基于动态网格技术和离散相模型的地铁隧道活塞风特性及通风竖井井口污染物扩散研究
燕成飞1郑学林1臧建彬2
Piston Wind Characteristics and Ventilation Shaft Pollutant Diffusion in Metro Tunnel Based on Dynamic Grid Technology and DPM
YAN ChengfeiZHENG XuelinZANG Jianbin
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作者信息:1.上海海事大学商船学院，201306，上海;
2.同济大学机械与能源工程学院，201804，上海
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Affiliation:Merchant shipping college, Shanghai maritime university, 201306, Shanghai, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2021.06.007
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中图分类号/CLCN:U453.5
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栏目/Col:研究报告
摘要:
利用动态网格技术和 DPM（离散相模型）技术，并使用控制变量法分析了地铁列车行车速度、阻塞比、通风竖井数量等因素对隧道内活塞风速度场分布规律的影响，以及不同竖井数量下井口释放污染物的扩散规律。结果表明：隧道内活塞风速度场的分布情况及通风房间内污染物的衰减规律与试验数据基本一致；竖井风量和行车速度、阻塞比成正比，而与竖井数量无明显关系；活塞风速与行车速度、阻塞比成正比，而与竖井数量亦无明显关系；当井口释放污染物时竖井的数量越多，隧道内的污染越严重。
Abstracts:
With dynamic grid technology and DPM technology, control variable method is used to analyze the influence of factors including metro train speed, blocking ratio, number of ventilation shafts on piston wind flow field distribution pattern in the tunnel, and diffusion pattern of pollutants under different shaft numbers. Results show that the distribution situation of piston wind flow field in tunnel and the decay pattern of pollutants in ventilation room is in accordance with test data; the wind volume is proportional to train speed and blocking ratio but has no obvious relationship with the number of ventilation shafts; piston wind speed is directly proportional to train speed and blocking ratio, but has no obvious relationship with the number of ventilation shafts. When pollutants are diffusing, the more ventilation shafts there are, the more serious the pollution in tunnel will be.
引文 / Ref:
燕成飞，郑学林，臧建彬.基于动态网格技术和离散相模型的地铁隧道活塞风特性及通风竖井井口污染物扩散研究[J].城市轨道交通研究，2021，24（6）：29.
YAN Chengfei，ZHENG Xuelin，ZANG Jianbin.Piston Wind Characteristics and Ventilation Shaft Pollutant Diffusion in Metro Tunnel Based on Dynamic Grid Technology and DPM[J].Urban mass transit，2021，24（6）：29.
YAN Chengfei，ZHENG Xuelin，ZANG Jianbin.Piston Wind Characteristics and Ventilation Shaft Pollutant Diffusion in Metro Tunnel Based on Dynamic Grid Technology and DPM[J].Urban mass transit，2021，24（6）：29.
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