基于激光雷达数据的首都机场风场模拟

摘要/Abstract

摘要： 低空风效应是指在特定的风况条件下,机场建筑物或其他位于跑道附近的人工结构对气流
造成显著扰动的现象,该效应易引起湍流甚至是出现风切变,进而给飞机的升降过程带来困难。
采用计算流体动力学(Computational fluid dynamics, CFD)方法对首都机场进行风场模拟,
并基于CFD在输入风速设置上的局限性,提出一种将高精度、高分辨率的激光雷达测风数据
导入CFD的方法,来研究这些地物对首都机场风速的影响。通过对模拟结果的分析,在风速
为11~15 m/s的西北风条件下的东跑道以及在同等风速的东南风条件下的西跑道与中间跑道均受到较大影响。

关键词: 低空风效应, 激光雷达, 计算流体动力学方法, 风场模拟

Abstract: The low-level wind effect refers to the phenomenon that the airport structure or
other artificial structures located near the runway cause significant disturbance
to the airflow under certain wind conditions. This effect is likely to cause
turbulence or even wind shear, and bring difficulties to the aircrafts' takeoff
and landing. The computational fluid dynamics(CFD) method was adopted to simulate the wind field at Capital
Airport, Beijing, China. To overcome the limitation of CFD in the setting of input wind speed,
high-precision and high-resolution data measured by lidar were introduced into
CFD as input condition to investigate the influence of buildings and
artificial structures on wind speed at Capital Airport. The simulation
results show that when the wind speed of 11~15 m/s under northwest wind
condition was applied, the air flow near east runway was influenced
significantly. The same situation happened in the west runway and
the middle runway under the south wind condition with the same wind speed.

Key words: low-level wind effect, lidar;, computational fluid dynamics nethod, wind field simulation

刘磊吴松华张洪玮. 基于激光雷达数据的首都机场风场模拟[J]. 大气与环境光学学报, 2019, 14(4): 259-265.

参考文献

1 Cheng Xueling, Hu Fei, Zeng Qingcun. Refined numerical simulation of complex terrain flow field [J]. Climatic and Environmental Research, 2015, 20(1): 1-10(in Chinese). 程雪玲, 胡非, 曾庆存. 复杂地形风场的精细数值模拟 [J]. 气候与环境研究, 2015, 20(1): 1-10． 2 Yang Jian. Nested WRF and CFD for Numerical Simulation of Localized Typhoon Wind Field [D]. Harbin: Master's Thesis of Harbin Institute of Technology. 2015(in Chinese). 杨剑. WRF与CFD嵌套的局地台风风场数值模拟研究 [D]. 哈尔滨: 哈尔滨工业大学硕士论文, 2015. 3 Fang Yanying, Xu Haiming, Zhu Rong, et al. Study on numerical simulation of wind energy resources based on WRF and CFD models [J]. Meteorological, 2012, 38(11): 1378-1389(in Chinese). 方艳莹, 徐海明, 朱蓉, 等. 基于WRF和CFD软件结合的风能资源数值模拟试验研究 [J]. 气象, 2012, 38(11): 1378-1389. 4 Franke J, Hirsch C, Jensen A G, et al. Recommendations on the use of CFD in wind engineering [C]. Proceedings of the International Conference on Urban Wind Engineering and Building Aerodynamics, 2004. 5 Liu Mingliang, Zhang Siqing, Li Shengnan. Analysis of mesh on the CFD simulation results [J]. Hydropower and Pumped Storage, 2016, 2(4): 41-47(in Chinese). 刘明亮, 张思青, 李胜男. 网格对CFD模拟结果的影响分析 [J]. 水电与抽水蓄能, 2016, 2(4): 41-47. 6 Wang Yuan, Lu Zhiliang, Guo Tongqing. CFD simulation of wind farm over natural terrain based on $k-varepsilon$ model [J]. Acta Energiae Solaris Sinica, 2016, 37(4): 1037-1042(in Chinese). 王远, 陆志良, 郭同庆. 基于$k-varepsilon$模型的实际地形风场CFD模拟研究 [J].太阳能学报, 2016, 37(4): 1037-1042. 7 Ma Minjin, Lin Chao, Zhao Surong, et al. Characteristics and a numerical study of low-level wind shear over Beijing Capital International Airport [J]. Journal of Lanzhou University: Natural Sciences, 2013, 49(3): 354-360(in Chinese). 马敏劲, 林超, 赵素蓉, 等. 北京首都国际机场低空风切变观测分析和数值模拟 [J]. 兰州大学学报: 自然科学版,2013, 49(3): 354-360. 8 Franke, J, Hirsch C, Krus H W, et al. Recommendations on the use of CFD in wind engineering [J]. Cost Action C, 2004, 14: C1. 9 Deng Yuanchang, Liu Sha, Yu Zhi, et al. Effect of roughness on CFD wind field simulation over natural terrain [J]. Acta Energiae Solaris Sinica, 2010, 31(12): 1644-1648(in Chinese). 邓院昌, 刘沙, 余志, 等. 实际地形风场CFD模拟中粗糙度的影响分析 [J]. 太阳能学报, 2010, 31(12): 1644-1648. 10 Liu C, Leung D Y C, Man A C S, et al. Computational fluid dynamics simulation of the wind flow over an airport terminal building [J]. Journal of Zhejiang University-Science A, 2010, 11(6): 389-401. 11 Li Jun, Hu Fei, Liu Lei, et al. On estimation of surface roughness for wind energy resources assessment [J]. Resources Science, 2011, 33(12): 2341-2348(in Chinese). 李军, 胡非, 刘磊, 等. 风能资源评估中地表粗糙度的研究 [J]. 资源科学, 2011, 33(12): 2341-2348. 12 Blocken B, van der Hout A, Dekker J, et al. CFD simulation of wind flow over natural complex terrain: Case study with validation by field measurements for Ria de Ferrol, Galicia, Spain [J]. Journal of Wind Engineering and Industrial Aerodynamics, 2015, 147: 43-57. 13 Li L, Chan P W. Numerical simulation study of the effect of buildings and complex terrain on the low-level winds at an airport in typhoon situation [J]. Meteorologische Zeitschrift, 2012, 21(2): 183-192.

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