Article

Metallurgical and Materials Transactions A

, Volume 43, Issue 3, pp 1060-1069

First online:

Predicting Thermal Conductivity Evolution of Polycrystalline Materials Under Irradiation Using Multiscale Approach

  • Dongsheng LiAffiliated withFundamental and Computational Science Directorate, Pacific Northwest National Laboratory Email author 
  • , Yulan LiAffiliated withFundamental and Computational Science Directorate, Pacific Northwest National Laboratory
  • , Shenyang HuAffiliated withFundamental and Computational Science Directorate, Pacific Northwest National Laboratory
  • , Xin SunAffiliated withFundamental and Computational Science Directorate, Pacific Northwest National Laboratory
  • , Mohammad KhaleelAffiliated withFundamental and Computational Science Directorate, Pacific Northwest National Laboratory

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Abstract

A multiscale methodology was developed to predict the evolution of thermal conductivity of polycrystalline fuel under irradiation. At the mesoscale level, a phase field model was used to predict the evolution of gas bubble microstructure. Generation of gas atoms and vacancies was taken into consideration. Gas bubbles were predicted to form, grow, and coalesce around grain boundary (GB) areas. On the macroscopic scale, a statistical continuum mechanics model was applied to predict the anisotropic thermal conductivity evolution during irradiation. Microstructures predicted by the phase field model were fed into the statistical continuum mechanics model to predict properties and behavior. A decrease of thermal conductivity during irradiation was demonstrated. The influence of irradiation flux, the exposure time, and the grain microstructure were investigated. If the initial GB microstructure was isotropic, the thermal conductivity under irradiation would be similarly isotropic. If the initial GB configuration was anisotropic, anisotropy of thermal conductivity would intensify under irradiation as gas bubbles coalesce around GB areas. The prediction of microstructure and property evolution of polycrystalline materials under irradiation by bridging two models in different scales were demonstrated successfully. This approach provides a deep understanding from a basic scientific viewpoint.