| About this Abstract |
| Meeting |
2022 TMS Annual Meeting & Exhibition
|
| Symposium
|
Mechanical Response of Materials Investigated Through Novel In-Situ Experiments and Modeling
|
| Presentation Title |
Toward Improved Constitutive Behavior Models Sensitive to High Strength Steel Microstructures through Advancements in Data Analysis Tools |
| Author(s) |
Eric J. Payton |
| On-Site Speaker (Planned) |
Eric J. Payton |
| Abstract Scope |
Improved microstructure-sensitive models are desired for predicting constitutive behavior of high strength steels. Fitting models of viscoplastic response of these alloys under dynamic loading conditions remains challenging due to testing costs, microstructural effects, and experimental variability, which propagates into model parameters during fitting. The complex, hierarchical microstructure of quench-and-temper and maraging steels presents a challenge for quantitative characterization, especially for fine austenite grain sizes where fewer variants may be observed. In the present work, several high strength steels are subjected to rapid thermal cycling to refine the microstructures and mechanically tested using split Hopkinson apparatus. The microstructures are characterized using an algorithm probabilistic reconstruction of the prior austenite microstructure from room temperature electron backscatter diffraction observations. This talk presents an overview of our efforts to develop novel model fusion, uncertainty quantification, synthetic microstructures, and data clustering algorithms to link microstructures to dynamic behavior of high strength steels. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Characterization, Modeling and Simulation, Iron and Steel |