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In order to further prevent subway crowd stampede accidents and improve the safety management of metro stations, a metro crowd stampede resilience concept was proposed based on resilience theory. Centered on absorption capacity, resistance capacity, recovery capacity, and adaptation capacity, the developmental stages of metro crowd stampede resilience were analyzed, and a resilience evaluation index system was constructed by identifying core influencing factors related to crowd density. By integrating SD with MEE model, a metro crowd stampede resilience evaluation model was developed. This model was then applied to analyze the Beijing Xizhimen Metro Station. Results show that the model overcomes the limitation of traditional static evaluation models in depicting the dynamic evolution of the metro system's resilience capacity over time, enabling a quantitative assessment of dynamic resilience changes. The overall resilience level of Xizhimen Station is Grade II (relatively high resilience). However, due to delays in real-time monitoring and insufficient emergency response, it drops to Grade III (moderate resilience) during morning peak hours, with adaptability constrained by the low coverage rate of intelligent systems.

, authors=Qiquan WANG, Weixiang FENG, Songli YANG, authorsList=Qiquan WANG, Weixiang FENG, Songli YANG, authorCompany=null, correspAuthors=null, 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=1282037431776023367, articleId=1282037428970033987, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于SD-MEE模型的地铁拥挤踩踏事故韧性评估, columnId=1149733271510106222, journalTitle=中国安全科学学报, columnName=公共安全, runingTitle=null, highlight=null, articleAbstract=

为进一步避免地铁拥挤踩踏事故发生，提高地铁站安全管理水平，基于韧性理论提出地铁拥挤踩踏韧性理念。首先，以吸收能力、抵抗能力、恢复能力和适应能力为核心，重点分析地铁拥挤踩踏事故韧性发展阶段，围绕人群密度核心影响因素构建地铁拥挤踩踏韧性评估指标体系；然后，将系统动力学（SD）与物元可拓（MEE）模型相结合，构建地铁拥挤踩踏韧性评估模型；最后，以北京西直门地铁站为例验证该模型。结果表明：该模型突破传统静态评估模型难以刻画地铁系统韧性能力随时间动态演变过程的局限，实现韧性能力动态变化的定量化评估；西直门地铁站总体韧性等级为Ⅱ级（较高韧性），但由于实时监测滞后和应急响应不足，在早高峰期间降为Ⅲ级（一般韧性），适应性受限于智能系统覆盖率较低。

, authors=王起全教授, 冯炜翔, 杨松立, authorsList=王起全教授, 冯炜翔, 杨松立, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=VWw6nKkSaiMoHTERVnW7dg==, magXml=0tX/G2M8Td+40oXvUhH1WA==, pdfUrl=null, pdf=XQYYpbQn5KDIyxkpXeKPKg==, pdfFileSize=5830336, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=8aOsZlUeFCSskUTaKEXRxQ==, mapNumber=null, fund=null)}, authors=[Author(id=1282037432216425292, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282037428970033987, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=wqq_100@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1282037432283534158, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282037428970033987, authorId=1282037432216425292, language=EN, stringName=Qiquan WANG, firstName=Qiquan, middleName=null, lastName=WANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=School of Safety Engineering, China University of Labor Relations, Beijing 100048, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1282037432363225935, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282037428970033987, authorId=1282037432216425292, language=CN, stringName=王起全教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中国劳动关系学院 安全工程学院，北京 100048, bio={"content":"

王起全（1976—），男，山东齐河人，博士，教授，主要从事公共安全应急管理、风险评价、大数据预警分析等方面的研究。E-mail: wqq_100@163.com。

"}, bioImg=null, bioContent=

王起全（1976—），男，山东齐河人，博士，教授，主要从事公共安全应急管理、风险评价、大数据预警分析等方面的研究。E-mail: wqq_100@163.com。

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