Modelling and assessment of thermal conductivity and melting behaviour of MOX fuel for fast reactor applications

Thermal conductivity and melting temperature of nuclear fuel are essential for analysing its performance under irradiation, since they determine the fuel temperature profile and the melting safety margin, re- spectively. A starting literature review of data and correlations revealed that most models implemented in state-of-the-art fuel performance codes (FPCs) describe the evolution of thermal conductivity and melting temperature of Light Water Reactor (LWR) MOX (uranium-plutonium mixed oxide) fuels, in limited ranges of operation and without considering the complete set of fundamental dependencies (i.e., fuel tempera- ture, burn-up, plutonium content, stoichiometry, and porosity). Since innovative Generation IV nuclear reactor concepts (e.g., ALFRED, ASTRID, MYRRHA) employ MOX fuel to be irradiated in Fast Reactor (FR) conditions, codes need to be extended and validated for application to design and safety analyses on fast reactor MOX fuel. The aim of this work is to overcome the current modelling and code limitations, pro- viding fuel performance codes with suitable correlations to describe the evolution under irradiation of fast reactor MOX fuel thermal conductivity and melting temperature. The new correlations have been ob- tained by a statistically assessed fit of the most recent and reliable experimental data. The resulting laws are grounded on a physical basis and account for a wider set of effects on MOX thermal properties (fuel temperature, burn-up, deviation from stoichiometry, plutonium content, porosity), providing clear ranges of applicability for each parameter considered. As a first test series, the new correlations have been im- plemented in the TRANSURANUS fuel performance code, compared to state-of-the-art correlations, and assessed against integral data from the HEDL P-19 fast reactor irradiation experiment. The integral val- idation provides promising results, pointing out a satisfactory agreement with the experimental data, meaning that the new models can be efficiently applied in engineering fuel performance codes.