Alessio Magni1
Lelio Luzzi1, Davide Pizzocri1, Arndt Schubert2, Paul Van Uffelen2, Alessandro Del Nevo3
1Politecnico di Milano; 2Joint Research Centre – Karlsruhe; 3 ENEA – Brasimone Research Centre.
Abstract
Thermal conductivity and melting temperature are fundamental properties of nuclear fuels since they determine the fuel temperature profile evolution, affecting the overall fuel performance under irradiation and the safety margin to fuel melting. Original models for these thermal properties of MOX fuels were recently published by the same authors. These correlations are based on recent and reliable experimental data, account for a comprehensive set of dependencies (fuel temperature, deviation from stoichiometry, plutonium content, porosity and burn-up). Their accuracy is validated against available data, both experimental and from lower-length scale calculations, showing predictions in line with the current experimental uncertainties (10-20% for the thermal conductivity, up to 2% for the melting temperature). This work proposes to assess the modelling uncertainties on both novel correlations for MOX thermal conductivity and melting temperature, by considering the standard errors on the correlation regressors emerging from the statistical fit procedure and hence identifying the sources of major uncertainty for future modelling improvement efforts. Based on the outcome, the model uncertainty range is propagated to the integral fuel pin scale by exploiting the statistical analysis tool of the TRANSURANUS fuel performance code, in which the novel correlations are implemented. The uncertainty analysis at the pin level is performed considering an irradiation experiment from the HEDL P-19 campaign, focused on the power-to-melt of MOX fuels under irradiation in fast reactor (sodium-cooled) conditions and hence appropriate for evaluating the impact of both modelling of thermal conductivity and melting temperature. The present work represents a first step towards complementing the state-of-the-art best-estimate fuel pin performance calculations with uncertainty and sensitivity analyses of the predicted pin behaviour.
Event Timeslots (1)
Wednesday – 15th September 2021
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Alessio Magni