Article(id=1149729533542183474, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149729526025994706, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1672-6073.2025.03.004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720454400000, receivedDateStr=2024-07-09, revisedDate=1728576000000, revisedDateStr=2024-10-11, acceptedDate=null, acceptedDateStr=null, onlineDate=1752046481738, onlineDateStr=2025-07-09, pubDate=1748707200000, pubDateStr=2025-06-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752046481738, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752046481738, creator=13701087609, updateTime=1752046481738, updator=13701087609, issue=Issue{id=1149729526025994706, tenantId=1146029695717560320, journalId=1146123302524792850, year='2025', volume='38', issue='3', pageStart='1', pageEnd='161', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1752046479946, creator=13701087609, updateTime=1753780086246, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1157000797948039291, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149729526025994706, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1157000797948039292, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149729526025994706, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=27, endPage=34, ext={EN=ArticleExt(id=1149729533718344251, articleId=1149729533542183474, tenantId=1146029695717560320, journalId=1146123302524792850, language=EN, title=Piston Wind Characteristics of Moving Trains in Subway Tunnels, columnId=1152669340382966151, journalTitle=Urban Rapid Rail Transit, columnName=Forum of Rapid Rail Transit, runingTitle=null, highlight=null, articleAbstract=

During subway train operation in tunnels, piston wind is generated, which significantly affects the tunnel flow field. Understanding piston wind characteristics is crucial for its effective utilization. It is of great significance to study the characteristics of piston wind for rational utilization of piston wind. Based on Bernoulli equation of unsteady flow, a lumped parameter theoretical model of piston wind in subway tunnel is established, and the characteristics of unsteady piston wind are analyzed. In order to verify the accuracy of the theoretical model, a reduced size model test bench of 1:16 was established, and the piston wind speed was tested experimentally. The comparison between the model value and the measured value shows that the Pearson correlation coefficient is higher than 0.98, and the average error is lower than 13%, which verifies the correlation and accuracy of the theoretical model. By using the lumped parameter theory model, the influence of different factors on the piston wind in subway tunnel is explored, and the grey correlation degree is analyzed. The results show that the congestion ratio is the biggest factor affecting the ventilation effect of the tunnel piston, followed by the train length and train speed, and the tunnel length is the least. Based on this, a fitting formula for the ventilation effect of the piston in common subway tunnels in China is proposed.

, correspAuthors=Jijian LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jijian LIU, Xin MENG, Huifeng LAN, Qianying WANG, Yuesong HE, Fengjun ZHANG, Ling ZHANG, Wenwen JIANG), CN=ArticleExt(id=1149729565402116426, articleId=1149729533542183474, tenantId=1146029695717560320, journalId=1146123302524792850, language=CN, title=地铁隧道运动列车的活塞风特性研究, columnId=1152669340680761737, journalTitle=都市快轨交通, columnName=快轨论坛, runingTitle=null, highlight=null, articleAbstract=

地铁列车在隧道内行驶过程中会形成活塞风,对隧道內的流场产生一定的影响,研究活塞风特性对合理利用它具有重大意义。基于非恒定流动伯努利方程,建立地铁隧道內活塞风的集总参数理论模型,从而分析非稳态活塞风特性。为了验证理论模型的准确性,建立1:16的缩尺寸模型试验台,并对活塞风风速进行测试。模型值与实测值对比结果表明,皮尔逊相关性系数高于 0.98,平均误差低于13%,验证了理论模型的相关性和准确性;利用该集总参数理论模型,探究不同因素对地铁隧道活塞风的影响,并进行灰关联度分析。研究结果表明,阻塞比是影响隧道活塞风通风效果的最大因素,列车长度和列车速度次之,而隧道长度最小,据此提出一个适用于我国常见地铁隧道活塞风通风效果的拟合公式。

, correspAuthors=刘纪俭, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=AEbofUY8kewg58jNOjEOsQ==, magXml=m2UkGvvhvG32G66MzryD4w==, pdfUrl=null, pdf=Fttb0QSLrXd4A39LKgtg3w==, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=NYgLTBD4JMdWPFSbYGwHfA==, mapNumber=null, authorCompany=null, fund=null, authors=

刘纪俭,男,大学本科,正高级工程师,从事地铁隧道通风气流组织的研究,

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刘纪俭,男,大学本科,正高级工程师,从事地铁隧道通风气流组织的研究,

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刘纪俭,男,大学本科,正高级工程师,从事地铁隧道通风气流组织的研究,

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Field experiments study on pressure characteristics of subway tunnel wall[J]. Journal of Central South University (Science and Technology), 2022, 53(5): 1643-1654., articleTitle=Field experiments study on pressure characteristics of subway tunnel wall, refAbstract=null)], funds=[Fund(id=1154050892660724007, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, awardId=2018V3-0119, language=CN, fundingSource=国家重点研发计划(2018V3-0119), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1154050883651358884, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, xref=1, ext=[AuthorCompanyExt(id=1154050883655553189, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, companyId=1154050883651358884, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Qingdao Metro Group Co., Ltd. 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language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 天津大学 环境科学与工程学院 天津 300354)])], figs=[ArticleFig(id=1154050890165113087, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, language=EN, label=Figure 1, caption=Schematic diagram of a piston wind model of a moving train, figureFileSmall=R4xSn2yL68NkL1aJAehabg==, figureFileBig=euIZWbFuOG42Fe/XcQ2Lbg==, tableContent=null), ArticleFig(id=1154050890232221952, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, language=CN, label=图1, caption=行驶列车活塞风模型简图, figureFileSmall=R4xSn2yL68NkL1aJAehabg==, figureFileBig=euIZWbFuOG42Fe/XcQ2Lbg==, tableContent=null), ArticleFig(id=1154050890295136513, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, language=EN, label=Figure 2, caption=Simplified diagram of tunnel section shape, figureFileSmall=YpKkZ4Es2dVXi/PKfDCZOg==, 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隧道尺寸 长度/m 宽度/m 高度/m 时间 /s
原型 960 4.8 5.44 4
模型 60 0.3 0.34 1
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隧道尺寸 长度/m 宽度/m 高度/m 时间 /s
原型 960 4.8 5.44 4
模型 60 0.3 0.34 1
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车辆尺寸 长度/m 宽度/m 高度/m 速度/(m/s) 加速度/( )
原型 80 3.2 3.84 12 1
模型 5 0.2 0.34 3 1
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车辆尺寸 长度/m 宽度/m 高度/m 速度/(m/s) 加速度/( )
原型 80 3.2 3.84 12 1
模型 5 0.2 0.34 3 1
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工况 x0 x1 x2 x3 x4
1 1.00 1.00 1.00 1.00 1.00
2 1.22 1.43 1.00 1.00 0.62
3 1.41 1.86 1.00 1.00 0.62
4 1.53 2.11 1.00 1.00 0.62
5 1.60 2.29 1.00 1.00 0.62
6 1.66 2.43 1.00 1.00 0.62
7 1.71 2.54 1.00 1.00 0.62
8 1.75 2.64 1.00 1.00 0.62
9 1.79 2.72 1.00 1.00 0.62
10 1.82 2.80 1.00 1.00 0.62
11 1.85 2.86 1.00 1.00 0.62
12 0.97 2.11 0.64 1.00 0.62
13 1.17 2.11 0.76 1.00 0.62
14 1.29 2.11 0.84 1.00 0.62
15 1.38 2.11 0.90 1.00 0.62
16 1.46 2.11 0.96 1.00 0.62
17 1.53 2.11 1.00 1.00 0.62
18 1.58 2.11 1.04 1.00 0.62
19 1.63 2.11 1.07 1.00 0.62
20 1.68 2.11 1.11 1.00 0.62
21 1.72 2.11 1.14 1.00 0.62
22 3.49 2.11 1.00 2.24 0.62
23 2.08 2.11 1.00 1.35 0.62
24 1.53 2.11 1.00 1.00 0.62
25 1.23 2.11 1.00 0.81 0.62
26 1.04 2.11 1.00 0.69 0.62
27 0.91 2.11 1.00 0.60 0.62
28 0.82 2.11 1.00 0.54 0.62
29 0.75 2.11 1.00 0.49 0.62
30 0.69 2.11 1.00 0.45 0.62
31 0.64 2.11 1.00 0.41 0.62
32 0.60 2.11 1.00 0.39 0.62
33 0.56 2.11 1.00 0.36 0.62
34 2.64 2.11 1.00 1.00 0.36
35 1.99 2.11 1.00 1.00 0.54
36 1.69 2.11 1.00 1.00 0.60
37 1.54 2.11 1.00 1.00 0.62
38 1.47 2.11 1.00 1.00 0.63
39 1.46 2.11 1.00 1.00 0.63
40 1.52 2.11 1.00 1.00 0.59
41 1.69 2.11 1.00 1.00 0.48
42 2.23 2.11 1.00 1.00 0.20
), ArticleFig(id=1154050892283236642, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, language=CN, label=表3, caption=原始数据初值化处理, figureFileSmall=null, figureFileBig=null, tableContent=
工况 x0 x1 x2 x3 x4
1 1.00 1.00 1.00 1.00 1.00
2 1.22 1.43 1.00 1.00 0.62
3 1.41 1.86 1.00 1.00 0.62
4 1.53 2.11 1.00 1.00 0.62
5 1.60 2.29 1.00 1.00 0.62
6 1.66 2.43 1.00 1.00 0.62
7 1.71 2.54 1.00 1.00 0.62
8 1.75 2.64 1.00 1.00 0.62
9 1.79 2.72 1.00 1.00 0.62
10 1.82 2.80 1.00 1.00 0.62
11 1.85 2.86 1.00 1.00 0.62
12 0.97 2.11 0.64 1.00 0.62
13 1.17 2.11 0.76 1.00 0.62
14 1.29 2.11 0.84 1.00 0.62
15 1.38 2.11 0.90 1.00 0.62
16 1.46 2.11 0.96 1.00 0.62
17 1.53 2.11 1.00 1.00 0.62
18 1.58 2.11 1.04 1.00 0.62
19 1.63 2.11 1.07 1.00 0.62
20 1.68 2.11 1.11 1.00 0.62
21 1.72 2.11 1.14 1.00 0.62
22 3.49 2.11 1.00 2.24 0.62
23 2.08 2.11 1.00 1.35 0.62
24 1.53 2.11 1.00 1.00 0.62
25 1.23 2.11 1.00 0.81 0.62
26 1.04 2.11 1.00 0.69 0.62
27 0.91 2.11 1.00 0.60 0.62
28 0.82 2.11 1.00 0.54 0.62
29 0.75 2.11 1.00 0.49 0.62
30 0.69 2.11 1.00 0.45 0.62
31 0.64 2.11 1.00 0.41 0.62
32 0.60 2.11 1.00 0.39 0.62
33 0.56 2.11 1.00 0.36 0.62
34 2.64 2.11 1.00 1.00 0.36
35 1.99 2.11 1.00 1.00 0.54
36 1.69 2.11 1.00 1.00 0.60
37 1.54 2.11 1.00 1.00 0.62
38 1.47 2.11 1.00 1.00 0.63
39 1.46 2.11 1.00 1.00 0.63
40 1.52 2.11 1.00 1.00 0.59
41 1.69 2.11 1.00 1.00 0.48
42 2.23 2.11 1.00 1.00 0.20
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影响因素 列车车速 列车长度 阻塞比 隧道长度
关联度 0.648 9 0.7138 0.741 5 0.4721
), ArticleFig(id=1154050892392288548, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, language=CN, label=表4, caption=各因素关联度, figureFileSmall=null, figureFileBig=null, tableContent=
影响因素 列车车速 列车长度 阻塞比 隧道长度
关联度 0.648 9 0.7138 0.741 5 0.4721
), ArticleFig(id=1154050892442620197, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149729533542183474, language=EN, label=Table 5, caption=The coefficient by which the formula is fitted, figureFileSmall=null, figureFileBig=null, tableContent=
公式系数
数值 -0.4824 0.0684 0.2306 157.5355 9.2406
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公式系数
数值 -0.4824 0.0684 0.2306 157.5355 9.2406
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地铁隧道运动列车的活塞风特性研究
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刘纪俭 1 , 孟鑫 1 , 兰慧峰 1 , 王倩颖 2 , 何岳松 2 , 张凤君 1 , 张领 1 , 姜文文 1
都市快轨交通 | 快轨论坛 2025,38(3): 27-34
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都市快轨交通 | 快轨论坛 2025, 38(3): 27-34
地铁隧道运动列车的活塞风特性研究
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刘纪俭1 , 孟鑫1, 兰慧峰1, 王倩颖2, 何岳松2, 张凤君1, 张领1, 姜文文1
作者信息
  • 1 青岛地铁集团有限公司 青岛 266100
  • 2 天津大学 环境科学与工程学院 天津 300354
  • 刘纪俭,男,大学本科,正高级工程师,从事地铁隧道通风气流组织的研究,

Piston Wind Characteristics of Moving Trains in Subway Tunnels
Jijian LIU1 , Xin MENG1, Huifeng LAN1, Qianying WANG2, Yuesong HE2, Fengjun ZHANG1, Ling ZHANG1, Wenwen JIANG1
Affiliations
  • 1 Qingdao Metro Group Co., Ltd. Qingdao 266100
  • 2 School of Environmental Science and Engineering Tianjin University Tianjin 300354
出版时间: 2025-06-01 doi: 10.3969/j.issn.1672-6073.2025.03.004
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地铁列车在隧道内行驶过程中会形成活塞风,对隧道內的流场产生一定的影响,研究活塞风特性对合理利用它具有重大意义。基于非恒定流动伯努利方程,建立地铁隧道內活塞风的集总参数理论模型,从而分析非稳态活塞风特性。为了验证理论模型的准确性,建立1:16的缩尺寸模型试验台,并对活塞风风速进行测试。模型值与实测值对比结果表明,皮尔逊相关性系数高于 0.98,平均误差低于13%,验证了理论模型的相关性和准确性;利用该集总参数理论模型,探究不同因素对地铁隧道活塞风的影响,并进行灰关联度分析。研究结果表明,阻塞比是影响隧道活塞风通风效果的最大因素,列车长度和列车速度次之,而隧道长度最小,据此提出一个适用于我国常见地铁隧道活塞风通风效果的拟合公式。

地铁隧道  /  活塞风  /  理论模型  /  灰关联度

During subway train operation in tunnels, piston wind is generated, which significantly affects the tunnel flow field. Understanding piston wind characteristics is crucial for its effective utilization. It is of great significance to study the characteristics of piston wind for rational utilization of piston wind. Based on Bernoulli equation of unsteady flow, a lumped parameter theoretical model of piston wind in subway tunnel is established, and the characteristics of unsteady piston wind are analyzed. In order to verify the accuracy of the theoretical model, a reduced size model test bench of 1:16 was established, and the piston wind speed was tested experimentally. The comparison between the model value and the measured value shows that the Pearson correlation coefficient is higher than 0.98, and the average error is lower than 13%, which verifies the correlation and accuracy of the theoretical model. By using the lumped parameter theory model, the influence of different factors on the piston wind in subway tunnel is explored, and the grey correlation degree is analyzed. The results show that the congestion ratio is the biggest factor affecting the ventilation effect of the tunnel piston, followed by the train length and train speed, and the tunnel length is the least. Based on this, a fitting formula for the ventilation effect of the piston in common subway tunnels in China is proposed.

subway tunnel  /  piston wind  /  theoretical model  /  grey correlation degree
刘纪俭, 孟鑫, 兰慧峰, 王倩颖, 何岳松, 张凤君, 张领, 姜文文. 地铁隧道运动列车的活塞风特性研究. 都市快轨交通, 2025 , 38 (3) : 27 -34 . DOI: 10.3969/j.issn.1672-6073.2025.03.004
Jijian LIU, Xin MENG, Huifeng LAN, Qianying WANG, Yuesong HE, Fengjun ZHANG, Ling ZHANG, Wenwen JIANG. Piston Wind Characteristics of Moving Trains in Subway Tunnels[J]. Urban Rapid Rail Transit, 2025 , 38 (3) : 27 -34 . DOI: 10.3969/j.issn.1672-6073.2025.03.004
随着城镇化进程的加快, 地铁在城市交通中扮演着日益重要的角色。截至 2023 年底,我国共计 29 个城市的地铁规模达到了 ${100}\mathrm{\;{km}}$ 及以上 [1] 。地铁在隧道中行驶时, 隧道壁面对空气流动具有阻碍作用。地铁前进方向的空气受到挤压后压力升高, 一部分向前流动, 另一部分则通过列车与隧道之间的环状空间向后运动。这种随着列车运行方向流动的气流被称为 “活塞风” [2] 。列车在运行过程中产生的这种活塞效应可以通过引入新风降低隧道机械通风系统的能耗, 并将列车运行产生的余热、余湿带出隧道, 提高隧道内的空气品质 [3] 。此外,活塞风也会影响火灾烟气的控制。 由于活塞风总是与列车运行方向相同, 即使起火列车减速停车后, 高温烟气在活塞风的影响下仍会继续向前蔓延,控制难度巨大 [4]
目前, 对于活塞风的研究主要有实验研究、数值模拟和理论分析。虽然全尺寸实验能够将实验对象的全部特征真实反映出来, 但是实施难度较大且费用昂贵。因此, 大多数实验研究选择建立缩尺寸模型。KIM 等 [5]$1 : {20}$ 比例尺的模型隧道内对地铁列车产生的活塞风进行实验分析, 研究通风竖井的流量和周围隧道的流场特征。随着计算机与计算流体力学的发展, 计算精度提高, 一些学者开始采用更加方便的数值模拟方法 [6] 。LOPEZ 等 [7] 利用 CFD 建模并研究了活塞效应对整体通风性能的影响, 量化了地铁通风系统不同参数的影响。但 CFD 计算也存在诸如动态网格模型的网格量巨大等缺陷, 使得研究通常只针对特定隧道, 通用性差。而通过将活塞效应简化为一维模型, 并联立伯努利方程和连续性方程求解的理论模型, 具有计算速度快、成本低等优点, 非常适合解决该问题。由于理论建模比较复杂, 现有的相关研究很少。
另一方面, 活塞风受列车速度、列车和隧道长度、 阻塞比等多种因素的影响, 但很少有研究关注这些因素间的耦合效应。例如, CHOI 等 [8] 只评估了列车车头长度和隧道横截面积的作用。CROSS 等 [9] 也只研究了改变列车的阻塞比对活塞风的影响。因此, 还缺乏一种通用的方法来评估活塞风的通风效果。
针对以上研究的不足, 本文从理论分析出发, 基于伯努利方程建立地铁隧道活塞风的数学模型, 其准确性经过了缩尺寸实验测试的验证。利用验证过的集总参数理论模型研究活塞风的 4 个影响因素的敏感性, 并基于灰关联分析给出了不同因素的影响程度排序。 最后,提出通用预测公式, 可用于预测我国大部分地铁隧道活塞风的通风效果。
为探究活塞风的影响因素, 首先对活塞效应建立理论模型。考虑活塞风具有不可压缩、非稳态和一维流动的特性, 本研究基于非恒定流伯努利方程, 建立列车通过隧道时所产生的活塞风集总参数理论模型。
$ \frac{{u}_{1}^{2}}{2g} + \frac{{P}_{1}}{\gamma } + {Z}_{1} = \frac{{u}_{2}^{2}}{2g} + \frac{{P}_{2}}{\gamma } + {Z}_{2} + {h}_{\mathrm{f}} + \frac{\beta }{g}{\int }_{s}\frac{\partial u}{\partial \tau }\mathrm{d}s $
式中, ${u}_{1}$ 为断面 1 的速度, $\mathrm{m}/\mathrm{s};{u}_{2}$ 为断面 2 的速度, $\mathrm{m}/\mathrm{s}$ ; ${P}_{1}$ 为断面 1 的压强, $\mathrm{{Pa}};{P}_{2}$ 为断面 2 的压强, $\mathrm{{Pa}};{Z}_{1}$ 为断面 1 的高程, $\mathrm{m};{Z}_{2}$ 为断面 2 的高程, $\mathrm{m}$ ; ${h}_{\mathrm{f}}$ 为沿程阻力损失, ${\mathrm{m}}^{2}/{\mathrm{s}}^{2};\beta$ 为流动不均匀系数,在隧道内 $\beta \approx 1;\gamma$ 为容重, $\mathrm{N}/{\mathrm{m}}^{3};s$ 为活塞风沿流动方向流动的距离, $\mathrm{m};\frac{\beta }{g}{\int }_{s}\frac{\partial u}{\partial \tau }\mathrm{d}s$ 为惯性水头, $\mathrm{m}$
地铁列车在隧道内的运动规律一般为加速一匀速一减速的过程。故下文将分别建立启动阶段、匀速阶段、匀减速阶段和停车阶段的活塞风模型, 见图1
根据连续性方程:
$ {A}_{1}{v}_{1}\mathrm{\;d}\tau = {Av}\mathrm{\;d}\tau + \left( {A - {A}_{1}}\right) \left( {{v}_{\mathrm{s}} - {v}_{1}}\right) \mathrm{d}\tau $
整理得
$ {v}_{\mathrm{s}} = \frac{{A}_{1}{v}_{1} - {Av}}{A - {A}_{1}} + {v}_{1} = \frac{{v}_{1} - v}{1 - \alpha } $
式中, ${v}_{1}$ 为列车行驶速度, $\mathrm{m}/\mathrm{s};{v}_{\mathrm{s}}$ 为环状空间空气回流速度, $\mathrm{m}/\mathrm{s};v$ 为隧道内活塞风风速, $\mathrm{m}/\mathrm{s};A$ 为隧道截面面积, ${\mathrm{m}}^{2};{A}_{1}$ 为列车截面面积, ${\mathrm{m}}^{2};\alpha$ 为阻塞比。
针对图1中的列车运动状态, 列车的运动速度为 ${v}_{1}$ ,隧道内活塞风风速为 $v$ ,对断面 1-2 的控制体建立非稳态伯努利方程, 即
$ {P}_{\mathrm{a}} = {P}_{2} + \frac{1}{2}\rho {v}^{2} + \left( {{\xi }_{1} + \lambda \frac{{l}_{12}}{{D}_{\mathrm{h}}}}\right) \frac{1}{2}\rho {v}^{2} + {l}_{12}\rho \frac{\mathrm{d}v}{\mathrm{\;d}\tau } $
式中, ${P}_{\mathrm{a}}$ 为大气压力, $\mathrm{{Pa}};{P}_{2}$ 为断面 2 的压强, $\mathrm{{Pa}}$ ; $\rho$ 为空气密度, $\mathrm{{kg}}/{\mathrm{m}}^{3};{\xi }_{1}$ 为隧道进口局部阻力系数, 取 0.50 ; $\lambda$ 为隧道内的沿程阻力系数,取 0.023 ; ${l}_{12}$ 为断面 1 与断面 2 之间的隧道长度, $\mathrm{m};{D}_{\mathrm{h}}$ 为隧道的水力直径, $\mathrm{m}$
断面 2 与断面 3 之间控制体的伯努利方程为
$ {P}_{3} = {P}_{2} + \left( {{\xi }_{2} + {\lambda }_{1}\frac{{l}_{1}}{d} + {\xi }_{3}}\right) \frac{1}{2}\rho {v}_{\mathrm{s}}^{2} + \rho {l}_{1}\frac{\mathrm{d}{v}_{\mathrm{s}}}{\mathrm{d}\tau } $
式中, ${P}_{3}$ 为断面 3 的压力, $\mathrm{{Pa}};{\xi }_{2}$ 为列车后部的局部阻力系数,取 0.22; ${\xi }_{3}$ 为列车前部的局部阻力系数, 取 0.28; ${\lambda }_{1}$ 为环状空间沿程阻力系数,取 0.019; $d$ 为环状空间水力直径, $\mathrm{m}$${l}_{1}$ 为列车长度, $\mathrm{m}$
断面 3 与断面 4 之间控制体的伯努利方程为
$ {P}_{3} + \frac{1}{2}\rho {v}^{2} = {P}_{\mathrm{a}} + \left( {{\xi }_{4} + \lambda \frac{{l}_{34}}{D}}\right) \frac{1}{2}\rho {v}^{2} + \rho {l}_{34}\frac{\mathrm{d}v}{\mathrm{\;d}\tau } $
式中, ${\xi }_{4}$ 为隧道出口局部阻力系数,取 ${1.0};{l}_{34}$ 为断面 3 与断面 4 之间的隧道段长度, $\mathrm{m}$
缩尺寸模型的设计应主要以相似理论为依据, 保证模型中的流体运动与原型流动具有相似性 [10] 。根据尼古拉斯曲线, 当隧道内的空气流动状态进入湍流时, 断面风速分布基本均匀,沿程阻力系数就不再与 ${Re}$ 数相关, 此时的流动阻力与惯性力均与流速的平方成正比。因此, 设计缩尺寸模型可忽略雷诺准则, 而仅保持与弗劳德准则相似。式(7) $\sim$ 式(10)列出了缩尺寸实验台(m)和实际地铁隧道(p)不同参数的相似比例。
速度比:
$ \left( \frac{{v}_{\mathrm{m}}}{{v}_{\mathrm{p}}}\right) = {\left( \frac{{L}_{\mathrm{m}}}{{L}_{\mathrm{p}}}\right) }^{\frac{1}{2}} $
加速度比:
$ \left( \frac{{a}_{\mathrm{m}}}{{a}_{\mathrm{p}}}\right) = 1 $
时间比:
$ \left( \frac{{\tau }_{\mathrm{m}}}{{\tau }_{\mathrm{p}}}\right) = {\left( \frac{{L}_{\mathrm{m}}}{{L}_{\mathrm{p}}}\right) }^{\frac{1}{2}} $
质量流率比:
$ \left( \frac{{M}_{\mathrm{m}}}{{M}_{\mathrm{p}}}\right) = {\left( \frac{{L}_{\mathrm{m}}}{{L}_{\mathrm{p}}}\right) }^{\frac{5}{2}} $
式中, ${L}_{\mathrm{m}}$ 为缩尺寸模型的几何尺寸, $\mathrm{m};{L}_{\mathrm{p}}$ 为全尺寸原型的几何尺寸, $\mathrm{m}$
目前,国内地铁隧道断面大多为马蹄形,然而在模型加工时马蹄形的隧道制作困难, 而矩形断面较易加工。在研究隧道活塞风时, 虽然不同形状的断面可能会带来边界层发展上的差异, 但在保证关键参数—— 水力直径和阻塞比一致的前提下, 这种差异通常不会显著影响隧道内的流场特性, 故所设计的缩尺寸实验台的水力直径和阻塞比与实际隧道相同,并简化为图2所示的矩形断面形式 [11]
根据消费工程师协会(The Society of Fire Protection Engineers, SFPE)的《SFPE 手册》可知, 为保证实验时活塞风的流动状态为湍流并进入阻力平方区, 缩尺寸实验的特征尺度应大于等于 ${0.3}\mathrm{\;m}$ 。为此,将缩尺寸模型实验台的特征长度比设置为 $1 : {16}$ ,此时各特征尺寸均满足 SFPE 中的要求。表1表2为缩尺寸模型的特征尺寸。
根据实验要求及实验仪器的特性, 实验系统速度测点布置如图3所示。隧道内的活塞风风速采用 TSI 热线风速仪测量, 如图4所示, 实验中将热线风速仪布置于隧道两端,测量范围、精度分别为 $0 \sim {10}\mathrm{m}/\mathrm{s}$${0.01}\mathrm{\;m}/\mathrm{s}$
隧道活塞风风速测试实验步骤如下:
1)启动风速测定仪表, 开启风速仪的自记功能;
2)列车模型在隧道内运行时, 由驱动电机控制列车运动状态, 使其按照预定速度和加(减)速度等参数进行运动;
3)数据记录完成后,改变工况并重复实验。
为验证第 1 章建立的活塞风非稳态特性理论预测模型的准确性, 在 2.1 节设计的缩尺寸实验台上进行了两组列车速度为 ${3.00}\mathrm{\;m}/\mathrm{s}$ 的实验。在设置列车的加/减速度时,参考目前我国常见的 $\mathrm{B}$ 型地铁列车, $\mathrm{B}$ 型车的启动加速度在 ${0.6} \sim {1.0}\mathrm{\;m}/{\mathrm{s}}^{2}$ ,制动减速度可达1.24 m/s212 。 同时考虑乘客的乘车舒适性, 在实际运行的过程中, 列车以 100%制动力制动,此时进站制动减速度平均值为 ${1.02}\mathrm{\;m}/{\mathrm{s}}^{2}$ ; 以 90%牵引力启动,此时出站加速度平均值为0.75m/s213 。因此,为反映实际地铁列车在启动或制动时的加速度情况, 在地铁缩尺寸实验模拟的研究中,采用 ${0.75}\mathrm{\;m}/{\mathrm{s}}^{2}$${1.00}\mathrm{\;m}/{\mathrm{s}}^{2}$ 作为典型工况。图5图6分别呈现了实验场景 $1\left( {a = {0.75}\mathrm{\;m}/{\mathrm{s}}^{2}}\right)$ 和实验场景 $2\left( {a = {1.00}\mathrm{\;m}/{\mathrm{s}}^{2}}\right)$ 的列车运动规律。
图78 分别对比了实验场景 1 和实验场景 2 的集总参数理论模型计算值和缩尺寸实验测试值。分析结果可以得出, 计算值与测试值皮尔逊相关系数分别为 0.992 7 和 0.984 7, 而平均误差分别为 12.46%和 11.63%。 皮尔逊相关系数均高于 0.98 ,且平均误差均低于 13%, 验证了理论模型的高度相关性和准确性。
探究隧道活塞风的多因素影响规律及其交互作用是有效利用活塞风的前提。列车速度、列车长度、隧道长度和列车-隧道阻塞比是 4 个主要因素。为确定这些因素的影响规律及其程度, 依次进行敏感性分析及灰关联计算。
为了确定列车速度的研究范围, 考虑列车在事故工况下的运行速度,将最小车速定为 $5\mathrm{\;m}/\mathrm{s}$ ; 考虑高速列车的全速运行场景,将最大车速定为 ${100}\mathrm{\;m}/\mathrm{s}$ 。不同车速对活塞风的影响是基于 ${1500}\mathrm{\;m}$ 长的地铁隧道进行计算的, 如图9所示。
列车在隧道中运行时, 其行驶速度将直接影响隧道内空气的流动特性。随着列车速度的增加, 空气在正、负压区域之间产生强烈的流动, 从而形成更强的活塞风效应, 使得活塞风风速增大。从图9中可以看出, 活塞风最大风速的持续时间会随着列车速度的增加而减小, 这是因为隧道长度在不同工况下是相同的, 列车速度与列车在隧道中的运行时间成反比。车速越小, 活塞风风速越小, 持续变化时间越长。随着车速从 $5\mathrm{\;m}/\mathrm{s}$ 增加到 ${100}\mathrm{\;m}/\mathrm{s}$ ,活塞风的最大风速由 $2\mathrm{\;m}/\mathrm{s}$ 增大到 ${30}\mathrm{\;m}/\mathrm{s}$ ,达到风速峰值的时间由 ${220}\mathrm{\;s}$ 减少到 15 s。
隧道活塞风通风换气次数常被用来定量比较车速对活塞风通风效果的影响。列车速度越快, 活塞效应越强, 因此隧道内的空气更新越快, 即换气次数越大。 图10拟合了列车车速 ${v}_{1}$ 与隧道通风换气次数 ${\eta }^{\prime }$ 之间的对数变化关系。根据该拟合公式, 换气次数增大, 速率会随着车速的增加而逐渐变缓。相比于 $5\mathrm{\;m}/\mathrm{s}$ 的车速, ${30}\mathrm{\;m}/\mathrm{s}$ 的车速对应的通风换气次数增大了 ${52.59}\%$ ;而车速从 ${30}\mathrm{\;m}/\mathrm{s}$ 增长到 ${100}\mathrm{\;m}/\mathrm{s}$ 时,换气次数仅增长 21.22%。
不同列车长度下的非稳态活塞风变化特性如图11所示。可以看出, 列车长度的变化会改变活塞风速度的峰值, 而不会影响其持续时间。活塞风风速随时间的增大呈现先增大后减小的趋势, 且风速最大值的出现时刻基本相同。随着车长从 ${20}\mathrm{\;m}$ 增加到 ${180}\mathrm{\;m}$ ,活塞风最大风速从 $4\mathrm{\;m}/\mathrm{s}$ 增加到 ${10.5}\mathrm{\;m}/\mathrm{s}$ ,增加了 ${162.5}\%$ 。这是因为列车长度的增加意味着列车在隧道内占据了更大的空间, 使得被推移的空气体积更大, 从而形成更大的压力差, 并导致活塞风速度的峰值增加。而活塞风的持续时间主要由列车通过隧道的时间决定, 这个时间取决于列车的速度,而非长度。
图12拟合了列车车长 ${l}_{1}$ 与隧道通风换气次数 ${\eta }^{\prime }$ 的指数变化关系。该拟合公式虽然与列车车速的拟合公式有所不同,但是其变化趋势却是相似的。相比于 ${20}\mathrm{\;m}$ 的车长, ${200}\mathrm{\;m}$ 的车长对应的通风换气次数增大了 77.8%。
由于阻塞比的定义是列车与隧道的横截面之比, 通常列车型号在同一条隧道中不变, 而隧道的截面会根据地理位置等影响产生变化。因此, 本研究将改变隧道的截面积来分析阻塞比对隧道活塞风的影响。
图13拟合了阻塞比 $\alpha$ 与隧道通风换气次数 ${\eta }^{\prime }$ 的四阶多项式变化曲线, 可以看出活塞风通风换气次数是随着阻塞比的增大而呈现先小后大的变化趋势。最小的通风换气次数为 0.68 次/列车,其出现在阻塞比为 0.59 的情况下。这主要是由于当阻塞比较小时, 活塞效应不明显, 形成的活塞风速大小几乎不变, 但是阻塞比越小, 隧道阻力越小, 活塞风衰减越慢, 因此通风量相对越大, 换气次数越高。而当阻塞比增加至 0.59 后, 由于隧道横截面积缩小, 隧道体积减小, 加之活塞风速度的提高, 使得换气次数也逐渐提高。
不同隧道长度下的非稳态活塞风变化特性如图14所示。可以看出, 隧道长度会同时改变活塞风的风速峰值和持续时间。随着隧道长度的增加, 活塞风的风速峰值减小。其原因为隧道长度增加意味着沿程摩擦阻力增大, 从而导致活塞风速度减小, 而持续时间会随着列车运行时间的增加而增大。
图15拟合了隧道长度 $L$ 与隧道通风换气次数 ${\eta }^{\prime }$ 之间的指数变化关系。当隧道长度增加时, 不仅活塞风速度降低, 而且隧道体积相应增大, 因此隧道的通风换气次数会降低。即隧道越长, 通风效果越差。由计算结果可知,相比于 ${500}\mathrm{\;m}$ 长的隧道, ${6000}\mathrm{\;m}$ 隧道的通风换气次数降低了近 84%。
为了更高效地利用地铁隧道活塞风特性, 并为工程实践做出理论上的指导, 采用灰关联度分析(grey relational analysis)对列车速度、列车长度、隧道长度、 列车-隧道阻塞比的计算值进行初值化处理并找出 4 个因素与活塞风通风换气次数之间的作用关系。
表3为计算值的初值化处理结果, 其中活塞风通风换气次数为母函数,记作 $\left\{ {{x}_{0}\left( n\right) }\right\}$ ; 列车速度、列车长度、列车-隧道阻塞比、隧道长度分别作为标志函数, 记作 $\left\{ {{x}_{i}\left( n\right) }\right\}$
通过式(11) $\sim$ 式(14)求出关联系数:
$ {\Delta }_{0i}\left( n\right) = \left| {{x}_{0}\left( n\right) - {x}_{i}\left( n\right) }\right| $
$ {\Delta }_{\max } = \mathop{\max }\limits_{i} \cdot \mathop{\max }\limits_{n}\left| {{x}_{0}\left( n\right) - {x}_{i}\left( n\right) }\right| $
$ {\Delta }_{\min } = \mathop{\min }\limits_{i} \cdot \mathop{\min }\limits_{n}\left| {{x}_{0}\left( n\right) - {x}_{i}\left( n\right) }\right| $
$ {\xi }_{0i}\left( n\right) = \frac{{0.5}{\Delta }_{\max }}{{\Delta }_{0i}\left( n\right) + {0.5}{\Delta }_{\max }} $
最后,根据式(15)计算关联度,得出各因素的关联度见表4
$ {r}_{0i} = \frac{1}{n}\left\lbrack {{\xi }_{0i}\left( 1\right) + {\xi }_{0i}\left( 2\right) + \cdots + {\xi }_{0i}\left( n\right) }\right\rbrack $
表4中各因素关联度计算值的大小可以看出, 阻塞比是影响隧道活塞通风效果的最大因素, 列车长度和列车速度次之, 而隧道长度最小。这是因为阻塞比被定义为列车截面积与隧道截面积的比值, 当阻塞比增大时, 列车与隧道之间的空气流动路径被压缩, 压力梯度急剧增大, 从而显著增强活塞效应。同时, 阻塞比越大, 列车与隧道之间的间隙越小, 空气流动受到的阻力越大, 活塞风速也越大, 从而增强隧道内的通风效果。相比之下,虽然列车速度的增加可以提高活塞风速, 但这种影响是线性的, 且无法在短时间内显著改变气流特性; 列车长度对活塞风的影响则主要体现在列车与隧道之间的相互作用长度上, 较长的列车可能会导致较大的压力差和较强的空气流动, 但与阻塞比相比影响较小;隧道长度对隧道通风效果的影响体现为压力损失, 其对压力梯度的影响为积累值, 变化相对较慢。据此提出一个包含列车速度、列车长度、 隧道长度、列车-隧道阻塞比 4 项因素的拟合公式, 即
$ {\eta }^{\prime } = A + B \cdot \ln \left( {v}_{1}\right) + C \cdot {l}_{1}^{0.2483} + D \cdot {L}^{-{0.733}} $
$ + E \cdot \left( {{\alpha }^{4} - {2.0255}{\alpha }^{3} + {1.6073}{\alpha }^{2} - {0.6038\alpha }}\right) $
表4中计算值代入式(16), 联立求得公式中各项常数的实际值(见表5)。经过分析模型值与实测值的对比结果, 发现二者的皮尔逊相关性系数高于 0.95 , 平均误差低于 13%,验证了理论模型的相关性和准确性。
目前国内地铁列车运行最高时速为 ${80} \sim {180}\mathrm{\;{km}}/\mathrm{h}$ ; 常见列车分为 4 辆、 6 辆和 8 辆编组,每辆车厢长 ${25}\mathrm{\;m}$ ; 区间隧道的长度一般在 $1 \sim 3\mathrm{\;{km}}$ 之间 [14] ; 隧道阻塞比一般为0.4~0.6[15] 。而式(16)是基于 $5 \sim {100}\mathrm{\;m}/\mathrm{s}$ 车速、 ${20} \sim {180}\mathrm{\;m}$ 列车长度、 ${0.1} \sim {0.9}$ 隧道阻塞比和 ${500} \sim$ ${6000}\mathrm{\;m}$ 隧道长度拟合而得,因此该拟合公式囊括了我国常见地铁隧道。
本文首先说明了 “活塞风” 的产生原因, 并以地铁隧道为研究对象, 建立了活塞风的理论建模, 在保证建立的模型与原型具有相同阻塞比, 且隧道断面流动特性尽可能还原的前提下, 对国内常见的地铁隧道断面形状进行了简化。其次针对地铁隧道活塞风模型进行验证分析, 评估其在不同参数配置下包括列车车速、列车长度、隧道长度和隧道阻塞比的准确性, 最后给出预测公式用来估计绝大多数地铁隧道活塞风的通风效果。可以得到以下结论:
1)本文中建立的隧道活塞风理论模型的针对通风换气次数的计算结果与实验测试数据展现出高度相关性, 皮尔逊相关系数达到 0.98 以上, 二者间的误差基本控制在 13%的范围内。因此, 可以认为理论预测模型具有较高的准确性和可靠性, 能够准确地反映隧道活塞风的非稳态特性。
2)通过对多种影响因素计算结果的灰关联分析得出:在影响隧道活塞风通风效果的诸多因素中,隧道阻塞比占据主导地位,其关联度显著高于其他因素, 其次为列车长度, 第三为列车车速, 而隧道长度的变化对于活塞风通风效果的关联度最低,影响最小。
3)给出一个可用于估计我国常见地铁隧道活塞风通风效果的预测公式。
  • 国家重点研发计划(2018V3-0119)
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2025年第38卷第3期
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doi: 10.3969/j.issn.1672-6073.2025.03.004
  • 接收时间:2024-07-09
  • 首发时间:2025-07-09
  • 出版时间:2025-06-01
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  • 收稿日期:2024-07-09
  • 修回日期:2024-10-11
基金
国家重点研发计划(2018V3-0119)
作者信息
    1 青岛地铁集团有限公司 青岛 266100
    2 天津大学 环境科学与工程学院 天津 300354
参考文献
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https://castjournals.cast.org.cn/joweb/dskgjt/CN/10.3969/j.issn.1672-6073.2025.03.004
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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