活塞(光学)
通风(建筑)
能量(信号处理)
汽车工程
火车
海洋工程
风速
新鲜空气
工程类
模拟
环境科学
机械工程
气象学
数学
物理
波前
光学
统计
地图学
入口
地理
作者
Deqiang He,Xiaoliang Teng,Yanjun Chen,Bin Liu,Jinxin Wu
标识
DOI:10.1016/j.seta.2021.101805
摘要
Ventilation and energy saving play a vital role in the sustainable development of cities, and the fresh air caused by the piston effect is closely connected with ventilation and energy savings of metro stations. This paper aims to propose a general theoretical formula of piston wind and analyze the energy-saving effects of metro station ventilation system in multi-vehicle models using fresh air. Firstly, the variation trend of velocity field of the numerical simulation result is verified by being compared with on-site experimental data. Secondly, a general theoretical formula of piston wind is put forward, which could be applied in various situations of the train running in the tunnel. To be specific, the factors that influence the piston wind can be investigated by this formula. Thirdly, the energy-saving effects of multiple-vehicle models are discussed and compared with the single-vehicle model. The results show that the energy savings of multi-vehicle models depend on the location, state, and the number of trains in the tunnel. Moreover, the fresh air velocity is a critical factor impacting the energy savings of metro stations. Namely, based on the utilized fresh air volume of the station entrance-exit and the operation strategy of metro station ventilation system, the energy saving can be obtained. Besides, the fresh air velocity acquired by prediction is more convenient than by field test and numerical simulation. Thus, it is essential to forecast the fresh air speed. Finally, the fresh air velocity is predicted based on deep learning, and the prediction is applicable to analyze the energy-saving effects of metro stations utilizing fresh air.
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