The climate crisis demands urgent action and a rapid shift towards carbon-free technologies. This requires the development of advanced materials for more efficient electricity production and storage, including innovation in nuclear reactor fuels. To enhance the safety and efficiency of both current and future nuclear power plants, it is crucial to understand and predict fuel behavior under operating and accidental conditions.

A critical issue is related to fission gases produced upon nuclear fissions. These gases have low solubility and form small bubbles that grow from nanoscale to microscale during fuel operation, significantly impacting the fuel's overall properties. While experimental characterization is essential, numerical simulations complement this work by modeling bubble formation and growth, as well as the consequences in terms of changes in fuel properties. This approach is key to the design of next-generation, high-performance nuclear fuels.

This PhD project aims to advance simulation models for fission gas behavior within the polycrystalline structure of nuclear fuels, with a particular focus on uranium oxides. The PhD student will develop a physical model using the phase-field method, compute necessary input parameters, and conduct numerical simulations that replicate irradiation experiments performed in our department. Direct comparison between simulation results and experimental data will enable deeper insights into the underlying physics of gas behavior, including bubble formation, gas release, and fuel swelling. Additionally, this project will serve as validation for the INFERNO scientific code that will be used for these simulations on national supercomputers.

The research will be conducted at the Nuclear Fuel Department (DEC) of the IRESNE Institute(CEA-Cadarache), in collaboration with CEA fuel modeling and experimental characterization experts. The PhD student will have opportunities to share their findings through scientific publications and presentations at international conferences. Throughout the project, they will develop expertise in multiphysics modeling, numerical simulations, and scientific computing. These highly transferable skills will prepare them for a successful career in academic research, industrial R&D, or materials engineering.

References :
https://doi.org/10.1063/5.0105072
https://doi.org/10.1016/j.commatsci.2019.01.019