Fuel Modelling at Extended Burnup: IAEA Coordinated Research Project FUMEX-II

The International Atomic Energy Agency sponsored a Coordinated Research Project on Fuel Modelling at Extended Burnup (FUMEX-II). Eighteen fuel modelling groups participated with the intention of improving their capabilities to understand and predict the behaviour of water reactor fuel at high burnups. The exercise was carried out in coordination with the OECD/NEA. The participants used a mixture of data derived from actual irradiation histories of high burnup experimental fuel and commercial irradiations where post-irradiation examination measurements are available, combined with idealised power histories intended to represent possible future extended dwell commercial irradiations and test code capabilities at high burnup. All participants have been asked to model nine priority cases out of some 27 cases made available to them for the exercise from the IAEA/OECD International Fuel Performance Experimental Database. Calculations carried out by the participants, particularly for the idealised cases, have shown how varying modelling assumptions affect the high burnup predictions, and have led to an understanding of the requirements of future high burnup experimental data to help discriminate between modelling assumptions. This understanding is important in trying to model transient and fault behaviour at high burnup. It is important to recognise that the code predictions presented here should notmore » be taken to indicate that some codes do not perform well. The codes have been designed for different applications and have differing assumptions and validation ranges; for example codes intended to predict Candu fuel operation with thin wall collapsible cladding do not need the clad creep and gap conductivity modelling found in PWR codes. Therefore, when a case is based on Candu technology or PWR technology, it is to be expected that the codes may not agree. However, it is the very differences in such behaviour that is useful in helping to understand the effects of such internal modelling. (authors)« less