|
|
|
| Construction and application of a field-scale rapid prediction system for wind field and pollutant dispersion |
| WANG Xinran1, YAN Chao2, CHEN Ling1, MIAO Shiguang2, ZHANG Liang1 |
1. China Institute of Atomic Energy, Beijing 102413 China;
2. Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089 China |
|
|
|
|
Abstract Objective To construct a rapid prediction system to improve the accuracy and efficiency of evaluation of the consequences of nuclear accidents at a field scale. Methods Base on a diagnostic wind field model and Lagrangian particle diffusion, we established a rapid prediction method for wind field and pollutant dispersion around complex underlying surfaces within a field scale, in a way of visual discrimination of buildings and vegetation distribution. With data simulation and the use of a real urban field example, the simulated results were compared with wind tunnel test measurements and computational fluid dynamics results to study the influence of complex underlying surfaces on wind field and pollutant transport in the region. Results The rapid prediction system could clearly simulate the high-resolution wind field and pollutant concentration distribution of the region in about five minutes. It could interface with geographic information software and couple with a mesoscale weather prediction model. In terms of accuracy, the system performed well in wind field simulation, with the fractional deviations of wind speed and wind direction being 0.33 and −0.08, respectively. Concentration field simulation was greatly affected by the wind field, and the ratios of simulated concentrations to observed concentrations were between 0.05 and 3.4, except for a few low concentration points. Conclusion The rapid prediction system can effectively simulate the distribution characteristics of the flow field and improve calculation efficiency when ensuring calculation accuracy, which provides an important reference for emergency response to nuclear accidents.
|
|
Received: 13 February 2023
|
|
|
|
|
|
[1] 朱好, 熊章辉, 刘新建, 等. 核电厂正常运行和事故条件下大气扩散模式的适用性分析[C]//中国核科学技术进展报告(第四卷)——中国核学会2015年学术年会论文集第5册(核材料分卷、辐射防护分卷). 北京: 中国原子能出版社, 2015: 515-524.
Zhu H, Xiong ZH, Liu XJ, et al. Analysis of the suitability of atmospheric dispersion models used under normal operational and accident conditions of NNPs[C]//China Nuclear Science and Technology Progress Report (Volume IV)——Proceedings of the 2015 Annual Conference of the Chinese Nuclear Society, Volume 5 (Nuclear Materials and Radiation Protection). Beijing: China Atomic Energy Press, 2015: 515-524.
[2] 王汉青, 刘镇铭, 张斌, 等. 大中尺度大气污染物扩散数值模拟研究进展[J]. 科学技术与工程,2023,23(9):3605-3617. DOI: 10.7498/aps.53.671
Wang HQ, Liu ZM, Zhang B, et al. Progress of numerical simulation of large and medium-scale atmospheric pollutant diffusion[J]. Sci Technol Eng, 2023, 23(9): 3605-3617. DOI: 10.7498/aps.53.671
[3] 程穆阳. 高斯模型在中小城市多点源大气扩散模拟中的应用研究—以绥化市为例[D]. 哈尔滨: 哈尔滨师范大学, 2020.
Cheng MY. Research on the application of Gauss model in multi-point atmospheric diffusion simulation of small and medium-sized cities-a case study of Suihua City[D]. Harbin: Harbin Normal University, 2020.
[4] 张良, 宋卫杰. 放射性释放源项反演模型的初步研究[J]. 中国辐射卫生,2021,30(1):63-68. DOI: 10.13491/j.issn.1004-714X.2021.01.014
Zhang L, Song WJ. Preliminary study on inversion model of radioactive release source terms[J]. Chin J Radiol Health, 2021, 30(1): 63-68. DOI: 10.13491/j.issn.1004-714X.2021.01.014
[5] 郑金阁, 程卫亚, 王晨潇, 等. 应用CFD方法研究结构对管道内气体混合均匀性影响[J]. 中国辐射卫生,2022,31(2):172-180. DOI: 10.13491/j.issn.1004-714X.2022.02.008
Zheng JG, Cheng WY, Wang CX, et al. Computational fluid dynamics analysis of influence of different pipe structures on gas mixing uniformity[J]. Chin J Radiol Health, 2022, 31(2): 172-180. DOI: 10.13491/j.issn.1004-714X.2022.02.008
[6] 邓景成, 刘思伟, 张冬阳. 大风条件下的交通污染物扩散路径模拟研究[J]. 环境科学与管理,2023,48(4):39-44. DOI: 10.3969/j.issn.1673-1212.2023.04.010
Deng JC, Liu SW, Zhang DY. Simulation study on diffusion path of traffic pollutants under strong wind[J]. Environ Sci Manag, 2023, 48(4): 39-44. DOI: 10.3969/j.issn.1673-1212.2023.04.010
[7] Röckle R. Bestimmung der Strömungsverhaltnisse im Bereich komplexer Bebauungsstrukturen[D]. Germany: Vom Fachbereich Mechanik, der Technischen Hochschule Darmstadt, 1990.
[8] Singh B, Hansen BS, Brown MJ, et al. Evaluation of the QUIC-URB fast response urban wind model for a cubical building array and wide building street canyon[J]. Environ Fluid Mech, 2008, 8(4): 281-312. DOI: 10.1007/s10652-008-9084-5
[9] Nelson MA, Williams MD, Zajic D, et al. Evaluation of an urban vegetative canopy scheme and impact on plume dispersion[C]//8th Symposium on the Urban Environment. Phoenix: American Meteorological Society, 2009.
[10] Lundquist JK, Chow FK, Mirocha JD, et al. An improved WRF for urban-scale and complex-terrain applications[C]//7th Symposium on the Urban Environment. San Diego: American Meteorological Society, 2007.
[11] Gromke C, Buccolieri R, Di Sabatino S, et al. Dispersion study in a street canyon with tree planting by means of wind tunnel and numerical investigations–evaluation of CFD data with experimental data[J]. Atmos Environ, 2008, 42(37): 8640-8650. DOI: 10.1016/j.atmosenv.2008.08.019
[12] Moonen P, Gromke C, Dorer V. Performance assessment of Large Eddy Simulation (LES) for modeling dispersion in an urban street canyon with tree planting[J]. Atmos Environ, 2013, 75: 66-76. DOI: 10.1016/j.atmosenv.2013.04.016
[13] 严磊, 李妍, 何旭辉, 等. 高山峡谷桥址处风场特性的大涡模拟研究[J]. 中南大学学报(自然科学版),2023,54(1):137-145. DOI: 10.11817/j.issn.1672-7207.2023.01.013
Yan L, Li Y, He XH, et al. Large-eddy simulation study of wind characteristics at bridge sites in high mountain canyons[J]. J Central South Univ (Sci Technol), 2023, 54(1): 137-145. DOI: 10.11817/j.issn.1672-7207.2023.01.013
[14] 高杨, 王占朝. 应用AERMOD模型预测大气污染物浓度的影响因素分析[J]. 环境影响评价,2021,43(3):55-60. DOI: 10.14068/j.ceia.2021.03.012
Gao Y, Wang ZC. Analysis of the influencing factors of applying AERMOD model to predict the concentration of air pollutants[J]. Environ Impact Assess, 2021, 43(3): 55-60. DOI: 10.14068/j.ceia.2021.03.012
|
|
|
|
