Article(id=1308453939326776139, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308453915104665783, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1672-6073.2026.02.016, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1745683200000, receivedDateStr=2025-04-27, revisedDate=1767628800000, revisedDateStr=2026-01-06, acceptedDate=null, acceptedDateStr=null, onlineDate=1789889329034, onlineDateStr=2026-09-20, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789889329034, onlineIssueDateStr=2026-09-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789889329034, creator=13701087609, updateTime=1789889329034, updator=13701087609, issue=Issue{id=1308453915104665783, tenantId=1146029695717560320, journalId=1146123302524792850, year='2026', volume='39', issue='2', pageStart='1', pageEnd='160', issueExtLink='null', onlineDate='null', pubDate='1775750400000', pubDateStr='2026-04-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789889323259, creator='13701087609', updateTime=1789889766020, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308455772237615687, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308453915104665783, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308455772237615688, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308453915104665783, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=129, endPage=134, ext={EN=ArticleExt(id=1308453939561657164, articleId=1308453939326776139, tenantId=1146029695717560320, journalId=1146123302524792850, language=EN, title=Thermal Environment Optimization of Metro Stations Based on Nature-Like Wind Technology, columnId=1152669334582243706, journalTitle=Urban Rapid Rail Transit, columnName=Electrical and Mechanical Engineering, runingTitle=null, highlight=null, articleAbstract=

To address the problems of high energy consumption and lagging thermal environment regulation in traditional air-conditioning systems of metro stations, this study proposes a dynamic thermal environment management system integrating nature-like wind technology with spatially gridded monitoring, CFD pre-simulation, and equipment-linked control. In the reconstruction project of Nanhu Station of Nanning Rail Transit Line 1, 45 sensors were deployed to construct a gridded monitoring network, and the layout of monitoring points and fan positions was optimized based on CFD pre-simulation. A hierarchical control strategy centered on perceived temperature was developed to realize the intelligent linkage between air conditioners and nature-like wind fans, so as to achieve the energy-saving effect of the air conditioning system. The results show that when the ambient temperature rises to 29℃, the system enhances turbulent heat dissipation (wind speed 0.8–2.5 m/s), making the perceived temperature equivalent to 27℃; the PMV value drops to 0.8–1.2 (PPD≤19%), and the comprehensive energy-saving rate in the air conditioning season reaches 32.1%. The system provides a replicable technical pathway for the green renovation of metro stations.

, authors=Tingsan WEI¹, Langteng GU¹, Zhengjie LI¹, Zhuangfei ZHANG², Jialiang YANG², Weishi SHI¹, authorsList=Tingsan WEI, Langteng GU, Zhengjie LI, Zhuangfei ZHANG, Jialiang YANG, Weishi SHI, authorCompany=null, correspAuthors=Weishi SHI, 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, fund=null), CN=ArticleExt(id=1308453939842675533, articleId=1308453939326776139, tenantId=1146029695717560320, journalId=1146123302524792850, language=CN, title=基于仿自然风技术的地铁车站热环境优化研究, columnId=1152669334955536763, journalTitle=都市快轨交通, columnName=机电工程, runingTitle=null, highlight=null, articleAbstract=

针对地铁车站传统空调系统能耗高、热环境调控滞后等问题，提出一种融合空间网格化监测、计算流体动力学（computational fluid dynamics, CFD）预模拟与设备联动控制等仿自然风技术的动态热环境管理系统。在南宁轨道交通1号线南湖站改造工程中，部署45处传感器构建网格化监测网络，基于CFD预模拟优化布局监测点与风扇位置；研究以体感温度为核心的分级控制策略，实现空调与仿自然风风扇的智能联动，达到空调系统节能的效果。结果表明：在环境温度提升至29℃时，系统通过增强湍流散热（风速0.8~2.5 m/s）使体感温度等效于27℃，预测平均热感觉指数（predicted mean vote, PMV）值降至0.8~1.2（预测不满意百分数（predicted percentage dissatisfied, PPD）≤19%），空调季综合节能率达32.1%。该系统为地铁站绿色改造提供可复用的技术路径。

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韦庭三，男，学士，高级工程师，主要从事轨道交通运维及节能技术研究，weitingsan@nngdjt.com

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韦庭三，男，学士，高级工程师，主要从事轨道交通运维及节能技术研究，weitingsan@nngdjt.com

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