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Projects: Projects for Investigator
Reference Number EP/R006075/1
Title Simulated Used Nuclear Fuel Dissolution as a Function of Fuel Chemistry and Near Field Conditions
Status Completed
Energy Categories Nuclear Fission and Fusion(Nuclear Fission, Nuclear supporting technologies) 100%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Chemistry) 50%;
PHYSICAL SCIENCES AND MATHEMATICS (Metallurgy and Materials) 40%;
ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences) 10%;
UKERC Cross Cutting Characterisation Not Cross-cutting 70%;
Sociological economical and environmental impact of energy (Environmental dimensions) 20%;
Sociological economical and environmental impact of energy (Consumer attitudes and behaviour) 10%;
Principal Investigator Dr C Corkhill
No email address given
Engineering Materials
University of Sheffield
Award Type Standard
Funding Source EPSRC
Start Date 09 April 2018
End Date 08 April 2021
Duration 36 months
Total Grant Value £338,985
Industrial Sectors Energy
Region Yorkshire & Humberside
Programme Energy : Energy
Investigators Principal Investigator Dr C Corkhill , Engineering Materials, University of Sheffield (99.998%)
  Other Investigator Dr NC Hyatt , Engineering Materials, University of Sheffield (0.001%)
Dr MC Stennett , Engineering Materials, University of Sheffield (0.001%)
Web Site
Abstract This research is a joint UK and US effort to understand the long-term safety of used nuclear fuel (UNF), the primary waste arising from the generation of electricity by nuclear fission. With more than 440 commercial nuclear power stations operating worldwide, a significant cumulative inventory of UNF has been produced, on the order of 300,000 metric tonnes. In the UK, several new nuclear reactors are planned for construction (e.g. Hinkley Point C), and the UNF reprocessing capability at Sellafield (ThORP) is due to close in 2018. Hence, the UK inventory, currently estimated at 3,500 - 8,000 tonnes, will continue to grow. The US currently (April 2016) has 80,150 metric tonnes of UNF, with a prediction of a total of approximately 140,000 metric tons by around 2050 when all currently operating reactors reach their designated life.The UK and the US presently have no final disposal route for UNF; fuel is currently stored in cooling ponds (UK and US) or dry storage (US only), but this is not a sustainable final solution. Both countries agree that disposal in a deep (200 m - 1000 m) geological formation is the most suitable solution, since it will isolate the UNF from the biosphere and future populations for more than 100,000 years - the period of time for which this material will be highly radioactive. In such a Geological Disposal Facility (GDF), the release of radionuclides to the environment will be controlled by the interaction of the UNF with groundwater, and with the materials that have been built as an engineered barrier around the waste, particularly the fuel cladding and the metal canister. Fundamental mechanistic understanding of how UNF interacts with groundwater under GDF conditions is of paramount importance for UK and US waste management programs, which seek to satisfy citizens and regulators regarding the reliability of long-term degradation predictions for UNF originating from a variety of fuel designs, burn-ups, reactor operations, and storage conditions.This research project is envisioned as a collaborative and joint enterprise between leading researchers from the UK and US who, collectively, bring mutually complementary and compatible skills, capabilities, and interests required to achieve a paradigm shift in our fundamental understanding of UNF dissolution in the presence of cladding and canister materials, and local groundwater conditions. This understanding will underpin the maturation of models for UNF evolution and interaction under different repository conditions, enabling reliable prediction of degradation and adjustment of repository conditions to achieve desired long-term performance and providing confidence in predicting behaviour for up to one million years.
Publications (none)
Final Report (none)
Added to Database 12/02/19