A quantitative phase-field model of gas bubble evolution in UO2

Xiao, Zhihua; Wang, Yafeng; Hu, Shenyang; Li, Yulan; Shi, San-Qiang

doi:10.1016/j.commatsci.2020.109867

Title: A quantitative phase-field model of gas bubble evolution in UO₂

Journal Article · 17 June 2020 · Computational Materials Science

DOI: https://doi.org/10.1016/j.commatsci.2020.109867 · OSTI ID:1635543

Xiao, Zhihua ^[1];

^[1]; Hu, Shenyang ^[2]; Li, Yulan ^[2]; Shi, San-Qiang ^[1]

The Hong Kong Polytechnic Univ. Shenzhen Research Inst. (China); The Hong Kong Polytechnic Univ. (China)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Due to the large formation energy of vacancies and noble gas atoms at interstitial and/or substitutional sites in nuclear fuel (UO₂), the thermodynamic equilibrium concentrations of these species are very low in the nuclear fuel matrix even at very high temperature, which imposes difficulties upon the quantitative study of bubble evolution via the phase-field method. In this study, a quantitative phase-field model is proposed to deal with this problem. The free energy density of the system is derived according to the principles of thermodynamics, with consideration of the elastic interaction and internal pressure of each gas bubble, and with the use of material parameters from experiments. The model enables one to study the kinetics of gas bubble growth with very dilute concentrations of vacancy and gas atoms in the matrix. With this model, the growth of a single bubble and multiple bubbles were simulated under different concentrations of vacancy and gas atoms and at different temperatures. The effect of elastic interaction energy and the generation rate of vacancies and gas atoms on bubble growth are analyzed.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE; National Natural Science Foundation of China (NSFC); Research Grants Council (RGC)

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1635543

Alternate ID(s):: OSTI ID: 1688435

Journal Information:: Computational Materials Science, Journal Name: Computational Materials Science Journal Issue: C Vol. 184; ISSN 0927-0256

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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