Article(id=1281627190668275994, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2026.01.0278, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1754755200000, receivedDateStr=2025-08-10, revisedDate=1762272000000, revisedDateStr=2025-11-05, acceptedDate=null, acceptedDateStr=null, onlineDate=1783493333736, onlineDateStr=2026-07-08, pubDate=1769529600000, pubDateStr=2026-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783493333736, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783493333736, creator=13701087609, updateTime=1783493333736, updator=13701087609, issue=Issue{id=1281627156769903305, tenantId=1146029695717560320, journalId=1146031787341344770, year='2026', volume='36', issue='1', pageStart='1', pageEnd='280', issueExtLink='null', onlineDate='null', pubDate='1769529600000', pubDateStr='2026-01-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783493325654, creator='13701087609', updateTime=1783588714348, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282027246013624992, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282027246013624993, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=112, endPage=120, ext={EN=ArticleExt(id=1281627190852825371, articleId=1281627190668275994, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Analysis of failure probability for in-service pipelines based on inverse Gaussian stochastic processes, columnId=1277328337617941059, journalTitle=China Safety Science Journal, columnName=Safety Technology and Engineering, runingTitle=null, highlight=null, articleAbstract=

In-service pipelines are subject to complex stresses, and their performance degradation over time constitutes a dynamic, time-varying stochastic process. To address the challenge that traditional deterministic functions struggle to accurately capture its inherent randomness, a dynamic analysis method for failure probability of in-service pipelines based on a dual stochastic process was proposed. The degradation of pipeline performance was simulated using an inverse Gaussian stochastic process, while the variation of internal pressure loads within the pipeline was described by an equal-interval stationary binomial rectangular wave process probability model. A dual stochastic process probability model for pipeline bearing capacity and internal pressure load was then constructed. Based on statistical parameters and performance degradation data from a specific pipeline's service period, inverse Gaussian distribution was used to fit the performance degradation models at six distinct time points, enabling dynamic failure probability prediction. The results show that the pipeline's service life is predicted to be 16 and 14 years using degradation data from 2 and 4 years, respectively. When utilizing degradation data from 6, 8, and 10 years, the predicted service lives are 12, 11, and 10 years, respectively. Sensitivity analysis indicates that wall thickness, yield strength, pipe diameter, and operating pressure have the most significant impacts on the pipeline's failure probability, followed by the initial depth of defects. In contrast, the initial length of defects, depth corrosion rate, and length corrosion rate have relatively minor effects.

, authors=Kaikai CHENG¹, Kewei LI¹, Xing WANG¹, Nana SUN¹, Gao LYU¹, Guangyuan WENG², authorsList=Kaikai CHENG, Kewei LI, Xing WANG, Nana SUN, Gao LYU, Guangyuan WENG, 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=1281627191624577310, articleId=1281627190668275994, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于逆高斯随机过程的在役管道失效概率分析, columnId=1277328337940902469, journalTitle=中国安全科学学报, columnName=安全技术与工程, runingTitle=null, highlight=null, articleAbstract=

在役管道受复杂应力的影响，性能随时间退化为一个动态时变随机过程，为解决传统确定性函数难以准确描述管道性能随机退化这一难题，提出一种基于双随机过程的在役管道失效概率动态分析方法。采用逆高斯随机过程模拟管道性能退化，以等时段平稳二项矩形波过程概率模型描述管道内压荷载变化，构建管道承载力-内压荷载双随机过程概率模型；基于某管道服役期统计参数和性能退化数据，采用逆高斯分布拟合6个时刻的管道性能退化模型，动态预测失效概率。研究结果表明：采用2、4年的退化数据预测管道的使用寿命为16、14年；采用6、8和10年的退化数据预测管道的使用寿命为12、11和10年。壁厚、屈服强度、管径和运行压力对管道的失效概率影响最大，缺陷初始深度次之，缺陷初始长度、深度腐蚀速率和长度腐蚀速率影响较小。

, authors=程凯凯副教授¹, 李科委¹, 王兴¹, 孙娜娜副教授¹, 吕高讲师¹, 翁光远教授², authorsList=程凯凯副教授, 李科委, 王兴, 孙娜娜副教授, 吕高讲师, 翁光远教授, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=elUgBoacZu/3v3U+Ct7w7g==, magXml=ZGnC4y6slkHo1fasVynMsQ==, pdfUrl=null, pdf=EYqj+lW01oMDV1Uq9GzkYQ==, pdfFileSize=5549586, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=9FY9i2tdrxh2auBZTOYRtw==, mapNumber=null, fund=null)}, authors=[Author(id=1281627192207585574, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627190668275994, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=chengkaikai_1990@126.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281627192278888744, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627190668275994, authorId=1281627192207585574, language=EN, stringName=Kaikai CHENG, firstName=Kaikai, middleName=null, lastName=CHENG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹College of Pipeline Engineering, Xi′an Shiyou University, Xi′an Shaanxi 710065, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281627192354386217, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627190668275994, authorId=1281627192207585574, language=CN, stringName=程凯凯副教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹西安石油大学 管道工程学院，陕西 西安 710065, bio={"content":"

程凯凯（1990—），女，甘肃天水人，博士，副教授，主要从事工程结构可靠性理论方面的研究。E-mail: chengkaikai_1990@126.com。

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程凯凯（1990—），女，甘肃天水人，博士，副教授，主要从事工程结构可靠性理论方面的研究。E-mail: chengkaikai_1990@126.com。

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