the as-printed surface roughness of additively manufactured (AM) parts was developed for predicting the minimum fatigue life. Distributions of the roughness feature-root radii and an extreme-value analysis of feature depths were incorporated in an energy-based elastic-plastic strain analysis to predict critical combinations of root radius and depth leading to early crack initiation. A probabilistic model was used to predict the minimum fatigue life by considering the distribution in the small and long crack growth life for cracks initiating from critical roughness valley depths in randomly instantiated samples. Model results were compared to experimental data on Ti-6Al-4V specimens bearing as-printed laser powder bed fusion surfaces. The proposed approach uses measurable surface quality outcomes of the AM process to predict the minimum fatigue life. Therefore, it can aid in optimizing an AM process and qualifying parts for fatigue-critical applications. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Mechanical Properties, Titanium |