MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING | 卷:774 |
A mechanism-based quantitative multi-scale framework for investigating irradiation hardening of tungsten at low temperature | |
Article | |
Wang, Yuanyuan1  Sun, Xin2  Zhao, Jijun1  | |
[1] Dalian Univ Technol, Key Lab Mat Modificat Laser Ion & Electron Beams, Dalian 116024, Peoples R China | |
[2] Oak Ridge Natl Lab, Energy & Transportat Sci Div, Oak Ridge, TN 37831 USA | |
关键词: Multiscale modeling framework; Irradiation hardening; Defects evolution kinetics; Strength model; Thermal softening; | |
DOI : 10.1016/j.msea.2020.138941 | |
来源: Elsevier | |
【 摘 要 】
We present the development and validation of a mechanism-based multi-scale modeling framework to quantitatively link the irradiation defect evolution kinetics at the microscopic scale to the macroscopic yield strength and flow stress evolution of tungsten irradiated at low temperature (0.08 < T/T-m < 0.18, where T-m is the melting point and is equal to 3673 K). The mechanism-based strength model, proposed as the superposition of thermal softening and modified dispersed barrier hardening, is developed to understand the underlying strengthening mechanisms. The thermal softening exponent as defined in the Johnson-Cook model is obtained by fitting un-irradiated yield strength at different temperatures. A set of irradiation-Induced defect kinetics equations with the thermodynamics parameters derived from the atomic calculations reported in the literature is used to determine the densities and sizes of defect clusters at the meso-scale, and the predicted irradiation damage characteristics are in reasonable quantitative agreement with experimental data from literature. The effects of irradiation condition (temperature and irradiation dose) and test temperature on yield strength are quantitatively predicted and compared with experimental measurements from the literature. The predicted irradiation hardening and strain hardening are compared with experimental data as model validation.
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