Article(id=1149742084602642873, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149742076708962589, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1672-6073.2024.05.016, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1704297600000, receivedDateStr=2024-01-04, revisedDate=1708963200000, revisedDateStr=2024-02-27, acceptedDate=null, acceptedDateStr=null, onlineDate=1752049474144, onlineDateStr=2025-07-09, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752049474144, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752049474144, creator=13701087609, updateTime=1752049474144, updator=13701087609, issue=Issue{id=1149742076708962589, tenantId=1146029695717560320, journalId=1146123302524792850, year='2024', volume='37', issue='5', pageStart='1', pageEnd='143', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1752049472262, creator=13701087609, updateTime=1753780124752, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1157000959420354689, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149742076708962589, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1157000959420354690, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1149742076708962589, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=107, endPage=115, ext={EN=ArticleExt(id=1149742084833329605, articleId=1149742084602642873, tenantId=1146029695717560320, journalId=1146123302524792850, language=EN, title=Microenvironment and Thermal Comfort of Subway Carriage Occupants Based on Amplitude-flow Fans, columnId=1152669334582243706, journalTitle=Urban Rapid Rail Transit, columnName=Electrical and Mechanical Engineering, runingTitle=null, highlight=null, articleAbstract=

Subway carriages are ventilated from the outside world through fans, which regulate the temperature, humidity, and wind speed of the internal environment of the carriages, improve air quality, and enhance the thermal comfort of passengers. Due to the limited number of applicable thermal comfort evaluation indices, accurately determining the thermal comfort of subway car occupants in transient environments is challenging. This paper first focuses on occupants of a Btype subway compartment as the research subject and proposes the joint application of DRBerkeley thermal comfort evaluation indexes by considering both airflow comfort and heat sensation. The study then employs the Stolwijk physiological model of human thermal regulation to construct a threedimensional model of the amplitudeflow fan and an overall simulation model of the subway compartment. Finally, using CFD software, STARCCM+, the study analyzes the effects of different fan speeds, fan hood disturbance speeds, and fan air supply temperatures on the microenvironment and thermal comfort of the occupants under seven different conditions during the summer. The results show that the DRBerkeley thermal comfort evaluation indexes can reasonably evaluate the thermal comfort of subway compartments under the premise of meeting the airflow comfort in summer; increasing the fan speed, reducing the hood disturbance speed, and reducing the fan air supply temperature can improve the thermal comfort of the occupants; in the seven working conditions, the fan speed of 1,400 rpm, the hood disturbance speed of 3.25 rpm, and the air supply temperature of 20°C have a uniform temperature and speed distribution in the compartments. The temperature and velocity distributions in the cabin were uniform, the occupant microenvironmental heat flow field was optimal, and thermal comfort was 0.766. This method can solve the occupant thermal comfort problem more comprehensively, which is of some reference significance for optimizing the thermal flow field environment in subway compartments and upgrading occupant thermal comfort.

, correspAuthors=Feng HE, 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=Zhixin GAO, Feng HE, Jing ZHAO, Lei DIAO), CN=ArticleExt(id=1149742097886004218, articleId=1149742084602642873, tenantId=1146029695717560320, journalId=1146123302524792850, language=CN, title=基于幅流风机的地铁车厢乘员微环境及热舒适性研究, columnId=1152669334955536763, journalTitle=都市快轨交通, columnName=机电工程, runingTitle=null, highlight=null, articleAbstract=

为优化地铁车厢内热流场环境,提升地铁车厢乘员的热舒适性,深入探究幅流风机不同性能参数对地铁车厢内气流分布和乘员热舒适性的影响机制。首先以某B型地铁车厢乘员为研究对象,综合考虑乘员气流舒适感和热感,提出联合应用 DRBerkeley 热舒适性评价指标;然后,使用 Stolwijk 人体热调节生理模型,搭建幅流风机三维模型和地铁车厢整体仿真模型;最后,通过CFD 软件 STARCCM+,使用DRBerkeley 热舒适性评价指标,以7种工况,分析夏季时不同风机转速、风罩扰动转速、风机送风温度对乘员部位微环境及热舒适性的影响。研究结果表明:DRBerkeley 热舒适评价指标能合理评估地铁车厢乘员的热舒适性;在夏季满足气流舒适性的前提下,增大风机转速、降低风罩扰动转速、降低风机送风温度能提升乘员热舒适性; 在7种工况中,风机转速 1400 rpm、风罩扰动转速3.25 rpm、送风温度20℃时的车厢内温度和速度分布均匀,乘员微环境热流场最佳,热舒适性较好,为0.766。

, correspAuthors=何锋, authorNote=null, correspAuthorsNote=
何锋,男,教授,从事新能源汽车和汽车服务规划与设计研究,
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高志鑫,男,硕士研究生,从事车辆流场及热舒适性方向研究,

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高志鑫,男,硕士研究生,从事车辆流场及热舒适性方向研究,

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高志鑫,男,硕士研究生,从事车辆流场及热舒适性方向研究,

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tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149742084602642873, language=CN, orderNo=5, keyword=DR-Berkeley)], refs=[Reference(id=1154000607301062680, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149742084602642873, doi=null, pmid=null, pmcid=null, year=2018, volume=21, issue=3, pageStart=98, pageEnd=101, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=宣守旺, 曹从咏, 周鹏, journalName=城市轨道交通研究, refType=null, unstructuredReference=宣守旺, 曹从咏, 周鹏. 基于计算流体动力学的地铁车厢气流性能评价分析[J]. 城市轨道交通研究, 2018, 21(3): 98-101., articleTitle=基于计算流体动力学的地铁车厢气流性能评价分析, refAbstract=null), Reference(id=1154000607368171545, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149742084602642873, doi=null, pmid=null, pmcid=null, year=2018, volume=21, issue=3, pageStart=98, pageEnd=101, url=null, language=null, rfNumber=[1], rfOrder=1, authorNames=XUAN Shouwang, CAO Congyong, ZHOU Peng, journalName=Urban mass transit, refType=null, 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数值 热感觉 热舒适 数值 热感觉 热舒适
-4 寒冷 很不舒服 1 微暖 -
-3 - 2 舒服
-2 不舒服 3 -
-1 微凉 - 4 炎热 很舒服
0 自然 自然 - - -
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数值 热感觉 热舒适 数值 热感觉 热舒适
-4 寒冷 很不舒服 1 微暖 -
-3 - 2 舒服
-2 不舒服 3 -
-1 微凉 - 4 炎热 很舒服
0 自然 自然 - - -
), ArticleFig(id=1154000606873243659, tenantId=1146029695717560320, journalId=1146123302524792850, articleId=1149742084602642873, language=EN, label=Table 2, caption=Analysis condition of flow field in carriage, figureFileSmall=null, figureFileBig=null, tableContent=
工况 风机转速/rpm 扰动转速/rpm 送风温度1℃
1 1 400 3.75 20
2 1 600 3.75 20
3 1 800 3.75 20
4 1 400 3.20 20
5 1400 4.30 20
6 1400 3.75 16
7 1 400 3.75 24
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工况 风机转速/rpm 扰动转速/rpm 送风温度1℃
1 1 400 3.75 20
2 1 600 3.75 20
3 1 800 3.75 20
4 1 400 3.20 20
5 1400 4.30 20
6 1400 3.75 16
7 1 400 3.75 24
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基于幅流风机的地铁车厢乘员微环境及热舒适性研究
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高志鑫 1 , 何锋 1 , 赵京 2 , 刁雷 1
都市快轨交通 | 机电工程 2024,37(5): 107-115
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都市快轨交通 | 机电工程 2024, 37(5): 107-115
基于幅流风机的地铁车厢乘员微环境及热舒适性研究
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高志鑫1 , 何锋1 , 赵京2, 刁雷1
作者信息
  • 1 贵州大学 机械工程学院 贵阳 550025
  • 2 贵州航航科技有限公司 贵阳 550025
  • 高志鑫,男,硕士研究生,从事车辆流场及热舒适性方向研究,

通讯作者:

何锋,男,教授,从事新能源汽车和汽车服务规划与设计研究,
Microenvironment and Thermal Comfort of Subway Carriage Occupants Based on Amplitude-flow Fans
Zhixin GAO1 , Feng HE1 , Jing ZHAO2, Lei DIAO1
Affiliations
  • 1 School of Mechanical Engineering Guizhou University Guiyang 550025
  • 2 Guizhou Hanghang Technology Co., Ltd. Guiyang 550025
doi: 10.3969/j.issn.1672-6073.2024.05.016
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为优化地铁车厢内热流场环境,提升地铁车厢乘员的热舒适性,深入探究幅流风机不同性能参数对地铁车厢内气流分布和乘员热舒适性的影响机制。首先以某B型地铁车厢乘员为研究对象,综合考虑乘员气流舒适感和热感,提出联合应用 DRBerkeley 热舒适性评价指标;然后,使用 Stolwijk 人体热调节生理模型,搭建幅流风机三维模型和地铁车厢整体仿真模型;最后,通过CFD 软件 STARCCM+,使用DRBerkeley 热舒适性评价指标,以7种工况,分析夏季时不同风机转速、风罩扰动转速、风机送风温度对乘员部位微环境及热舒适性的影响。研究结果表明:DRBerkeley 热舒适评价指标能合理评估地铁车厢乘员的热舒适性;在夏季满足气流舒适性的前提下,增大风机转速、降低风罩扰动转速、降低风机送风温度能提升乘员热舒适性; 在7种工况中,风机转速 1400 rpm、风罩扰动转速3.25 rpm、送风温度20℃时的车厢内温度和速度分布均匀,乘员微环境热流场最佳,热舒适性较好,为0.766。

城市轨道交通  /  地铁车厢  /  幅流风机  /  热舒适性  /  DR-Berkeley

Subway carriages are ventilated from the outside world through fans, which regulate the temperature, humidity, and wind speed of the internal environment of the carriages, improve air quality, and enhance the thermal comfort of passengers. Due to the limited number of applicable thermal comfort evaluation indices, accurately determining the thermal comfort of subway car occupants in transient environments is challenging. This paper first focuses on occupants of a Btype subway compartment as the research subject and proposes the joint application of DRBerkeley thermal comfort evaluation indexes by considering both airflow comfort and heat sensation. The study then employs the Stolwijk physiological model of human thermal regulation to construct a threedimensional model of the amplitudeflow fan and an overall simulation model of the subway compartment. Finally, using CFD software, STARCCM+, the study analyzes the effects of different fan speeds, fan hood disturbance speeds, and fan air supply temperatures on the microenvironment and thermal comfort of the occupants under seven different conditions during the summer. The results show that the DRBerkeley thermal comfort evaluation indexes can reasonably evaluate the thermal comfort of subway compartments under the premise of meeting the airflow comfort in summer; increasing the fan speed, reducing the hood disturbance speed, and reducing the fan air supply temperature can improve the thermal comfort of the occupants; in the seven working conditions, the fan speed of 1,400 rpm, the hood disturbance speed of 3.25 rpm, and the air supply temperature of 20°C have a uniform temperature and speed distribution in the compartments. The temperature and velocity distributions in the cabin were uniform, the occupant microenvironmental heat flow field was optimal, and thermal comfort was 0.766. This method can solve the occupant thermal comfort problem more comprehensively, which is of some reference significance for optimizing the thermal flow field environment in subway compartments and upgrading occupant thermal comfort.

urban rail transit  /  subway carriage  /  amplitude-flow fan  /  thermal comfort  /  DR-Berkeley
高志鑫, 何锋, 赵京, 刁雷. 基于幅流风机的地铁车厢乘员微环境及热舒适性研究. 都市快轨交通, 2024 , 37 (5) : 107 -115 . DOI: 10.3969/j.issn.1672-6073.2024.05.016
Zhixin GAO, Feng HE, Jing ZHAO, Lei DIAO. Microenvironment and Thermal Comfort of Subway Carriage Occupants Based on Amplitude-flow Fans[J]. Urban Rapid Rail Transit, 2024 , 37 (5) : 107 -115 . DOI: 10.3969/j.issn.1672-6073.2024.05.016
在密闭的地铁车厢内, 空气质量和热量积累直接影响乘员的舒适性, 且可能增加流行性呼吸道传染病的传播风险。为了改善地铁车厢内的空气质量和乘员的热舒适性, 可以通过空调通风系统中的幅流风机将空气送风、回风和废排风进行有序组织, 形成合理的气流组织, 实现车厢与外界的通风, 有效改善室内环境的温湿度、清洁度和空气质量,进而提升乘员的舒适性。
在地铁车厢乘员热舒适性方面, 许多学者进行了相关研究。宣守旺等 [ 1 ] 研究了不同工况对地铁车厢内温度、速度、气流性能的影响, 并得出最优工况, 但并未充分分析乘员热舒适性; 瞿珏等 [ 2 ] 研究指出,以固定人体热边界条件作为输入仿真模拟, 通过气流组织参数以及固定人体温度进行热舒适评价的结果并不精确, 李伟健等 [ 3 ]通过实验研究人体执咸觉与生理执调节的关系, 为建立更精确的人体模型提供了一定的指导;陈吉清等 [ 4 ] 通过将人体热调节模型与乘员舱热环境耦合, 研究了暖风对乘员热反应及舒适性的影响, 并得出了相应的变化规律; 刘海军等 [ 5 ] 建立了多节点人体热调节模型,采用预测平均投票数-预计不满意者的百分数评价指标(predicted mean vote-predicted percentage of dissatisfied, PMV-PPD), 分析了地铁车厢乘员的热舒适性; 赵楠 [ 6 ] 通过模拟分析加载幅流风机前后及风机不同送风温度的地铁车厢内流场, 发现加载幅流风机可改善气流组织,提高乘员舒适性;陈阳等 [ 7 ] 通过分析地铁车厢同车不同温度的空调设定模式, 得出最低不满意率的方案; 黄木生 [ 8 ] 提出自适应舒适标准-气流不舒适度准则(adaptive comfort standard-dissatisfied of draft, ACS-DR), 适用非均匀瞬态温度场, 且能够考虑空气流动带来的不舒适感; Zhang 等 [ 9 ] 进行 109 次非均匀和瞬态人体实验, 建立了 Berkeley 热舒适评价模型, 更全面地反映了热舒适性; 杨志刚等 [ 10 ] 采用 Berkeley 热舒适评价模型,通过分析不同工况对夏季汽车驾驶员热舒适影响, 得到各影响因素对人体热感觉和热舒适的影响程度。然而, 目前该模型在地铁车厢热舒适性研究中应用较少, 且对进行热量交换的人体皮肤微环境的关注也相对较低。
本文以某地铁 2 号线 $\mathrm{B}$ 型车厢为研究对象,通过 STAR-CCM+软件, 使用 Stolwijk 人体热调节生理模型, 运用 DR-Berkeley 热舒适评价模型, 模拟分析了幅流风机不同工况对地铁车厢乘员的热感觉与热舒适性,修正了已有文献 [ 10 - 11 ] 对整体热舒适评价的选取规则。同时关注人体部位微环境参数, 得出较优的工况, 为优化地铁车厢内部热环境提供合理可行的参考。
Berkeley 反映热舒适性, 气流不舒适度(dissatisfied of draft, DR)反映气流不舒适感, 车厢内乘员对气流变化较敏感,将车厢气流组织满意度量化为热舒适程度的指标之一, 形成 DR-Berkeley 热舒适性评价指标。 DR 的函数表达式为
$\mathrm{{DR}}= \left({{34}- {t}_{\mathrm{a}}}\right){\left( V -{0.05}\right)}^{0.62}\left({{0.37V}{T}_{\mathrm{u}}+ {3.14}}\right)$
式中, ${t}_{\mathrm{a}}$ 为乘员部位的温度, ${}^{\circ }\mathrm{C};V$ 为监测点的气流速度, $\mathrm{m}/\mathrm{s}$${T}_{\mathrm{u}}$ 为局部湍流强度, $\%$ ,因车厢内流速较低,湍流强度 ${T}_{\mathrm{u}}$$5\%$ 。在 ASHRAE Standard 55 中规定, DR<20%才能符合大多数乘员对气流的满意度。
Berkeley 局部热感觉回归式为
${S}_{1}= 8{\left\{ 1 +{e}^{-{c}_{1}\left({{T}_{\mathrm{{sl}}}- {T}_{\mathrm{{sls}}}}\right)- {K}_{1}\left\lbrack {\left({{T}_{\mathrm{{sl}}}- {T}_{\mathrm{{sa}}}}\right)- \left({{T}_{\mathrm{{sls}}}- {T}_{\mathrm{{sas}}}}\right)}\right\rbrack }\right\}}^{-1}+ \\{C}_{2i}\frac{\mathrm{d}{T}_{\mathrm{{sl}}}}{\mathrm{d}t}+ {C}_{3i}\frac{\mathrm{d}{T}_{\mathrm{c}}}{\mathrm{d}t}- 4 $
式中, ${T}_{\mathrm{{sl}}}$ 为人体局部表面温度, $\mathrm{C};{S}_{1}$ 为局部热感觉; ${T}_{\mathrm{{sls}}}$ 为热舒适管理模块(thermal comfort management, TCM)的人体局部表面温度; ${T}_{\text{sas }}$ 为 TCM 设定的平均温度; ${T}_{\mathrm{{sa}}}$ 为平均皮肤温度; ${T}_{\mathrm{c}}$ 为核心温度; ${C}_{1}\text{、}{K}_{1}$${C}_{2i}$${C}_{3i}$ 为常数回归系数; $t$ 为时间, $\mathrm{s}$
局部热舒适指标回归式为
${C}_{\mathrm{L}}= \left\lbrack \begin{array}{l}\frac{-4 -\left({{C}_{6}+ {C}_{7}\left|{S}_{0}\right|}\right)}{{\left|\left(-4 +{C}_{3}\left|{S}_{0}\right|\right)+ {C}_{8}\right|}^{n}}- \frac{-4 -\left({{C}_{6}+ {C}_{7}\left|{S}_{0}\right|}\right)}{{\left|\left( 4 +{C}_{3}\left|{S}_{0}\right|\right)+ {C}_{8}\right|}^{n}}\\\frac{{e}^{{15}\left({{S}_{1}+ {C}_{3}\left|{S}_{0}\right|+ {C}_{8}}\right)} + 1}{{\left|\left( 4 +{C}_{1}\left|{S}_{0}\right|\right)+ {C}_{8}\right|}^{n}}\end{array}\right\rbrack \times $
${\left({S}_{1}+ {C}_{3}\left|{S}_{0}\right|+ {C}_{8}\right)}^{n}+ {C}_{6}+ {C}_{7}\left|{S}_{0}\right|$
式中, ${C}_{\mathrm{L}}$ 表示局部热舒适性; ${S}_{0}$ 为整体热感觉绝对值; ${C}_{3}$${C}_{6}$${C}_{7}$${C}_{8}$$\mathrm{n}$ 均为常数回归系数,其中整体热感觉正负不同时, ${C}_{3}$${C}_{7}$ 数值不相同。
整体热感觉回归式为
${S}_{0}= \frac{\sum {W}_{i}{S}_{1}}{\sum {W}_{i}}$
式中, ${W}_{i}$ 为各部位影响权重。
整体热舒适的计算参照以下规则:①整体热舒适为最小 2 个局部热舒适平均值; ②对热环境有一定控制或为瞬态时, 整体热舒适为最小 2 个局部热舒适与最大热舒适的平均值。若双手或双脚构成最不舒服的 2 个身体部位, 则忽略第 2 低的手或脚舒适度值, 并使用第 3 低的局部舒适值作为规则中的第 2 低舒适度值。 热感觉与热舒适指标对应人体热感觉状态如 表 1 所示。
以某地铁 2 号线 $\mathrm{B}$ 型车厢为参考,建立车厢物理模型。车厢在车长方向上对称,建立 $1/2$ 车厢三维模型,如 图 1 所示。 $1/2$ 车厢模型长 $9\mathrm{\;m}$ ,宽 ${2.8}\mathrm{\;m}$ ,地板到顶板的高度为 ${2.1}\mathrm{\;m}$ 。设 2 个进风口在地铁顶部两侧, 设 1 个回风口在地铁中间顶部, 设 2 个废排风口在地铁底部两侧缝隙及 2 个在顶部末端, 采取上送风、 上回风、上下排风形式。车厢乘员由 stolwijk 的热调节生理模型构建 [ 12 ] ,人体被划分为 14 个不同部分: 躯干,头部,左、右上臂,左、右下臂,左、右手,左、 右大腿,左、右小腿,左、右脚,每个部分进一步细分为核心层、皮肤层、肌肉层和脂肪层, 以便更精确地模拟和分析热调节模型。车厢乘员 12 人皆是坐态, 平均身高为 ${1.70}\mathrm{\;m}$ ,体重为 ${70}\mathrm{\;{kg}}$ , 图 1 中, ${d1}\sim {d6}$ 表示乘员 1~乘员 6。
幅流风机作为仿真模拟的重要部件, 其风罩由集风板及挡风板组成, 在风罩电机的固有频率下, 风罩呈周期性摆动。风机在叶轮转动和风罩扰动下形成动态气流往车厢送风。其中,叶轮长 ${0.8}\mathrm{\;m}$ ,宽 ${0.175}\mathrm{\;m}$ , 高 ${0.138}\mathrm{\;m}$ 。幅流风机实物如 图 2 所示,简化模型如 图 3 所示。
使用 STRA-CCM+软件, 对几何形体进行精细的清理与表面修复, 以构建优质的三角形面网格。在叶轮、人体表面、风罩等部位引入棱柱层并局部细化网格单元, 在风机出口栏栅与地铁车厢交界处, 选用 interface 连接并进行 15%的细致加密。网格生成策略上, 选取多面体网格生成器, 以优化计算资源配置, 核心网格优化循环设定为 5 次迭代, 并将网格质量的阈值设定为 0.5 , 使仿真模拟热流场分布更加精确, 以保证分析结果的准确有效性。地铁车厢整体单元网格数量为 3428286 , 网格节点数量为 13952307 , 地铁车厢整体网格划分模型如 图 4 所示。
求解器设置为隐式非稳态, 湍流模型为 Realizable $\mathrm{k}- \varepsilon$ ,时间为二阶离散格式,最大步数为 1000 步,时间步长为 0.016 s。风机叶轮与气流相互作用,选择刚体运动、分离流模型。车厢对称面设置为对称边界, 无太阳辐射, TCM 边界设置相对湿度为 40%, 外部环境温度 ${36.5}^{\circ }\mathrm{C}$ ,车速设置为 ${80}\mathrm{\;{km}}/\mathrm{h}$ ,送风温度为 ${20}^{\circ }\mathrm{C}$ 。 壁面边界为热对流, 车窗、车门、车身热传递系数分别为 ${3.1}\text{、}{4.6}\text{、}{2.5}\mathrm{\;w}/\left({{\mathrm{m}}^{2}\cdot \mathrm{k}}\right)$ 。废排风口设置为压力出口, 回风口设置为质量流量入口, 幅流风机转速为 ${1400}\mathrm{{rpm}}$ ,扰动场函数与风罩电机扰动转速关系为
$\omega =\frac{{19}{\pi }^{2}{n}_{\mathrm{r}}\times \cos \left(\frac{{n}_{\mathrm{r}}{\pi t}}{30}\right)}{2700}$
式中, $\omega$ 为叶轮转速; ${n}_{\mathrm{r}}$ 为风罩电机扰动转速。
地铁车厢热流场受到风机送风及外界热环境影响, 乘员身体部位与周围热环境的热交换直接影响人体热舒适性。车厢两侧乘员对称, 所受气流组织及热交换相同,为降低计算复杂度, 选取 6 位乘员进行微环境及热舒适研究分析。如 图 5 所示, 在人体热调节模型的 14 个节段分别设定距离人体表面皮肤 $1\mathrm{\;{mm}}$ 的部位作为监测点, 用以表示乘员微环境热流场与人体部位进行热交换。文献[ 11 ]已经采用实验验证了仿真模拟的可行性, 本研究不再赘述。
采用 表 2 所示的 7 个工况分析风机转速、扰动场函数、送风温度 3 个因素对车厢乘员微环境及人体热舒适的影响。
通过仿真得到不同风机转速下乘员各部位监测点的温度值和风速值,如 图 6 所示,工况 1 、工况 2 、工况 3 车厢速度场与温度场均受风机转速的影响, 乘员各身体部位微环境监测点平均风速随风机转速增大而增大,温度随转速增大而减小。
头部和手部监测点所受风速及温度变化幅度较大, 这是由于头部距离进风口及风机较近, 手部受到风机直吹。小腿及脚部位温度值变化幅度较小, 这是由于风机在顶部往下排风,风机产生的风速随着气流在车厢内扩散衰减, 且小腿部位并未受到风机直吹, 风速变化趋势不大,温度值变化幅度也较小。
气流组织不舒适性主要受各部位微环境风速及温度影响。计算不同转速下乘员各部位 DR 值,如 图 7 所示。由 图 7 可知, 随着风机转速的增大, 乘员大部分部位 DR 值也随着增大。其中,头部、左右手受到风机口气流直吹,这些部位的风速值较大,并随着风机转速增大呈上升趋势;而左小臂、左大腿等部位受到幅流风机风罩的扰动影响, 周围微环境气流紊乱交错, 脚部处于侧缝废排风口, 排风带动气流, 故这些部位的 DR 值较高。工况 1 和 2 的 DR 值均小于 20%, 即车厢气流组织达到大多数乘员的满意度, 而工况 3 中各部位 DR 值均最高,其中右手部位 DR 值更是达到 20.59%,气流组织呈现不舒适性。
通过仿真得到乘员部位核心层温度, 皮肤表面温度, 通过 Berkeley 热舒适性评价指标公式, 计算不同转速下乘员局部和整体的热感觉及热舒适值, 如 图 8 所示。由 图 8 (a) $\sim$ (c)可知,将工况 1、工况 2、工况 3 的人体热感觉与热舒适进行对比,躯干、上臂、左小臂及脚部位热感觉为负值, 其余部位都为正值, 这是由于风机气流主要吹向上肢部位, 脚部受到底部侧缝废排风口带动气流, 故这些部位热感觉为偏冷状态。
随着风机转速增大, 乘员身体各部位热感觉呈降低变冷的趋势。大部分部位随着热感觉降低, 其局部热舒适性得到了改善,仅有躯干和脚部位热感觉降低, 热舒适性变差。其中, 工况 3 左小臂热舒适值最高, 其热感觉为-0.303,热舒适值为 3.340 ; 工况 1 右小腿热舒适值最低,其热感觉为 2.160 ,热舒适值为 -1.160 ; 随着风机转速增大, 右脚部位局部热感觉从-0.668 降低到 -0.688 ,其热舒适性从 1.610 降低到 1.590 ,躯干局部热感觉从-1.630 降低到-1.680, 其热舒适性从 0.788 降低到 0.730 。说明在炎热的夏季时,人体大部分部位喜好偏冷环境, 而躯干和脚部更喜好温暖环境。由于地铁车厢热环境为瞬态流场, 乘员整体热舒适值根据 1.1 节的规则②进行计算。如 图 8(d) 可知, 随着风机转速的增大, 整体热感觉降低, 从 0.657 变到 0.631 , 而整体热舒适从 0.585 上升到 0.656 ,皆处于较舒服状态。
综上, 随着风机转速增大, 乘员整体热感觉降低, 整体热舒适上升,而当风机转速为 ${1800}\mathrm{{rpm}}$ 时,气流组织呈不舒适性, 故过高风机转速不可取。
在研究舒适气流的组织时, 机械风和自然风因其频谱特性的差异而引起不同感受。通过调整风罩扰动转速, 进而影响风机扰动场函数, 使机械风的频谱特性接近自然风,提升乘员气流舒适感和热舒适性。
通过仿真计算得到不同风罩扰动转速下乘员各部位监测点的风速值和 DR 值,如 图 9 所示。由 图 9(a) 可知, 随着扰动转速增大, 乘员不同部位风速变化较为紊乱,其中在工况 5 时乘员部位风速值跳跃最大, 左手微环境风速达到最高的 ${0.627}\mathrm{\;m}/\mathrm{s}$ ,而右小臂及右大腿微环境风速达到最低的 0.0521 m/s 和 0.0543 m/s。 由 图 9(b) 可知, 气流不舒适性指标与不同扰动转速下乘员风速值变化趋势一致, 工况 1 与工况 4 气流舒适性在不同部位表现不同,但整体气流舒适性差异不大, 而工况 5 气流舒适性最差。在头部、左右手及左大腿等部位气流不舒适性较差,其中最差的左手 $\mathrm{{DR}}$ 值在工况 5 时达到了 19.871%,接近舒适性不满意的状态; 而躯干、左、右上臂、右小臂、右大腿、左、右小腿等部位气流舒适性较好, 其中右小臂和右大腿气流不舒适性为 0.454%和 0.635%,气流舒适性最佳。可见, 较高的扰动转速使得气流较不均匀, 各部位气流不舒适性差异较大, 影响乘员整体气流舒适性。
计算不同扰动转速下乘员局部和整体的热感觉及热舒适性,如 图 10 所示。由 图 10(a)图 10(b) 可知, 小臂部位和大腿部位热感觉降低,左小臂热感觉从 -0.252 降低到-0.288 ,热舒适值从 3.260 上升到 3.300 ; 右大腿热感觉从 0.830 降低到 0.751 ,热舒适值从 0.739 上升到 0.857 。其他部位局部热感觉随扰动转速增大而上升, 变化幅度较大的头部局部热感觉从 1.460 上升到 1.920, 其热舒适从 0.0069 降低到 -0.581; 右小腿局部热感觉从 2.010 上升到 2.230, 其热舒适从 -0.943 降低到-1.260; 变化幅度最小的右脚局部热感觉从-0.767 上升到 -0.618 , 热舒适从 1.520 上升到 1.650 ; 躯干局部热感觉从 -1.680 上升到 1.600 ,热舒适从 0.726 上升到 0.820 , 随着扰动转速增大, 人体各部位热感觉并未均匀变化。
综上, 扰动转速增大, 扰动场函数使气流组织变化, 小臂及大腿部位局部热感觉降低, 其他部位热感觉上升。
图 10(c) 可知,随着扰动转速的增大,整体热感觉增大, 而整体热舒适呈下降趋势, 工况 4 时整体热舒适最佳为 0.766 ,而工况 5 热舒适相对工况 4 降低了 0.279。这是由于不同的扰动场函数使得车厢空间内气流变化, 影响不同部位气流舒适性及热舒适性, 最终影响乘员整体热舒适性。可见, 风罩扰动转速较低时, 乘员热舒适性更好。
随着送风温度的变化, 车厢乘员人体各部位微环境的风速受到的影响很小, 乘员受到的温度值影响较大。对比分析不同送风温度下乘员各部位的温度值和 DR 值,如 图 11 所示。由 图 11(a) 可知,人体各部位温度随着送风温度的增大而升高, 尤其人体上半部分距离送风口更近, 温度值升幅最为明显, 其中右上臂监测点的温度值达到最高的 ${31.835}^{\circ }\mathrm{C}$ 。由 图 11(b) 可知, 在各部位微环境风速值基本相同的情况下, 气流不舒适性随着送风温度增大而降低。在工况 7 时气流舒适性最佳,左手 DR 值最高为 12.64%,大部分 DR 值小于 10%;而工况 6 时人体气流不舒适性最差,其中头部 DR 值达到了 18.69%,左大腿 DR 值为 17.94%, 左、右手 DR 值更是高达 19.83%、21.01%,为大部分乘员不满意的气流组织。可见不同送风温度下,人体气流舒适性主要受微环境温度的影响。
不同送风温度下乘员局部和整体的热感觉及热舒适值对比如 图 12 所示。由 图 12(a)图 12(b) 可知, 人体部位局部热感觉随着送风温度增大而上升, 头部、 上臂、小臂、手、大腿及小腿部位随着局部热感觉上升, 其局部舒适性降低。其中变化较明显的头部热感觉从 1.76 上升到 2.01, 热舒适从 -0.278 下降到 -0.778 ; 左小臂局部热感觉从-0.677 上升到 0.220, 热舒适从 3.930 下降到 2.440 , 从非常舒服变为舒服; 右小腿局部热感觉从 1.940 上升到 2.330, 热舒适从 -0.824 下降到 -1.420 ,从有点不舒服变为不舒服。这说明夏季人体大部分部位更喜欢偏冷的热环境。而躯干与脚部位随着局部热感觉的上升,其局部热舒适性得到提升。 躯干局部热感觉从-1.860 上升到-1.480, 其热舒适从 0.499 提升到 0.951 ;左脚局部热感觉从-0.978 上升到 -0.766, 热舒适从 1.320 提升到 1.640 ;右脚热感觉从 -0.987 上升到 -0.517 , 热舒适从 1.320 提升到 1.770 。 这说明人体躯干和脚部更喜欢温暖的热环境。
图 12(c) 可知,随着送风温度的增大,整体热感觉从 0.437 上升到 0.885 ,而整体热舒适从 0.910 降低到 0.0916。工况 6 整体热舒适最佳为 0.910 ,但其微环境气流呈不舒适状态, 故过低送风温度不可取。总体来看, 夏季外环境偏热, 在能够保证气流舒适性的情况下, 人们更喜欢较低的送风温度, 热感觉降低, 热舒适得到改善。
1) 送风温度为 ${16}^{\circ }\mathrm{C}$ 时,其整体热舒适值为最高的 0.910 , 人体呈现良好的热舒适性, 但其右手微环境监测点的 DR 值达到 21.01%,人体受到的吹风感不舒适,判断该工况下乘员感觉到不舒适。DR-Berkeley 热舒适评价指标综合考虑了人体热感觉、热舒适及微环境气流舒适性, 用于评估地铁车厢乘员人体热舒适性是合理的。
2) 在整体热感觉偏热的夏季时, 乘员更喜好较高的风机转速、较低的扰动场函数、较低的送风温度。 随着风机转速的增大, 整体热感觉降低, 从 0.657 降至 0.631 , 整体热舒适提升, 从 0.585 上升到 0.656 ; 随着扰动转速的增大, 整体热感觉从 0.586 上升到 0.692 , 而整体热舒适从 0.766 降低到 0.487 ; 随着送风温度的增大, 整体热感觉从 0.437 上升到 0.885 , 而整体热舒适从 0.910 降低到 0.0916。
3) 人体大部分部位喜好偏冷环境, 而躯干和脚部更喜好温暖环境。研究发现, 躯干和脚部热舒适值随着局部热感觉增大而上升, 其他部位热舒适值随着局部热感觉增大而降低。
4) 在 7 种工况中,风机转速为 ${1400}\mathrm{{rpm}}$ 、扰动转速为 ${3.20}\mathrm{{rpm}}$ 、送风温度为 ${20}^{\circ }\mathrm{C}$ 时车厢内乘员微环境气流舒适性最佳,热舒适性较好为 0.766 。
  • 贵州省科技计划项目(黔科合支撑[2022]一般251)
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2024年第37卷第5期
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doi: 10.3969/j.issn.1672-6073.2024.05.016
  • 接收时间:2024-01-04
  • 首发时间:2025-07-09
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  • 收稿日期:2024-01-04
  • 修回日期:2024-02-27
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贵州省科技计划项目(黔科合支撑[2022]一般251)
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    1 贵州大学 机械工程学院 贵阳 550025
    2 贵州航航科技有限公司 贵阳 550025

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何锋,男,教授,从事新能源汽车和汽车服务规划与设计研究,
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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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