DISTINCTIVE is a multi-disciplinary collaboration of 10 universities and 3 key industry partners from across the UK’s civil nuclear sector.
PhD/PDRA – PhD
Academic Lead – Bruce Hanson
Researcher – James Goode
University – University of Leeds
The current declared lifetimes for the AGR power stations from EDF Energy will result in the generation of approximately 8,800t of AGR fuel across the whole fleet.
Of this inventory over 2,300t has been reprocessed to date, meaning there is estimated to be about 6,600t spent fuel which needs to be managed . NDA has reported that their preferred option for AGR, outside of current reprocessing contracts in Thorp, is to keep the fuel in interim storage, prior to packaging for disposal in the UK GDF in 2075 . Risks exist with long term wet storage of AGR and so a transition to dry storage may be a preferred option. However, this transition, as well as the dry store environment, may carry unknown risks to cladding integrity and so a better understanding is required before this route can be implemented.
The objective of this project is to answer key questions associated with the transition from wet to dry storage:
To answer these questions we propose a series of small scale tests using a simulant AGR fuel element. The test element will consist of cladding that is representative of that stored in a wet environment with a sealed simulant pellet inside. The testing will be carried out in a bespoke “drying” rig that will be capable of investigating the effect of temperature and pressure, with a range of gases. A key aspect of this project will be a high degree of instrumentation of the sample and rig, to ensure that a full mass balance can be constructed and the physical and chemical processes present can be identified. Materials analysis of the cladding, before and after “drying” to determine any overall effects on cladding integrity, will be carried out using range of techniques at IPSE’s sister the Institute of Materials Research.
An important output from this project will be a process model that will be able to predict optimum conditions for AGR drying. The model will be built up and validated using results from the experiments.
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