Article(id=1149741763620942774, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, articleNumber=1003-3033(2024)02-0110-07, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2024.02.1066, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1692028800000, receivedDateStr=2023-08-15, revisedDate=1700668800000, revisedDateStr=2023-11-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1752049397615, onlineDateStr=2025-07-09, pubDate=1709049600000, pubDateStr=2024-02-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752049397615, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752049397615, creator=13701087609, updateTime=1752049397615, updator=13701087609, issue=Issue{id=1149741761771258326, tenantId=1146029695717560320, journalId=1146031787341344770, year='2024', volume='34', issue='2', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752049397175, creator=13701087609, updateTime=1756468934610, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1168278645379440971, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1168278645379440972, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=110, endPage=116, ext={EN=ArticleExt(id=1149741763860018106, articleId=1149741763620942774, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Risk assessment of hydrogen peroxide production technology by using anthraquinone process based on dynamic Bayesian network, columnId=1149733271128420907, journalTitle=China Safety Science Journal, columnName=Safety social science and safety management, runingTitle=null, highlight=null, articleAbstract=

In order to reduce the risk of fire and explosion caused by the anthraquinone process for preparing hydrogen peroxide,a risk assessment was carried out for the extraction and purification process,which is a more hazardous process in the preparation of hydrogen peroxide by anthraquinone process. Firstly,hazard sources of this process were analysed and a fault tree model was established through Freefta software. On the basis of this fault tree model,a dynamic Bayesian network model was drawn using GeNIe software. Secondly,expert scoring method and fuzzy analysis method were used to calculate prior probabilities of basic events in the model,and GeNIe software was used to calculate posterior probabilities of basic events in the model under the set preconditions. Eventually,by comparing change range between prior and posterior probabilities,important basic events were determined,hazard sources causing fire and explosion were revealed,and emergency response technologies were proposed. The results show that four major hazard sources,including pollution caused by degradation products and impurities,generation and increase of side reactions in process,catalyst failure and active chemical properties of hydrogen peroxide,have great impact on fire and explosion during extraction and purification process. It is more effective to develop emergency response technologies for important hazard sources from the perspective of preventing fire spread and liquid evacuation.

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为降低因蒽醌法制备双氧水而引起的火灾爆炸风险,从蒽醌法制备双氧水工艺中选取危险性较大的萃取净化工序展开风险评估。首先,分析该工序的危险源,采用Freefta软件建立事故树模型,在该模型的基础上使用GeNIe软件绘制事故树转换的动态贝叶斯网络模型;然后,运用专家打分法和模糊分析法计算模型中基本事件的先验概率,运用GeNIe软件在设定的前置条件下计算模型中基本事件的后验概率;最后,比较先验、后验概率之间的变化幅度,确定重要基本事件,揭示引起火灾爆炸的危险源并制定应急处置技术。结果表明:降解物与杂质造成污染、工艺副反应产生并增多、催化剂失效以及双氧水自身化学性质活跃4种重要危险源对萃取净化工序火灾爆炸影响最大;从阻止火灾蔓延与液体疏通的角度针对重要危险源制定应急处置技术效果较好。

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张术琳 (1992—),女,山东烟台人,博士,讲师,主要从事矿井热动力灾害防治、爆炸安全防护技术等方面的研究。E-mail:

鲁 义 教授

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张术琳 (1992—),女,山东烟台人,博士,讲师,主要从事矿井热动力灾害防治、爆炸安全防护技术等方面的研究。E-mail:

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张术琳 (1992—),女,山东烟台人,博士,讲师,主要从事矿井热动力灾害防治、爆炸安全防护技术等方面的研究。E-mail:

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鲁 义 教授

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鲁 义 教授

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tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=https://zhuanlan.zhihu.com/p/626594414, language=null, rfNumber=[2], rfOrder=1, authorNames=null, journalName=null, refType=null, unstructuredReference=双氧水生产装置现状、技术复杂性、防控措施、典型事故分析[EB/OL].(2023-05-04). https://zhuanlan.zhihu.com/p/626594414., articleTitle=双氧水生产装置现状、技术复杂性、防控措施、典型事故分析, refAbstract=null), Reference(id=1168128610633265727, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, doi=null, pmid=null, pmcid=null, year=2021, volume=37, issue=4, pageStart=40, pageEnd=44, url=null, language=null, rfNumber=[3], rfOrder=2, authorNames=李志红, journalName=石油化工安全环保技术, refType=null, unstructuredReference=李志红. 过氧化氢生产工艺危险性分析及防控措施研究[J]. 石油化工安全环保技术, 2021, 37(4):40-44., articleTitle=过氧化氢生产工艺危险性分析及防控措施研究, refAbstract=null), Reference(id=1168128610696180288, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, doi=null, pmid=null, pmcid=null, year=2021, volume=37, issue=4, pageStart=40, pageEnd=44, url=null, language=null, rfNumber=[3], rfOrder=3, authorNames=LI Zhihong, journalName=Petrochemical Safety and Environmental Protection Technology, refType=null, unstructuredReference=LI Zhihong. 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Journal of Safety and Environment, 2007, 7(4):108-110., articleTitle=Study of hydrogen peroxide explosion mechanism and its prevention measures, refAbstract=null)], funds=[Fund(id=1168128609878291001, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, awardId=52304215, language=CN, fundingSource=国家自然科学基金资助(52304215), fundOrder=null, country=null), Fund(id=1168128609974759994, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, awardId=2022GK2042, language=CN, fundingSource=湖南省重点研发计划项目(2022GK2042), fundOrder=null, country=null), Fund(id=1168128610218029627, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, awardId=2023JJ40292, language=CN, fundingSource=湖南省自然科学基金资助(2023JJ40292), fundOrder=null, country=null), Fund(id=1168128610276749884, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, awardId=22C0240, language=CN, fundingSource=湖南省教育厅科学研究项目(22C0240), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1168128606531236361, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, xref=null, ext=[AuthorCompanyExt(id=1168128606535430666, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, companyId=1168128606531236361, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Resource & Environment and Safety Engineering,Hunan University of Science and Technology,Xiangtan Hunan 411201,China), AuthorCompanyExt(id=1168128606543819275, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, companyId=1168128606531236361, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=湖南科技大学 资源环境与安全工程学院,湖南 湘潭 411201)])], figs=[ArticleFig(id=1168128608448033321, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=EN, label=Fig.1, caption=Process flow diagram of hydrogen peroxide preparation by anthraquinone method, figureFileSmall=C30BPP86/66NPQ+MvtKTfg==, figureFileBig=FOVsWxSsReYLOEMDGV3kFA==, tableContent=null), ArticleFig(id=1168128608506753578, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=CN, label=图1, caption=蒽醌法制备双氧水工艺流程[9], figureFileSmall=C30BPP86/66NPQ+MvtKTfg==, figureFileBig=FOVsWxSsReYLOEMDGV3kFA==, tableContent=null), ArticleFig(id=1168128608557085227, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=EN, label=Fig.2, caption=Fault tree model, figureFileSmall=C0bU79yINyLE3Ivp3qAr6A==, figureFileBig=4YqTMqsA525Wp0ZJ/lX+/A==, tableContent=null), ArticleFig(id=1168128608636777004, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=CN, label=图2, caption=事故树模型, figureFileSmall=C0bU79yINyLE3Ivp3qAr6A==, figureFileBig=4YqTMqsA525Wp0ZJ/lX+/A==, tableContent=null), ArticleFig(id=1168128608691302957, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=EN, label=Fig.3, caption=Dynamic Bayesian network model, figureFileSmall=WqWok+yeQtFMdTP4r0Iv7A==, figureFileBig=1bvHrRAxF7qbWw93CIjjTg==, tableContent=null), ArticleFig(id=1168128608745828910, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=CN, label=图3, caption=动态贝叶斯网络模型, figureFileSmall=WqWok+yeQtFMdTP4r0Iv7A==, figureFileBig=1bvHrRAxF7qbWw93CIjjTg==, tableContent=null), ArticleFig(id=1168128608859075119, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=EN, label=Tab.1, caption=

Summary of experts information

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信息 E1 E2 E3 E4 E5
学历 博士 博士 硕士 硕士 博士
工龄 4年 10年 4年 3年 6年
职位 讲师 副教授 讲师 讲师 副教授
信息 E6 E7 E8 E9 E10
学历 博士 博士 博士 博士 博士
工龄 3年 4年 3年 15年 8年
职位 讲师 讲师 讲师 教授 副教授
), ArticleFig(id=1168128608942961200, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=CN, label=表1, caption=

专家信息汇总

, figureFileSmall=null, figureFileBig=null, tableContent=
信息 E1 E2 E3 E4 E5
学历 博士 博士 硕士 硕士 博士
工龄 4年 10年 4年 3年 6年
职位 讲师 副教授 讲师 讲师 副教授
信息 E6 E7 E8 E9 E10
学历 博士 博士 博士 博士 博士
工龄 3年 4年 3年 15年 8年
职位 讲师 讲师 讲师 教授 副教授
), ArticleFig(id=1168128609043624497, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=EN, label=Tab.2, caption=

Summary of experts scoring and prior probabilities

, figureFileSmall=null, figureFileBig=null, tableContent=
X E1 E2 E3 E4 E5 E6 E7 E8 E9 E10 Y
X1 L L L VL L VL L L L L 7.80×10-3
X2 L VL L L L VL L L L VL 7.20×10-3
X3 VL VL VL VL VL VL VL L VL VL 5.90×10-3
X4 VL VL VL VL VL VL VL VL VL L 6.01×10-3
X5 L M M M M L M M M M 1.36×10-2
X6 VL L VL L L VL VL VL L L 7.20×10-3
X7 M VH H H H VH VH H M H 3.40×10-2
X8 VL VL L VL VL VL VL VL VL L 6.10×10-3
X9 M M H H M H H M H H 2.35×10-2
X10 L VL VL L L VL VL VL VL VL 6.30×10-3
X11 L M L L L M L VL L L 8.90×10-3
X12 VL VL VL VL L VL VL VL L VL 6.40×10-3
X13 VL VL VL L L VL VL VL VL VL 6.10×10-3
X14 VL VL VL VL VL VL VL VL VL VL 5.80×10-3
X15 VL L VL VL VL VL VL VL VL VL 6.10×10-3
X16 M L L L L M L L M L 9.60×10-3
X17 L L M M L M L L L H 1.04×10-2
X18 VL VL VL L VL VL VL L VL L 6.30×10-3
X19 VL L L VL VL VL VL L L VL 6.70×10-3
X20 VL VL VL L VL VL VL VL VL VL 5.90×10-3
X21 VL L VL VL VL VL L VL VL VL 6.23×10-3
X22 L L L M L L L L L M 9.02×10-3
X23 L VL L VL L L VL VL VL VL 6.40×10-3
X24 VL L VL VL VL VL L VL L VL 6.60×10-3
X25 VL L L L VL L VL L L L 7.40×10-3
X26 L L VL L VL VL VL VL VL VL 6.30×10-3
X27 M M H H M M H M M H 1.90×10-2
X28 M M M M M H M H H M 1.87×10-2
X29 L L L M L M M L M L 1.00×10-2
X30 VL L L VL VL VL VL VL L L 6.90×10-3
X31 VL L L L L VL L L L L 7.70×10-3
X32 VL VL VL VL VL VL VL VL VL VL 5.80×10-3
X33 VL VL VL VL VL VL VL VL VL VL 5.80×10-3
X34 VL VL VL VL VL VL VL VL VL VL 5.80×10-3
X35 L VL L L VL VL L VL VL VL 6.30×10-3
X36 M M H H H M M M H M 2.05×10-2
X37 L VL L VL L VL L VL VL VL 6.40×10-3
X38 VL L VL VL VL VL VL L VL VL 6.20×10-3
), ArticleFig(id=1168128609140093490, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=CN, label=表2, caption=

专家打分与先验概率汇总

, figureFileSmall=null, figureFileBig=null, tableContent=
X E1 E2 E3 E4 E5 E6 E7 E8 E9 E10 Y
X1 L L L VL L VL L L L L 7.80×10-3
X2 L VL L L L VL L L L VL 7.20×10-3
X3 VL VL VL VL VL VL VL L VL VL 5.90×10-3
X4 VL VL VL VL VL VL VL VL VL L 6.01×10-3
X5 L M M M M L M M M M 1.36×10-2
X6 VL L VL L L VL VL VL L L 7.20×10-3
X7 M VH H H H VH VH H M H 3.40×10-2
X8 VL VL L VL VL VL VL VL VL L 6.10×10-3
X9 M M H H M H H M H H 2.35×10-2
X10 L VL VL L L VL VL VL VL VL 6.30×10-3
X11 L M L L L M L VL L L 8.90×10-3
X12 VL VL VL VL L VL VL VL L VL 6.40×10-3
X13 VL VL VL L L VL VL VL VL VL 6.10×10-3
X14 VL VL VL VL VL VL VL VL VL VL 5.80×10-3
X15 VL L VL VL VL VL VL VL VL VL 6.10×10-3
X16 M L L L L M L L M L 9.60×10-3
X17 L L M M L M L L L H 1.04×10-2
X18 VL VL VL L VL VL VL L VL L 6.30×10-3
X19 VL L L VL VL VL VL L L VL 6.70×10-3
X20 VL VL VL L VL VL VL VL VL VL 5.90×10-3
X21 VL L VL VL VL VL L VL VL VL 6.23×10-3
X22 L L L M L L L L L M 9.02×10-3
X23 L VL L VL L L VL VL VL VL 6.40×10-3
X24 VL L VL VL VL VL L VL L VL 6.60×10-3
X25 VL L L L VL L VL L L L 7.40×10-3
X26 L L VL L VL VL VL VL VL VL 6.30×10-3
X27 M M H H M M H M M H 1.90×10-2
X28 M M M M M H M H H M 1.87×10-2
X29 L L L M L M M L M L 1.00×10-2
X30 VL L L VL VL VL VL VL L L 6.90×10-3
X31 VL L L L L VL L L L L 7.70×10-3
X32 VL VL VL VL VL VL VL VL VL VL 5.80×10-3
X33 VL VL VL VL VL VL VL VL VL VL 5.80×10-3
X34 VL VL VL VL VL VL VL VL VL VL 5.80×10-3
X35 L VL L L VL VL L VL VL VL 6.30×10-3
X36 M M H H H M M M H M 2.05×10-2
X37 L VL L VL L VL L VL VL VL 6.40×10-3
X38 VL L VL VL VL VL VL L VL VL 6.20×10-3
), ArticleFig(id=1168128609240756787, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=EN, label=Tab.3, caption=

Transition probabilities without maintenance

, figureFileSmall=null, figureFileBig=null, tableContent=
t + τ N DS1 DS2 F
N e x p [ - ( λ 1 + λ 4 + λ 5 ) τ ] 0 0 0
DS1 λ 4 λ 1 + λ 4 + λ 5 { 1 - e x p [ - ( λ 1 + λ 4 + λ 5 ) τ ] } e x p [ - ( λ 2 + λ 6 ) τ ] 0 0
DS2 λ 5 λ 1 + λ 4 + λ 5 { 1 - e x p [ - ( λ 1 + λ 4 + λ 5 ) τ ] } λ 6 λ 2 + λ 6 { 1 - e x p [ - ( λ 2 + λ 6 ) τ ] } e x p ( - λ 3 τ ) 0
F λ 1 λ 1 + λ 4 + λ 5 { 1 - e x p [ - ( λ 1 + λ 4 + λ 5 ) τ ] } λ 2 λ 2 + λ 6 { 1 - e x p [ - ( λ 2 + λ 6 ) τ ] } 1 - e x p ( - λ 3 τ ) 1
), ArticleFig(id=1168128609341420084, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=CN, label=表3, caption=

无维修状态下的转移概率[16]

, figureFileSmall=null, figureFileBig=null, tableContent=
t + τ N DS1 DS2 F
N e x p [ - ( λ 1 + λ 4 + λ 5 ) τ ] 0 0 0
DS1 λ 4 λ 1 + λ 4 + λ 5 { 1 - e x p [ - ( λ 1 + λ 4 + λ 5 ) τ ] } e x p [ - ( λ 2 + λ 6 ) τ ] 0 0
DS2 λ 5 λ 1 + λ 4 + λ 5 { 1 - e x p [ - ( λ 1 + λ 4 + λ 5 ) τ ] } λ 6 λ 2 + λ 6 { 1 - e x p [ - ( λ 2 + λ 6 ) τ ] } e x p ( - λ 3 τ ) 0
F λ 1 λ 1 + λ 4 + λ 5 { 1 - e x p [ - ( λ 1 + λ 4 + λ 5 ) τ ] } λ 2 λ 2 + λ 6 { 1 - e x p [ - ( λ 2 + λ 6 ) τ ] } 1 - e x p ( - λ 3 τ ) 1
), ArticleFig(id=1168128609429500469, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=EN, label=Tab.4, caption=

Transition probabilities of moving nodes

, figureFileSmall=null, figureFileBig=null, tableContent=
X λ 1 λ 2 λ 3 λ 4 λ 5 λ 6 X λ 1 λ 2 λ 3 λ 4 λ 5 λ 6
X4 0.09 0.57 0.48 0.27 0.53 0.28 X20 0.10 0.62 0.57 0.28 0.56 0.30
X8 0.01 0.66 0.73 0.29 0.59 0.32 X32 0.10 0.63 0.60 0.29 0.57 0.31
X12 0.10 0.67 0.89 0.30 0.60 0.33 X33 0.10 0.63 0.62 0.29 0.58 0.31
X13 0.01 0.60 0.69 0.29 0.59 0.32 X34 0.09 0.59 0.51 0.27 0.54 0.29
X14 0.08 0.53 0.40 0.25 0.49 0.26 X35 0.10 0.67 0.86 0.30 0.59 0.33
X18 0.01 0.66 0.78 0.30 0.60 0.33
), ArticleFig(id=1168128609509192246, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=CN, label=表4, caption=

动节点转移概率

, figureFileSmall=null, figureFileBig=null, tableContent=
X λ 1 λ 2 λ 3 λ 4 λ 5 λ 6 X λ 1 λ 2 λ 3 λ 4 λ 5 λ 6
X4 0.09 0.57 0.48 0.27 0.53 0.28 X20 0.10 0.62 0.57 0.28 0.56 0.30
X8 0.01 0.66 0.73 0.29 0.59 0.32 X32 0.10 0.63 0.60 0.29 0.57 0.31
X12 0.10 0.67 0.89 0.30 0.60 0.33 X33 0.10 0.63 0.62 0.29 0.58 0.31
X13 0.01 0.60 0.69 0.29 0.59 0.32 X34 0.09 0.59 0.51 0.27 0.54 0.29
X14 0.08 0.53 0.40 0.25 0.49 0.26 X35 0.10 0.67 0.86 0.30 0.59 0.33
X18 0.01 0.66 0.78 0.30 0.60 0.33
), ArticleFig(id=1168128609593078327, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=EN, label=Tab.5, caption=

Posterior probabilities and relative differences of events

, figureFileSmall=null, figureFileBig=null, tableContent=
X G Z X G Z X G Z X G Z
X1 1.09×10-2 0.40 X11 2.30×10-2 1.58 X21 9.70×10-3 0.56 X31 1.40×10-2 0.81
X2 1.03×10-2 0.44 X12 1.03×10-2 0.62 X22 2.92×10-2 2.25 X32 6.10×10-3 0.06
X3 7.20×10-3 0.22 X13 1.10×10-2 0.80 X23 1.18×10-2 0.84 X33 6.10×10-3 0.06
X4 7.16×10-3 0.19 X14 9.61×10-3 0.67 X24 1.43×10-2 1.17 X34 6.10×10-3 0.06
X5 1.57×10-2 0.15 X15 8.85×10-3 0.46 X25 2.18×10-2 1.95 X35 1.22×10-2 0.94
X6 2.01×10-2 1.80 X16 2.48×10-2 1.57 X26 1.50×10-2 1.37 X36 7.32×10-2 2.57
X7 8.10×10-2 1.40 X17 2.67×10-2 1.57 X27 5.89×10-2 2.11 X37 1.52×10-2 1.36
X8 7.90×10-3 0.29 X18 1.32×10-2 1.11 X28 6.01×10-2 2.21 X38 1.33×10-2 1.15
X9 7.09×10-2 2.02 X19 1.42×10-2 1.11 X29 3.96×10-2 2.96
X10 1.67×10-2 1.67 X20 1.03×10-2 0.76 X30 1.52×10-2 1.21
), ArticleFig(id=1168128609748267576, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741763620942774, language=CN, label=表5, caption=

事件的后验概率与相对差值

, figureFileSmall=null, figureFileBig=null, tableContent=
X G Z X G Z X G Z X G Z
X1 1.09×10-2 0.40 X11 2.30×10-2 1.58 X21 9.70×10-3 0.56 X31 1.40×10-2 0.81
X2 1.03×10-2 0.44 X12 1.03×10-2 0.62 X22 2.92×10-2 2.25 X32 6.10×10-3 0.06
X3 7.20×10-3 0.22 X13 1.10×10-2 0.80 X23 1.18×10-2 0.84 X33 6.10×10-3 0.06
X4 7.16×10-3 0.19 X14 9.61×10-3 0.67 X24 1.43×10-2 1.17 X34 6.10×10-3 0.06
X5 1.57×10-2 0.15 X15 8.85×10-3 0.46 X25 2.18×10-2 1.95 X35 1.22×10-2 0.94
X6 2.01×10-2 1.80 X16 2.48×10-2 1.57 X26 1.50×10-2 1.37 X36 7.32×10-2 2.57
X7 8.10×10-2 1.40 X17 2.67×10-2 1.57 X27 5.89×10-2 2.11 X37 1.52×10-2 1.36
X8 7.90×10-3 0.29 X18 1.32×10-2 1.11 X28 6.01×10-2 2.21 X38 1.33×10-2 1.15
X9 7.09×10-2 2.02 X19 1.42×10-2 1.11 X29 3.96×10-2 2.96
X10 1.67×10-2 1.67 X20 1.03×10-2 0.76 X30 1.52×10-2 1.21
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基于动态贝叶斯网络的蒽醌法制备双氧水工艺风险评估
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张术琳 , 王澜凝 , 鲁义
中国安全科学学报 | 安全社会科学与安全管理 2024,34(2): 110-116
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中国安全科学学报 | 安全社会科学与安全管理 2024, 34(2): 110-116
基于动态贝叶斯网络的蒽醌法制备双氧水工艺风险评估
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张术琳 , 王澜凝, 鲁义
作者信息
  • 湖南科技大学 资源环境与安全工程学院,湖南 湘潭 411201
  • 张术琳 (1992—),女,山东烟台人,博士,讲师,主要从事矿井热动力灾害防治、爆炸安全防护技术等方面的研究。E-mail:

    鲁 义 教授

Risk assessment of hydrogen peroxide production technology by using anthraquinone process based on dynamic Bayesian network
Shulin ZHANG , Lanning WANG, Yi LU
Affiliations
  • School of Resource & Environment and Safety Engineering,Hunan University of Science and Technology,Xiangtan Hunan 411201,China
出版时间: 2024-02-28 doi: 10.16265/j.cnki.issn1003-3033.2024.02.1066
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为降低因蒽醌法制备双氧水而引起的火灾爆炸风险,从蒽醌法制备双氧水工艺中选取危险性较大的萃取净化工序展开风险评估。首先,分析该工序的危险源,采用Freefta软件建立事故树模型,在该模型的基础上使用GeNIe软件绘制事故树转换的动态贝叶斯网络模型;然后,运用专家打分法和模糊分析法计算模型中基本事件的先验概率,运用GeNIe软件在设定的前置条件下计算模型中基本事件的后验概率;最后,比较先验、后验概率之间的变化幅度,确定重要基本事件,揭示引起火灾爆炸的危险源并制定应急处置技术。结果表明:降解物与杂质造成污染、工艺副反应产生并增多、催化剂失效以及双氧水自身化学性质活跃4种重要危险源对萃取净化工序火灾爆炸影响最大;从阻止火灾蔓延与液体疏通的角度针对重要危险源制定应急处置技术效果较好。

蒽醌法  /  制备工艺  /  双氧水  /  动态贝叶斯网络  /  风险评估  /  事故树  /  应急处置技术

In order to reduce the risk of fire and explosion caused by the anthraquinone process for preparing hydrogen peroxide,a risk assessment was carried out for the extraction and purification process,which is a more hazardous process in the preparation of hydrogen peroxide by anthraquinone process. Firstly,hazard sources of this process were analysed and a fault tree model was established through Freefta software. On the basis of this fault tree model,a dynamic Bayesian network model was drawn using GeNIe software. Secondly,expert scoring method and fuzzy analysis method were used to calculate prior probabilities of basic events in the model,and GeNIe software was used to calculate posterior probabilities of basic events in the model under the set preconditions. Eventually,by comparing change range between prior and posterior probabilities,important basic events were determined,hazard sources causing fire and explosion were revealed,and emergency response technologies were proposed. The results show that four major hazard sources,including pollution caused by degradation products and impurities,generation and increase of side reactions in process,catalyst failure and active chemical properties of hydrogen peroxide,have great impact on fire and explosion during extraction and purification process. It is more effective to develop emergency response technologies for important hazard sources from the perspective of preventing fire spread and liquid evacuation.

anthraquinone process  /  preparation process  /  hydrogen peroxide  /  dynamic Bayesian network  /  risk assessment  /  fault tree  /  emergency response technology
张术琳, 王澜凝, 鲁义. 基于动态贝叶斯网络的蒽醌法制备双氧水工艺风险评估. 中国安全科学学报, 2024 , 34 (2) : 110 -116 . DOI: 10.16265/j.cnki.issn1003-3033.2024.02.1066
Shulin ZHANG, Lanning WANG, Yi LU. Risk assessment of hydrogen peroxide production technology by using anthraquinone process based on dynamic Bayesian network[J]. China Safety Science Journal, 2024 , 34 (2) : 110 -116 . DOI: 10.16265/j.cnki.issn1003-3033.2024.02.1066
我国正处于高速发展期,双氧水作为一种绿色化工产品,使用范围广泛。目前,普遍采用蒽醌法制备双氧水,该方法存在积液、管道泄漏等不可避免的安全隐患,随时间推移会演化为重大事故。如2023年5月,山东鲁西新区中化集团双氧水生产区发生超压爆炸事故,造成9人死亡、1人受伤[1]。历年涉及双氧水重大事故统计结果显示,12%的事故是由萃取净化工序存在的危险源直接引起[2]
随着蒽醌法制备双氧水工艺的成熟,明确该工艺的危险性是进行工艺风险评估与提升应急处置技术的前提。李志红[3]从蒽醌法基本原理出发,通过列举危险性的具体数值来分析事故发生的原因。王所伟等[4]从受限空间角度分析蒽醌法存在的危险。二者分别从工艺原料环境与人员作业环境2方面证明蒽醌法危险性较大。在明确工艺危险性的基础上展开工艺风险评估是事故预防的有效手段。李奇等[5]运用危险与可操作性分析挖掘出蒽醌法生产工艺流程危险的偏差。李永磊等[6]运用图形化法与二维图形评级技术对比评估2种双氧水制备工艺。这些评价方法均是在时间不变的情况下评价双氧水制备工艺风险,而事故发生概率会随时间变化,因此,要考虑时间因素下各种不利状态累积对双氧水制备工艺安全的影响。不仅如此,当前企业普遍存在应急措施不全面、应急处置技术不成熟的现象,忽视了生产过程中风险分析和预警,对事前预警防范重视不够[7]。一旦发生事故,很可能引发灾难性的多米诺骨牌连锁效应[8]
因此,笔者拟选用蒽醌法,深入分析风险评估方法挖掘出的重要危险源,并针对重要危险源改进应急处置技术,以期降低双氧水制备工艺火灾爆炸事故产生的损失。
蒽醌法具有耗能少、原料获取方便的优点,但工艺复杂,主要包括氢化、氧化、萃取净化、后处理等4道工序,流程如图1所示[9]
在整体工艺流程中,萃取净化工序危险性大。2种反应塔内贮存大量的双氧水,极易受酸碱环境影响,作业夹带的有机溶剂和金属粒子等杂质进入塔内会发生剧烈的分解反应[10];同时,双氧水会受热自发进行分解反应,产生可燃气体易导致火灾爆炸。因此,选择蒽醌法制备双氧水工艺中具有代表性的萃取净化工序进行风险评估,通过揭示重要危险源并提出应急处置技术的改进方向,达到双氧水制备工艺整体安全性的目的。
利用事故树与动态贝叶斯网络相结合的风险评估方法,首先,针对萃取净化工序辨识危险源,找出中间事件;随后,按照逻辑关系逐层向下分析理顺基本事件,并建立事故树模型(图2)。根据事故树模型,利用各个事件之间的因果关系进行映射转换,建立贝叶斯网络模型。相比于事故树模型,贝叶斯网络考虑了多对共因因素对系统的影响[11]。在贝叶斯网络模型基础上,采用马尔可夫模型来描述该制备工艺可能存在的危险状态以及各个危险状态之间的概率转移关系。因此,需要讨论时间对各个状态下事故发生概率的影响,即事件的先验概率与转移概率。通过以往经验与数据收集计算出的概率称为先验概率;描述系统中事件从某一状态出发经过任意一次转移达到另一种状态的概率称为转移概率。
根据时间对基本事件影响程度的大小,将贝叶斯网络节点划分为静节点和动节点,并分别求出静节点的先验概率与动节点的转移概率。
采用专家打分法修正贝叶斯网络模型中的节点概率,从而确定贝叶斯网络节点的先验概率。将事故发生的可能性用极低(VL)、低(L)、中(M)、高(H)、极高(VH) 5个等级表示,邀请10位专家(E1—E10)对基本事件打分,并采用层次分析法判断专家对同一基本事件打分是否合理。根据专家学历、工龄、职位构建判断矩阵,专家信息见表1
通过计算矩阵一致性指标C1与一致性比率Cr检查数据可信度,相关公式如下[12]: C 1 = λ m a x - n n - 1 C r = C 1 R。其中,n为矩阵阶数,λmax为最大特征值,R为平均一致性指标,查表可得R取1.49[13]。通常认为Cr小于0.1[14],表示专家权重符合要求,计算得Cr =0.068<0.1,说明专家意见分歧不大,判断矩阵成立。此外,由于数据资源不丰富,参考数据较少,利用模糊分析法解决不能给出具体数值的问题。同时,结合专家打分法计算基本事件中静节点的先验概率Y。专家打分与Y的计算结果见表2
引入时间片的概念描述一段时间中事故发生概率的变化趋势,计算动节点的转移概率。用退化状态(Degradation State,DS)来描述动节点机能减退、甚至完全消失的情况,动节点在不同时间片中有 4种状态,分别为正常N、第1退化状态(DS1)、第2退化状态(DS2)和失效F。为了描述状态间的转换关系,用λ表示动节点的失效率,设λ1为从正常状态转换为失效状态的失效率,简写为N—F。按上述命名规律,分别令λ2λ3λ4λ5λ6为DS1—F、DS2—F、N—DS1、N—DS2、DS1—DS2的失效率。假定没有维修故障,仅研究各个状态间的失效率。动节点失效转换关系公式[15]为:λ2 =λ5λ3 =λ4 =λ6λ1 +λ4 +λ5 =λλ1:λ4:λ5=1∶3:6。取相邻时间片为90天,无维修状态下时间片的转移概率[16]表3,其中, τ为给定时间片对应时间即2 160 h,t为初始时间即0 h,动节点转移概率见表4
在时间片的基础上,利用GeNIe软件对动节点建立动态贝叶斯网络模型,并进行条件更新,动态贝叶斯网络模型如图3所示。
以90天(3个月)为一个时间片,研究未来3年内的萃取净化工序火灾爆炸事故发生概率,共12个时间片。计算可得,萃取净化工序初始时刻事故发生概率为0.0621,第36个月事故发生概率为 0.310 3,且发生概率持续增长。在萃取净化工序中,双氧水化学性质不稳定、溶液环境多变、装置设备复杂,易导致事故发生。如2021年10月,江苏富强新材料有限公司净化塔内双氧水分解引起火灾,造成2人死亡、1人受伤[17]
为找出对事故影响较大的重要危险源,需拟定危险事故为前置条件,利用动态贝叶斯网络逆向分析,求出该事故下各个基本事件的发生概率,即后验概率。随后,计算先验、后验概率的相对差值,判断重要基本事件。基于上述思路,拟定一年一定发生火灾爆炸事故,用G表示事件后验概率,Z表示相对差值,二者具体数值见表5。选取相对差值由大到小排序前10位的基本事件为重要基本事件,分别为:X6、X9、X10、X11、X22、X25、X27、X28、X29、X36。这些节点对顶上事件影响较大,因此,要着重提升上述基本事件的安全性,防止安全事故发生。
将上述10个重要基本事件划分为4类重要危险源:降解物与杂质污染、副反应产生并增多、催化剂失效、双氧水化学性质活跃。对4类危险源分别提出相应应急处置技术。
降解物与杂质会随工作液夹带流入双氧水槽发生剧烈反应。在工作液槽与可燃气(液)储槽设置阻火器与蒸汽灭火系统。当火势出现时,启动阻火器防止火灾蔓延,同时,启动蒸汽灭火系统释放蒸汽灭火。
副反应产物会造成工作液黏稠,降低反应速率,产生液泛。在氧化液气液分离器口设置放空管并在氢化塔内设置氢化液泵。液泛时放空管使氧化液增多提高氧化效率;氢化液泵输送喷淋氢化液,控制溶液酸碱度并提高氢化效率,缓解积液情况。
失效的催化剂不仅会影响反应效率,其粉化颗粒携带异物进入氧化塔内发生剧烈反应。在管道内设止逆阀,并设氢化液循环系统。当颗粒进入氧化塔时,开启止逆阀阻止工作液流动,防止进一步发生反应;同时,氢化液循环系统工作,氢化液流量增加以提高工作液流动速度,防止发生偏流结块。
萃取塔内大量双氧水受影响会迅速发生连锁分解反应,蒋慧灵等[18]研究表明:双氧水在75~85℃存在吸热过程,应采取水流强度不小于0.047 L/(m2·s) 的冷却措施以保证安全。张志刚等[19]提出利用水冷却以提高热惰性因子来降低双氧水分解速率。在双氧水存储区设置水喷淋系统与温度阈值;当双氧水分解热量上升,启动水喷淋系统并开启报警装置以避免引发事故。
1) 采用动态贝叶斯网络模型分析时间对萃取净化工序火灾爆炸事故发生概率的影响,得到该工序未来3年内发生事故的概率随时间持续升高,第36个月到达0.310 3。
2) 对萃取净化工序进行风险评估,通过计算先验、后验概率相对差值得出4类重要危险源,分别为:降解物与杂质污染、副反应产生并增多、催化剂失效、双氧水化学性质活跃。
3) 根据重要危险源特性改进应急处置技术:设置放空管、液泵与止逆阀来疏通液体从而完善循环系统;选用水蒸汽与水喷淋的灭火方式来提高灭火效率从而完善灭火系统。
  • 国家自然科学基金资助(52304215)
  • 湖南省重点研发计划项目(2022GK2042)
  • 湖南省自然科学基金资助(2023JJ40292)
  • 湖南省教育厅科学研究项目(22C0240)
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ZHANG Zhigang, JIANG Huiling, HUANG Ping. Study of hydrogen peroxide explosion mechanism and its prevention measures[J]. Journal of Safety and Environment, 2007, 7(4):108-110.
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doi: 10.16265/j.cnki.issn1003-3033.2024.02.1066
  • 接收时间:2023-08-15
  • 首发时间:2025-07-09
  • 出版时间:2024-02-28
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  • 收稿日期:2023-08-15
  • 修回日期:2023-11-23
基金
国家自然科学基金资助(52304215)
湖南省重点研发计划项目(2022GK2042)
湖南省自然科学基金资助(2023JJ40292)
湖南省教育厅科学研究项目(22C0240)
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    湖南科技大学 资源环境与安全工程学院,湖南 湘潭 411201
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https://castjournals.cast.org.cn/joweb/zgaqkxxb/CN/10.16265/j.cnki.issn1003-3033.2024.02.1066
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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