Abstract
Fatigue performance is crucial for gas turbine components, and it is greatly affected by the manufacturing processes. Ability to predict the expected fatigue life of a component based on surface integrity has been the objective in this work, enabling new processing methods.
Alloy 718 samples were prepared by different machining setups, evaluated in fatigue testing and surface integrity investigations. These results generated two predictive statistical multi-variate regression models.
The fatigue correlated well with roughness, residual stresses and deformation. The two models showed great potential, which encourages further exploration to fine-tune the procedure for the particular case.
| Original language | English |
|---|---|
| Article number | 106059 |
| Pages (from-to) | 106059 |
| Number of pages | 1 |
| Journal | International Journal of Fatigue |
| Volume | 144 |
| DOIs | |
| Publication status | Published - Mar 2021 |
Keywords
- Surface integrity
- Fatigue prediction
- Alloy 718
- Machining
- Non-conventional machining
Project and Funding Information
- Funding Info
- The results from this work was granted from the research project G5Demo-2 [2013-04666] and SWE DEMO MOTOR [2015-06047] financed by VINNOVA, Sweden’s innovation agency. Special thanks to GKN Aerospace Sweden AB. The authors also would like to thank the KK- foundation and the SiCoMaP research school.