Performances of three atmospheric dispersion models in predicting near-surface tritium concentration distribution

被引:0
|
作者
Ran, Yiling [1 ]
Wang, Yuxuan [1 ]
Nie, Baojie [1 ]
Su, Chunlei [2 ]
Li, Zhiming [2 ]
Wang, Dezhong [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Nucl Sci & Engn, Key Lab Nucl Power Syst & Equipment, Minist Educ, Shanghai 200240, Peoples R China
[2] Northwest Inst Nucl Technol, Xian 710024, Peoples R China
基金
中国国家自然科学基金;
关键词
Atmospheric dispersion model; Complex topography; Radioactivity;
D O I
10.1016/j.fusengdes.2024.114728
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
Tritium discharge from the fusion system and its environmental impact receive wide attention. Considerable deviation exists in various atmospheric dispersion models for evaluating near-surface tritium concentration distribution. To quantitatively find out the diversity of these models, a performances comparison was performed based on the case of tritium discharge from the ITER site. Wind tunnel experiments were preliminarily performed to test the performances of these models. Annual average tritium concentration and individual radiation dose were assessed for some selected residential areas adjacent to the ITER site. It is indicated that atmospheric dispersion simulation by the CFD method is significantly influenced by the modeling of the turbulence. Atmospheric dispersion predicted by the CFD-RANS model with default parameters is weaker, resulting in higher downwind pollutant concentration, compared with the CFD-LES model, Gaussian plume model and Lagrangian puff model. Wind tunnel experimental results relatively support the CFD-LES model with strong turbulent dispersion. CFD-LES model is superior in reflecting the effects of complex topography in high resolution and shows strong turbulent dispersion. Individual radiation dose under normal operation at selected residential areas near ITER was estimated to be much lower than the natural radiation level and also the ITER dose limit even considering the uncertainty margin.
引用
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页数:14
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