|本期目录/Table of Contents|

[1]孟祥坤,陈国明,朱红卫.海底管道泄漏风险演化复杂网络分析[J].中国安全生产科学技术,2017,13(4):26-32.[doi:10.11731/j.issn.1673-193x.2017.04.005]
　MENG Xiangkun,CHEN Guoming,ZHU Hongwei.Complex network analysis on risk evolution of submarine pipeline leakage[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2017,13(4):26-32.[doi:10.11731/j.issn.1673-193x.2017.04.005]
点击复制

海底管道泄漏风险演化复杂网络分析
分享到：

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
13
期数:
2017年4期
页码:
26-32
栏目:
学术论著
出版日期:
2017-04-30

文章信息/Info

Title:
Complex network analysis on risk evolution of submarine pipeline leakage
文章编号:
1673-193X(2017)-04-0026-06
作者:
孟祥坤; 陈国明; 朱红卫
中国石油大学华东 海洋油气装备与安全技术研究中心，山东 青岛 266580
Author(s):
MENG Xiangkun;  CHEN Guoming;  ZHU Hongwei
Center for Offshore Equipment and Safety Technology, China University of Petroleum, Qingdao Shandong 266580, China
关键词:
海底管道; 泄漏事故; 风险; 演化模型; 复杂网络
Keywords:
submarine pipeline;  leakage accident;  risk;  evolution model;  complex network
分类号:
TE58
DOI:
10.11731/j.issn.1673-193x.2017.04.005
文献标志码:
A
摘要:
为了控制海底管道泄漏连锁风险，基于复杂网络，提出针对管道系统泄漏演化的半定量风险演化评价方法，将复杂的事故风险发展过程转化为简洁的网络分析计算。首先，构建包含30个风险节点与54条连接边的海底管道泄漏演化复杂网络模型；其次，采用无权有向网络中的节点出入度和聚类系数进行风险分析，确定影响管道泄漏的关键节点，提出断链控制方案；最后，将演化模型转化为带权的有向网络，采用Dijkstra算法计算各初始事件导致泄漏事故的最短路径。结果表明：海底管道系统泄漏网络的聚类系数为0.13，网络聚集程度偏低而演化性较强；各初始事件的最短路径均不超过10，表现出明显的小世界网络特征，初始事件的风险经少数几步传递即可导致泄漏事故的发生。海底管道泄漏风险演化规律的研究可为抑制初始事件、控制传递事件和减轻后果事件提供理论依据，对预防海底管道泄漏事故发生、保障管道持续安全运行具有现实意义。
Abstract:
To control the cascading risk of submarine pipeline leakage, a semi-quantitative assessment method on risk evolution of submarine pipeline system leakage was proposed based on the complex network, so as to convert the complex development process of accident risk into the simple network analysis and calculation. Firstly, a complex network model on evaluation of submarine pipeline leakage was constructed, which included 30 risk nodes and 54 connection edges. Secondly, the risk analysis was carried out by using the out-in degree of nodes and the clustering coefficients in the unweighted and directed network, then the key nodes influencing the pipeline leakage were determined, and the chain breaking control scheme was put forward. Finally, the evaluation model was converted into a directed network with weight, and the shortest paths of each initial event leading to the leakage accident was calculated by using the Dijkstra algorithm. The results showed that the clustering coefficient of the submarine pipeline system leakage network was 0.13, the network aggregation degree was relatively low, while the evolvability was stronger. All the shortest paths of each initial event were no more than 10, which presented the obvious characteristics of small-world network. The risk of initial events would result in the pipeline leakage accident only by the transfer of a few steps. The research can provide the theoretical foundation for the inhibition of initial events, control of transfer events and mitigation of consequential events, and it has practical significance for preventing the leakage accidents and guarding the continuous safety operation of submarine pipeline.

参考文献/References:

［1］金晓剑, 赵英年, 李健民, 等. 海洋石油工程领域“十一五”技术创新成果及“十二五”展望［J］. 中国海上油气, 2011, 23(5):285-292. JIN Xiaojian, ZHAO Yingnian, LI Jianmin, et al. Technology innovation achievements of the Eleventh Five-year Plan and prospect of the Twelfth Five-year Plan in offshore oil engineering field［J］. China Offshore Oil and Gas, 2011, 23(5):285-292.
［2］Aljaroudi A, Khan F, Akinturk A, et al. Risk assessment of offshore crude oil pipeline failure［J］. Journal of Loss Prevention in the Process Industries, 2015, 37: 101-109.
［3］Vinnem J E. Offshore risk assessment vol. 1 principles, modelling and applications of QRA studies［M］. 3rd ed. London: Springer Verlag, 2014.
［4］胡显伟, 段梦兰, 官耀华. 基于模糊 Bow-tie 模型的深水海底管道定量风险评价研究［J］. 中国安全科学学报, 2012, 22( 3): 128-133. HU Xianwei，DUAN Menglan，GUAN Yaohua. Quantitative risk assessment of deepwater submarine pipeline based on fuzzy bow-tie model［J］. China Safety Science Journal, 2012, 22( 3): 128-133.
［5］李新宏, 朱红卫, 陈国明, 等. 海底管道泄漏天然气扩散规律数值模拟［J］. 油气储运, 2016, 35(2): 215-220. LI Xinhong, ZHU Hongwei, CHEN Guoming, et al. Numerical simulation on the gas diffusion law due to leakageof submarine pipeline［J］. Oil & Gas Storage and Transportation, 2016, 35(2): 215-220.
［6］刘瑞凯, 吴明, 王同秀, 等. 海底埋地热油管道泄漏扩散的数值模拟［J］. 中国安全生产科学技术, 2012, 8(8): 63-68. LIU Ruikai, WU Ming, WANG Tongxiu, et al. Numerical simulation on leakage and diffusion of submarine buried hot oil pipeline［J］. Journal of Safety Science and Technology, 2012, 8(8): 63-68.
［7］B. Blocken, T. Stathopoulos, P. Saathoff， et al. Numerical evaluation of pollutant dispersion in the built environment: comparisons between models and experiments［J］. Journal of Wind Engineering and Industrial Aerodynamics, 2008, 96 (10): 1817-1831.
［8］陈长坤, 纪道溪. 基于复杂网络的台风灾害演化系统风险分析与控制研究［J］. 灾害学, 2012, 27(1): 1-4. CHEN Changkun, JI Daoxi. Risk analysis and control for the evolution disaster system of typhoon based on complex network［J］. Journal of Catastrophology, 2012, 27(1): 1-4.
［9］房丙午, 黄志球, 王勇, 等. 基于贝叶斯网络的复杂系统动态故障树定量分析方法［J］. 电子学报, 2016, 44(5): 1234-1239. FANG Bingwu, HUANG Zhiqiu, WANG Yong, et al. Quantitative analysis method of dynamic fault tree of complex system using Bayesian Network［J］. Acta Electronica Sinica, 2016, 44(5): 1234-1239.
［10］郑啸, 陈建平, 邵佳丽, 等. 基于复杂网络理论的北京公交网络拓扑性质分析［J］. 物理学报, 2012, 61(19): 95-105. ZHENG Xiao，CHEN Jianping，SHAO Jiali，et al. Analysis on topological properties of Beijing urban public transit based on complex network theory［J］. Acta Physica Sinica, 2012, 61(19): 95-105.
［11］武喜萍, 杨红雨, 韩松臣. 基于复杂网络理论的多元混合空管技术保障系统网络特征分析［J］. 物理学报, 2016, 65(14): 15-23. WU Xiping, YANG Hongyu, HAN Songchen. Analysis on network properties of multivariate mixed air traffic management technical support system based on complex network theory［J］. Acta Physica Sinica, 2016, 65(14): 15-23.
［12］苏慧玲, 李扬. 基于电力系统复杂网络特征的线路脆弱性风险分析［J］. 电力自动化设备, 2014, 34(2): 101-107. SU Huiling, LI Yang. Line vulnerability risk analysis based on complex network characteristics of power system［J］. Electric Power Automation Equipment, 2014, 34(2): 101-107.
［13］郭恒, 陈国明. 基于图论的海洋平台连锁风险评价［J］. 中国安全科学学报, 2012, 22(5): 106-112. GUO Heng, CHEN Guoming. Offshore platform chain risk assessment based on Graph Theory［J］. China Safety Science Journal, 2012, 22(5): 106-112.
［14］徐俊明. 图论及其应用［M］. 合肥: 中国科学技术大学出版社, 2010: 31-34.

相似文献/References:

[1]刘瑞凯,吴〓明,王同秀,等.海底埋地热油管道泄漏扩散的数值模拟[J].中国安全生产科学技术,2012,8(8):63.
　LIU Rui kai,WU Ming,WANG Tong xiu,et al.Numerical simulation on leakage and diffusion of submarine buried hot oil pipeline[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2012,8(4):63.
[2]李久安,,彭小明,等.多功能闸门应急处理难溶性液态有机泄漏物性能[J].中国安全生产科学技术,2012,8(9):27.
[3]华〓敏,尹〓新,潘旭海.毒气泄漏事故避难场所避难效果分析[J].中国安全生产科学技术,2012,8(9):95.
　HUA Min,YIN Xin,PAN Xu hai.Effect analysis of shelter for toxic gas release incident[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2012,8(4):95.
[4]雷洋,马继军,谢永平,等.火电厂液氨泄漏事故影响分析及对策研究[J].中国安全生产科学技术,2013,9(5):56.[doi:10.11731/j.issn.1673-193x.2013.05.011]
　LEI Yang,MA Ji jun,XIE Yong ping,et al.Impact analysis and response of liquid ammonia leakage accident in thermal power plant[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2013,9(4):56.[doi:10.11731/j.issn.1673-193x.2013.05.011]
[5]易高翔,杨春生,马良俊,等.基于GIS危险化学品泄漏扩散事故处置系统研究与实现*[J].中国安全生产科学技术,2008,4(05):70.
　YI Gao xiang,YANG Chun sheng,MA Liang jun,et al.Research and implementation of treatment system for leakage and diffusion of hazardous material based on GIS[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2008,4(4):70.
[6]黄坤,李沅桦,孔令圳.基于参考应力法的海底腐蚀管道剩余强度评价[J].中国安全生产科学技术,2017,13(7):163.[doi:10.11731/j.issn.1673-193x.2017.07.026]
　HUANG Kun,LI Yuanhua,KONG Lingzhen.Evaluation on residual strength of submarine corrosion pipeline based on reference stress method[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2017,13(4):163.[doi:10.11731/j.issn.1673-193x.2017.07.026]
[7]杨继星,佘笑梅,黄玉钏,等.基于BP神经网络的苯储罐泄漏事故风险评价模型研究[J].中国安全生产科学技术,2019,15(1):157.[doi:10.11731/j.issn.1673-193x.2019.01.025]
　YANG Jixing,SHE Xiaomei,HUANG Yuchuan,et al.Research on risk assessment model for leakage accident of benzene tank based on BP neural network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2019,15(4):157.[doi:10.11731/j.issn.1673-193x.2019.01.025]
[8]朱红卫,智晨潇,李新宏,等.基于JSA-BN的水上提管维修作业风险分析[J].中国安全生产科学技术,2019,15(3):98.[doi:10.11731/j.issn.1673-193x.2019.03.016]
　ZHU Hongwei,ZHI Chenxiao,LI Xinhong,et al.Risk analysis on operation of abovewater lifting pipeline maintenance based on JSA-BN[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2019,15(4):98.[doi:10.11731/j.issn.1673-193x.2019.03.016]
[9]余杨,高涵韬,徐立新,等.基于毕达哥拉斯模糊贝叶斯网络的海底管道泄漏风险分析*[J].中国安全生产科学技术,2022,18(11):19.[doi:10.11731/j.issn.1673-193x.2022.11.003]
　YU Yang,GAO Hantao,XU Lixin,et al.Risk analysis on leakage of submarine pipeline based on Pythagorean fuzzy Bayesian network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2022,18(4):19.[doi:10.11731/j.issn.1673-193x.2022.11.003]
[10]杨亚吉,曲兆光,王文光,等.基于瞬态特性的海底长输天然气管道泄漏规律研究[J].中国安全生产科学技术,2023,19(6):119.[doi:10.11731/j.issn.1673-193x.2023.06.017]
　YANG Yaji,QU Zhaoguang,WANG Wenguang,et al.Research on leakage law of submarine long-distance gas pipeline based on transient characteristics[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(4):119.[doi:10.11731/j.issn.1673-193x.2023.06.017]

备注/Memo

备注/Memo:
国家重点研发计划项目(2016YFC0802305)；山东省科技发展计划项目（2014GSF120014）
更新日期/Last Update: 2017-05-11