About this Abstract |
| Meeting |
2027 TMS Annual Meeting & Exhibition
|
| Symposium
|
Computational Thermodynamics and Kinetics
|
| Presentation Title |
Multiscale Computational Framework for Microstructure Evolution Prediction in Solid-Phase Processed Oxide Dispersion Strengthened Steels |
| Author(s) |
Lukasz Kuna, Lei Li, Shadab Anwar Shaikh, Aishani Sharma, Xiao Li, Eda Aydogan Gungor, Jens Darsell, Stuart Maloy, Ayoub Soulami |
| On-Site Speaker (Planned) |
Lukasz Kuna |
| Abstract Scope |
Solid phase processing is important for oxide dispersion strengthened steel fabrication as it provides an avenue for the production of steels with uniform dispersions of nano-oxides while avoiding the lengthy, costly, and inhomogeneity-prone steps of conventional powder metallurgy. In this work, a multiscale, multi-physics computational framework has been developed to better understand process-structure correlations during the fabrication of cladding tubes. The framework couples macroscale smoothed particle hydrodynamics simulations of thermomechanical behavior with a mesoscale coupled phase field and crystal plasticity model to predict microstructure evolution and residual properties. The model accounts for the contributions of oxide particles to mechanical strengthening via Orowan strengthening and to thermodynamic effects via Smith-Zener pinning of boundaries. The influence of average oxide particle size and volume fraction on dynamic recrystallization behavior is assessed to predict the resulting microstructure. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
ICME, Nuclear Materials, Computational Materials Science & Engineering |