| About this Abstract |
| Meeting |
2021 TMS Annual Meeting & Exhibition
|
| Symposium
|
AI/Data informatics: Tools for Accelerated Design of High-temperature Alloys
|
| Presentation Title |
Uncertainty Quantification for Thermo-mechanical Behavior of Aircraft Engine Materials in Elevated Temperatures |
| Author(s) |
Arulmurugan Senthilnathan, Pinar Acar |
| On-Site Speaker (Planned) |
Arulmurugan Senthilnathan |
| Abstract Scope |
The Turbine inlet temperature (TIT) is a crucial parameter, which affects the overall efficiency of gas turbine engines. However, its indirect measurement leads to uncontrolled uncertainty in thermal and mechanical properties. An important example of turbine materials is the Titanium-Aluminum alloys owing to their resistance to high thermal and mechanical stresses. Consequently, the goal of the present study is to understand the changes in microstructural and thermo-mechanical behavior of Titanium-Aluminum alloys at TIT, by considering the effects of the uncertainty. The mechanical response of the alloy is computed using LAMMPS for a range of elevated temperature values to incorporate the uncertainty in TIT. The propagation of the TIT uncertainty on the mechanical properties is identified with the computed range for the stress-strain response. The future work will utilize these physics-based simulations to develop a machine learning model that can predict the stress-strain behavior of the alloy at a given temperature. |
| Proceedings Inclusion? |
Planned: |