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 its performance under irradiation, since they determine the fuel temperature profile and the melting safety margin, respectively. Currently, 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 temperature, 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, providing the TRANSURANUS fuel performance code with suitable correlations to describe the evolution under irradiation of fast reactor MOX fuel thermal conductivity and melting temperature (herein considered as the solidus temperature). After an extensive review of existing data and correlations available in the open literature, new correlations have been obtained by a statistically assessed fit of the most recent and reliable experimental data (i.e., the significance of the regressors is evaluated based on their p-values). The resulting laws are grounded on a physical basis and account for a wider set of effects impacting on MOX thermal properties. The new correlations have been implemented in the TRANSURANUS code, compared to state-of-the-art correlations and assessed against integral data from the HEDL P-19 fast reactor irradiation experiment. The integral validation 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.

MAGNI A.;  BARANI Tommaso;  DEL NEVO Alessandro;  PIZZOCRI Davide;  STAICU Dragos;  VAN UFFELEN Paul;  LUZZI Lelio; 

2020-08-11

ELSEVIER SCIENCE BV

JRC120352

0022-3115 (online),   

https://www.sciencedirect.com/science/article/pii/S0022311520310187?via%3Dihub,    https://publications.jrc.ec.europa.eu/repository/handle/JRC120352,   

10.1016/j.jnucmat.2020.152410 (online),