About this Abstract |
| Meeting |
MS&T26: Materials Science & Technology
|
| Symposium
|
Uncertainty Quantification in Ultra-High Temperature Materials Manufacturing
|
| Presentation Title |
Generalization of a Crystal Plasticity Model from Grade 91 to Grade 92 Steel: A Coupled High-Throughput Constitutive Model and Data-Driven Analysis Approach |
| Author(s) |
Shree Ram Acharya, Anjana Anu Talapatra, Wissam A. Saidi, Laurent Capolungo, Madison Z. Wenzlick |
| On-Site Speaker (Planned) |
Shree Ram Acharya |
| Abstract Scope |
Materials used in advanced energy applications must tolerate extreme environments and mechanical loads. Steels with varying composition and microstructure are developed for these applications but their performance must be evaluated prior to use. Constitutive models can predict macroscale mechanical properties in terms of deformation mechanisms at relevant operating conditions, however, the large number of parameters required leads to difficulty in fitting each model for a novel material. Uncertainty quantification methods enable parameter calibration based on experimental results and further provide a measure of confidence in model predictions. This study presents a calibration framework developed by coupling high-throughput computation using LApx, a constitutive model, with uncertainty quantification using data-driven features through an out-of-the-box toolset, FOQUS. This study reports the general features of the framework and exploration of the generalizability of a tensile and creep rate simulation model developed for Grade 91 steel to Grade 92 steel. |