4.7 Article

A CALPHAD-informed approach to modeling constituent redistribution in Zr-based metallic fuels using BISON

期刊

JOURNAL OF NUCLEAR MATERIALS
卷 544, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.jnucmat.2020.152657

关键词

Uranium-plutonium-zirconium; Metallic fuel; Constituent redistribution; CALPHAD; BISON

资金

  1. US Department of Energy Fuel Cycle Technologies program from Idaho National Laboratory
  2. US Department of Energy [DE-AC07-05ID14517]

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A CALPHAD-informed constituent redistribution model was developed and incorporated into the BISON fuel performance code, calibrated with three uncertain model parameters to accurately predict the behavior of U-Zr fuels. Model predictions for U-Pu-Zr fuels were less accurate, with potential improvement by reducing uncertainties in ternary phase transition temperatures and collecting more kinetic data. The new model was successfully coupled with existing thermomechanics models to accurately simulate irradiation of U-Zr fuels at the engineering scale.
A CALPHAD-informed (Computer Coupling of Phase Diagrams and Thermochemistry) constituent redistribution model was developed for Zr-based metallic fuels and incorporated into the BISON fuel performance code. Three uncertain model parameters associated with beta and gamma phase kinetics were calibrated using integral test data from U-Zr fuel elements irradiated in Experimental Breeder Reactor II. The calibrated constituent redistribution model was shown to predict the behavior of U-Zr fuels with excellent accuracy. Model predictions for U-Pu-Zr fuels were physically reasonable but less accurate. Reduction of uncertainties in the ternary phase transition temperatures and collection of kinetic data for the zeta phase are expected to improve the model's ternary predictions. Finally, the new model was coupled to existing thermomechanics models in BISON to simulate irradiation of an entire U-Zr fuel element, demonstrating its ability to accurately predict the behavior of U-Zr fuels with realistic geometries and mesh resolutions at the engineering scale. (C) 2020 Elsevier B.V. All rights reserved.

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