The overall aim of the PhD project and associated PDRA position is to construct the basis for a predictive tool for spent fuel behaviour; to model spent fuel in aqueous environments, across length-scales, using results from atomistic simulations, using physical and chemical kinetics, combining radiolysis models with molecular dynamics. We plan to close the loop between experiment and theory, by designing experiments that mimic and test the idealized scenarios implicit in these models. This project will bring the theorists and experimentalists together on a joint venture; retaining, building and developing knowledge-base for future generations.
Later, we plan to increase the complexity of the model; adding defect impurities, lattice damage, modifying the crystallography and the stoichiometry. We plan to vary the physical and chemical environment; mimicking the fuel in the spent fuel pool, in long-term storage and in operation, during an accident scenario. In the longer term, this approach will be extended to exotic fuels (nitrides, silicides for example), linking to work in the ATLANTIC consortium.
The PhD project will focus on building the model, collaborating with international partners (CEA) and within the UK (Lancaster, Bath) to better understand the fundamental behaviour of water at the surface of spent fuel. We plan to develop FACSIMILE + COMSOL models in collaboration with NNL, moving towards real-world systems. We will then design experiments that mimic these idealised scenarios and test them. This will involve the deposition and control of actinide-based surfaces, using the dedicated actinide deposition system run at UoB.
The PDRA will focus on experimental aspects of the project, using facilities such as the DCF and Surrey Ion Beam Centre to mimic radiation damage from specific fission product species. Further, we have a collaboration with the KURRI and CLADS facility in Japan, which will enable us to irradiate thin film fuel samples with high neutron fluxes. These samples will be investigated for their dissolution properties and compared to (and provide input to) model calculations. Our methodology is ambitious and at the cutting edge of what is possible today but utilizes some of the unique facilities that the UK possesses, and more importantly combines knowledge pools across the UK and, more widely, across the world, to input into the foundations of a predictive tool for SNF behaviour.
Academic Lead: Ross Springell
Researcher: Angus Siberry
Location: University of Bristol