Article(id=1281616692405047700, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281616655499366465, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2026.02.0206, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1760889600000, receivedDateStr=2025-10-20, revisedDate=1766073600000, revisedDateStr=2025-12-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1783490830756, onlineDateStr=2026-07-08, pubDate=1772208000000, pubDateStr=2026-02-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783490830756, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783490830756, creator=13701087609, updateTime=1783490830756, updator=13701087609, issue=Issue{id=1281616655499366465, tenantId=1146029695717560320, journalId=1146031787341344770, year='2026', volume='36', issue='2', pageStart='1', pageEnd='270', issueExtLink='null', onlineDate='null', pubDate='1772208000000', pubDateStr='2026-02-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783490821957, creator='13701087609', updateTime=1783588693138, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282027157069218127, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281616655499366465, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282027157069218128, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281616655499366465, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=121, endPage=126, ext={EN=ArticleExt(id=1281616692723814805, articleId=1281616692405047700, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Risk assessment model for embankment slope failure in mining goafs, columnId=1277328337617941059, journalTitle=China Safety Science Journal, columnName=Safety Technology and Engineering, runingTitle=null, highlight=null, articleAbstract=

To address the challenges in accurately describing uncertainty and multiple failure modes in the risk assessment of embankment slope failures in goaf areas, a risk assessment model based on an improved T-S fuzzy fault tree approach was proposed. Initially, Gaussian fuzzy numbers were introduced to characterize the failure states and occurrence probabilities of basic events, thereby addressing the over-reliance on precise probabilistic data in conventional fault tree analysis and the insufficient representation of intermediate event states. Subsequently, T-S fuzzy model was employed to replace traditional AND/OR relationships in logic gates, capturing the uncertainty and fuzzy characteristics among events, and thereby deriving the failure probability of slope collapse. Finally, an engineering case study was conducted for validation. The results demonstrate that the proposed approach simplifies the fault tree construction, identifies the key risk factors leading to slope failure, provides a ranking of their influence, and reveal the intrinsic relationships between failure events and various factors.

, authors=Bo ZHAO^{1, 2}, authorsList=Bo ZHAO, 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=1281616692954501526, articleId=1281616692405047700, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=采空区路堤边坡滑塌的风险评估模型, columnId=1277328337940902469, journalTitle=中国安全科学学报, columnName=安全技术与工程, runingTitle=null, highlight=null, articleAbstract=

为解决采空区路堤边坡滑塌风险评估中存在的不确定性与多态故障难以准确描述的问题，提出一种基于改进T-S模糊故障树的采空区路堤边坡滑塌风险评估模型。首先，引入高斯模糊数表征各基本事件的故障状态和发生概率，以处理传统故障分析中对数据精确概率的过度依赖，以及事件中间状态表达不足的局限；然后，采用T-S模糊模型替代传统逻辑门中的“与”“或”关系，刻画事件间的不确定性和模糊信息特征，进而推导出边坡发生滑塌的故障概率；最后，通过工程实例进行验证。结果表明：该方法能降低故障树的建立难度，能够识别边坡滑塌的关键致险因子，并给出其影响程度排序，反映出滑塌事件与各因素间的内在关联。

, authors=赵博副教授^{1, 2}, authorsList=赵博副教授, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=GmGkU2gMjZWJOGKmxlQ1Nw==, magXml=aXw8dsru1JrVooIfhW8bIA==, pdfUrl=null, pdf=lk4vmrvLNftpaviGvpR3EQ==, pdfFileSize=2573944, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=SYDL4cbNZtkQWg4aksH3LQ==, mapNumber=null, fund=null)}, authors=[Author(id=1281616693344571806, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281616692405047700, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=zhaobo@tyut.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281616693424263585, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281616692405047700, authorId=1281616693344571806, language=EN, stringName=Bo ZHAO, firstName=Bo, middleName=null, lastName=ZHAO, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=¹College of Civil Engineering, Taiyuan University of Technology, Taiyuan Shanxi 030024, China
²Technology Innovation Center for Risk Prevention and Control of Major Project Geosafety, Ministry of Natural Resources, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281616693508149666, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281616692405047700, authorId=1281616693344571806, language=CN, stringName=赵博副教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=¹太原理工大学 土木工程学院，山西 太原 030024
²自然资源部 重大工程地质安全风险防控工程技术创新中心，北京 100083, bio={"content":"

赵博（1986—），男，山西太原人，博士，副教授，主要从事灾害评价与防治方面的研究。E-mail: zhaobo@tyut.edu.cn。

"}, bioImg=null, bioContent=

赵博（1986—），男，山西太原人，博士，副教授，主要从事灾害评价与防治方面的研究。E-mail: zhaobo@tyut.edu.cn。

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