About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Ceramics and Ceramic-Based Composites for Nuclear Applications III
|
| Presentation Title |
Data-driven prediction of graphite oxidation behaviors in accidental conditions of high temperature gas-cooled reactors: graphite size and shape effects |
| Author(s) |
Suela Lee, Sang Hyun Ryu, Yi Je Cho |
| On-Site Speaker (Planned) |
Suela Lee |
| Abstract Scope |
Under accident conditions in high temperature gas-cooled reactors (HTGRs), air and steam ingress induce severe graphite oxidation, reducing both service life and safety. Although experimental investigations have characterized oxidation behavior, such investigations demand significant time and cost. Data-driven prediction of material properties addresses these limitations and enables efficient analysis and forecasting of graphite performance in extreme environments. In this study, data-driven techniques were applied to predict graphite oxidation in HTGR accident scenarios, with emphasis on size and shape effects. Correlations among graphite properties, oxidation conditions, and oxidation behaviors were quantified to identify the most influential factors. Artificial intelligence models, trained on varying feature sets, were evaluated for accuracy to establish a high performance predictor of graphite oxidation behavior. An empirical kinetic model incorporating size and shape effects is also proposed. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Nuclear Materials, Ceramics, Environmental Effects |