| About this Abstract |
| Meeting |
2023 TMS Annual Meeting & Exhibition
|
| Symposium
|
Microstructural, Mechanical and Chemical Behavior of Solid Nuclear Fuel and Fuel-cladding Interface
|
| Presentation Title |
Accelerating the Qualification of Nuclear Fuels Through Advanced Characterization and Multiscale Modeling |
| Author(s) |
Joshua T. White |
| On-Site Speaker (Planned) |
Joshua T. White |
| Abstract Scope |
Qualification of nuclear fuels for use in modern nuclear reactors currently requires lengthy, and costly, irradiation test campaigns to provide assurance of the reactor performance under a variety of scenarios. The Nuclear Regulatory Commission is interested in advanced modeling and simulation methods to expedite the qualification of fuels by utilizing improved mechanistic models combined with separate effects experiments to decrease the number of required data sets to commission fuels for use. The use of innovative machine learning (ML) tools coupled with state-of-the-art experimental measurements will be used to benchmark the models as well as reduce the uncertainty, providing confidence in fuel performance in-pile. This talk will focus on UN and UC, two potential high-impact fuels for microreactors and gas-cooled reactors. The developed ML models will be integrated with multiphysics engineering-scale neutronics and reactor simulations that ultimately define safety margins for novel nuclear fuels within specific reactor conditions. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Nuclear Materials, Machine Learning, |