Article(id=1282037409105821919, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282037390130790473, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.12.0535, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1752422400000, receivedDateStr=2025-07-14, revisedDate=1758124800000, revisedDateStr=2025-09-18, acceptedDate=null, acceptedDateStr=null, onlineDate=1783591137433, onlineDateStr=2026-07-09, pubDate=1766851200000, pubDateStr=2025-12-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783591137433, onlineIssueDateStr=2026-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783591137433, creator=13701087609, updateTime=1783591137433, updator=13701087609, issue=Issue{id=1282037390130790473, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='12', pageStart='1', pageEnd='259', issueExtLink='null', onlineDate='null', pubDate='1766851200000', pubDateStr='2025-12-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783591132910, creator='13701087609', updateTime=1783593783109, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282048505929777979, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282037390130790473, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282048505929777980, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282037390130790473, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=111, endPage=118, ext={EN=ArticleExt(id=1282037409353285856, articleId=1282037409105821919, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Construction and factor analysis of accident causation model for long-distance oil and gas pipelines, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

In order to explore the theoretical connotation and practical path of the systematic causation model of oil and gas pipeline accidents, 241 domestic and international oil and gas long-distance pipeline accidents were counted first, and the types of domestic and foreign accident causes and the contents of investigation reports were compared and analyzed. Secondly, we integrated the factor system of HFACS model and the hierarchical structure of STAMP model, and put forward an accident causation model that covers 4 system levels and 17 influencing factors. Finally, the N-K model and social network analysis method were used to carry out risk coupling calculation, network model construction, centrality analysis and core-edge analysis. The results show that equipment failure and pipeline corrosion account for 35.3% and 22.8% of the causes of oil and gas long-distance pipeline accidents. The risk coupling value is directly proportional to the number of system-level couplings. Inadequate safety training, delayed emergency response, lack of safety oversight, lack of risk awareness, lack of risk communication, behavioral violations and equipment process issues are the core influences on the accidents. The full life cycle management of accidents includes the reduction phase, readiness phase, response phase, and recovery phase.

, authors=Qian WANG1, Weichun CHANG2, Jingrong ZHAO1, Zhihao WANG1, Zenian GOU2, Ruipeng TONG**, 1, authorsList=Qian WANG, Weichun CHANG, Jingrong ZHAO, Zhihao WANG, Zenian GOU, Ruipeng TONG, authorCompany=null, correspAuthors=Ruipeng TONG, 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=1282037409642692833, articleId=1282037409105821919, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=油气长输管道事故致因模型构建与要素分析, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为探究油气管道事故系统致因模型的理论内涵和实践路径,首先,统计241起国内外油气长输管道事故,对比分析国内外事故原因类型和调查报告内容;其次,融合人因分析与分类系统(HFACS)模型的因素体系和系统理论事故建模与过程(STAMP)模型的层级结构,提出涵盖4个系统层级和17个影响因素的事故致因模型;最后,运用N-K模型和社会网络分析方法开展风险耦合度计算、网络模型构建、中心性分析和核心-边缘分析。结果表明:设备故障和管道腐蚀占油气长输管道事故原因的35.3%和22.8%;风险耦合值与系统层级耦合数量成正比;安全培训不足、应急响应延迟、安全监督缺失、风险意识不足、风险沟通缺失、行为违规、设备工艺问题是事故的核心影响因素,事故全生命周期管理包括缩减阶段、预备阶段、反应阶段和恢复阶段。

, authors=王乾1, 常维纯高级工程师2, 赵晶荣1, 王智浩1, 苟泽念2, 佟瑞鹏教授**, 1, authorsList=王乾, 常维纯高级工程师, 赵晶荣, 王智浩, 苟泽念, 佟瑞鹏教授, authorCompany=null, correspAuthors=佟瑞鹏教授, authorNote=

王乾(1999—),男,河北秦皇岛人,博士研究生,主要研究方向为安全管理、风险评估。E-mail:

, correspAuthorsNote=
** 佟瑞鹏(1977—),男,黑龙江穆棱人,博士,教授,主要从事行为安全管理、职业心理健康、环境风险评估等方面的研究。E-mail:
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王乾(1999—),男,河北秦皇岛人,博士研究生,主要研究方向为安全管理、风险评估。E-mail:

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王乾(1999—),男,河北秦皇岛人,博士研究生,主要研究方向为安全管理、风险评估。E-mail:

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油气长输管道事故致因模型构建与要素分析
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王乾 1 , 常维纯高级工程师 2 , 赵晶荣 1 , 王智浩 1 , 苟泽念 2 , 佟瑞鹏教授 **, 1
中国安全科学学报 | 安全工程技术 2025,35(12): 111-118
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中国安全科学学报 |安全工程技术 2025 , 35 (12) : 111 -118
油气长输管道事故致因模型构建与要素分析
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lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=tongrp@cumtb.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=1, authorType=1, ext={EN=AuthorExt(id=1282037412939415812, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282037409105821919, authorId=1282037412863918338, language=EN, stringName=Ruipeng TONG, firstName=Ruipeng, middleName=null, lastName=TONG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=**, 1, address=1School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1282037413010718981, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282037409105821919, authorId=1282037412863918338, language=CN, stringName=佟瑞鹏教授, firstName=null, middleName=null, lastName=null, 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王乾1 , 常维纯高级工程师2, 赵晶荣1, 王智浩1, 苟泽念2, 佟瑞鹏教授**, 1
作者信息
  • 1中国矿业大学(北京) 应急管理与安全工程学院,北京 100083
  • 2国家管网集团 科学技术研究总院分公司,天津 300457
通讯作者:
** 佟瑞鹏(1977—),男,黑龙江穆棱人,博士,教授,主要从事行为安全管理、职业心理健康、环境风险评估等方面的研究。E-mail:
作者简介:

王乾(1999—),男,河北秦皇岛人,博士研究生,主要研究方向为安全管理、风险评估。E-mail:

Construction and factor analysis of accident causation model for long-distance oil and gas pipelines
Qian WANG1 , Weichun CHANG2, Jingrong ZHAO1, Zhihao WANG1, Zenian GOU2, Ruipeng TONG**, 1
Affiliations
  • 1School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
  • 2PipeChina Research Institute of Science and Technology, Tianjin 300457, China
出版时间: 2025-12-28 doi: 10.16265/j.cnki.issn1003-3033.2025.12.0535
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为探究油气管道事故系统致因模型的理论内涵和实践路径,首先,统计241起国内外油气长输管道事故,对比分析国内外事故原因类型和调查报告内容;其次,融合人因分析与分类系统(HFACS)模型的因素体系和系统理论事故建模与过程(STAMP)模型的层级结构,提出涵盖4个系统层级和17个影响因素的事故致因模型;最后,运用N-K模型和社会网络分析方法开展风险耦合度计算、网络模型构建、中心性分析和核心-边缘分析。结果表明:设备故障和管道腐蚀占油气长输管道事故原因的35.3%和22.8%;风险耦合值与系统层级耦合数量成正比;安全培训不足、应急响应延迟、安全监督缺失、风险意识不足、风险沟通缺失、行为违规、设备工艺问题是事故的核心影响因素,事故全生命周期管理包括缩减阶段、预备阶段、反应阶段和恢复阶段。

油气长输管道事故  /  事故致因模型  /  事故影响因素  /  系统理论事故建模与过程(STAMP)  /  人因分析与分类系统(HFACS)  /  N-K模型  /  社会网络分析

In order to explore the theoretical connotation and practical path of the systematic causation model of oil and gas pipeline accidents, 241 domestic and international oil and gas long-distance pipeline accidents were counted first, and the types of domestic and foreign accident causes and the contents of investigation reports were compared and analyzed. Secondly, we integrated the factor system of HFACS model and the hierarchical structure of STAMP model, and put forward an accident causation model that covers 4 system levels and 17 influencing factors. Finally, the N-K model and social network analysis method were used to carry out risk coupling calculation, network model construction, centrality analysis and core-edge analysis. The results show that equipment failure and pipeline corrosion account for 35.3% and 22.8% of the causes of oil and gas long-distance pipeline accidents. The risk coupling value is directly proportional to the number of system-level couplings. Inadequate safety training, delayed emergency response, lack of safety oversight, lack of risk awareness, lack of risk communication, behavioral violations and equipment process issues are the core influences on the accidents. The full life cycle management of accidents includes the reduction phase, readiness phase, response phase, and recovery phase.

oil and gas long-distance pipeline accidents  /  accident causation model  /  accident influencing factors  /  systems theoretic accident modeling and processes(STAMP)  /  human factors analysis and classification system (HFACS)  /  N-K model  /  social network analysis
王乾, 常维纯高级工程师, 赵晶荣, 王智浩, 苟泽念, 佟瑞鹏教授. 油气长输管道事故致因模型构建与要素分析. 中国安全科学学报, 2025 , 35 (12) : 111 -118 . DOI: 10.16265/j.cnki.issn1003-3033.2025.12.0535
Qian WANG, Weichun CHANG, Jingrong ZHAO, Zhihao WANG, Zenian GOU, Ruipeng TONG. Construction and factor analysis of accident causation model for long-distance oil and gas pipelines[J]. China Safety Science Journal, 2025 , 35 (12) : 111 -118 . DOI: 10.16265/j.cnki.issn1003-3033.2025.12.0535
  • 国家自然科学基金资助(52074302)
  • 国家管网集团科学技术研究总院科研项目(GWHT20250000101)
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2025年第35卷第12期
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doi: 10.16265/j.cnki.issn1003-3033.2025.12.0535
  • 接收时间:2025-07-14
  • 首发时间:2026-07-09
  • 出版时间:2025-12-28
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  • 收稿日期:2025-07-14
  • 修回日期:2025-09-18
基金
国家自然科学基金资助(52074302)
国家管网集团科学技术研究总院科研项目(GWHT20250000101)
作者信息
    1中国矿业大学(北京) 应急管理与安全工程学院,北京 100083
    2国家管网集团 科学技术研究总院分公司,天津 300457

通讯作者:

** 佟瑞鹏(1977—),男,黑龙江穆棱人,博士,教授,主要从事行为安全管理、职业心理健康、环境风险评估等方面的研究。E-mail:
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2种不同金属材料的力学参数

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Genus
种数
Number of
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占总种数比例
Percentage of total
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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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