Causal chain of maritime accidents in Yangtze River Estuary considering coupling effects of multi-risk factors

doi:10.16265/j.cnki.issn1003-3033.2023.03.1367

Abstract

Abstract:

In order to explore the causes of maritime accidents in the Yangtze River Estuary waters, a ship traffic accident analysis method considering the coupling effect of multiple factors was proposed. Firstly, this paper conducted an in-depth analysis of multi-source maritime accident investigation reports and related literatures based on text mining technolog. A set of factors that induced maritime accidents in the Yangtze River Estuary waters was constructed from the environment, ship, human and organizational aspects. Then, the chi-square test was used to analyze the coupling relationship between these risk factors. A BN model of maritime accidents in the Yangtze River Estuary waters was constructed under the action of multi-factor coupling. Finally, the prevention and control countermeasures for ship traffic accidents in the Yangtze River Estuary waters were proposed by performing a sensitivity analysis on the model. The results show that: there are eight causal chains that induce ship traffic accidents in the Yangtze River Estuary waters, and wind, improper cargo stowage, ship type, unsafe speed, negligence of lookout, failure to fully estimate the danger, failure to perform the duty of giving way and failure of control equipment are the eight mutual risk factors that induce ship traffic accidents in the Yangtze River Estuary waters.

Key words: coupling effects of multi-risk factors, Yangtze River Estuary, maritime accidents, causal chains, Bayesian network (BN)

FU Shanshan, ZHANG Yue, XI Yongtao, WENG Jinxian. Causal chain of maritime accidents in Yangtze River Estuary considering coupling effects of multi-risk factors[J]. China Safety Science Journal, 2023, 33(3): 60-67.

Figures/Tables 10

Tab.1

Fig.1

Tab.2

Tab.3

Tab.4

Tab.5

Fig.2

Fig.3

Tab.6

Tab.7

References 15

[1]	WU Bing, TIAN Huibin, YAN Xinping, et al. A probabilistic consequence estimation model for collision accidents in the downstream of Yangtze River using Bayesian networks[J]. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2020, 234(2): 422-436. doi: 10.1177/1748006X19825706
[2]	YAN Xinping, WAN Chengpeng, ZHANG Di, et al. Safety management of waterway congestions under dynamic risk conditions: a case study of the Yangtze River[J]. Applied Soft Computing, 2017, 59: 115-128. doi: 10.1016/j.asoc.2017.05.053
[3]	ZHANG Di, YAN Xinping, YANG Zaili, et al. An accident data-based approach for congestion risk assessment of inland waterways: a Yangtze River case[J]. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2014, 228(2): 176-188. doi: 10.1177/1748006X13508107
[4]	陈伟炯, 卢忆宁, 张善杰, 等. 跨海大桥船桥碰撞模糊Bow-tie风险评估方法[J]. 中国安全科学学报, 2018, 28(1):87-92. doi: 10.16265/j.cnki.issn1003-3033.2018.01.015
	CHEN Weijiong, LU Yining, ZHANG Shanjie, et al. A method for assessing risk of ship sea-bridge collision based on fuzzy-Bow-tie[J]. China Safety Science Journal, 2018, 28(1):87-92. doi: 10.16265/j.cnki.issn1003-3033.2018.01.015
[5]	KUM S, SAHIN B. A root cause analysis for Arctic Marine accidents from 1993 to 2011[J]. Safety Science, 2015, 74: 206-220. doi: 10.1016/j.ssci.2014.12.010
[6]	ZHANG Mingyang, ZHANG Di, GOERLANDT F, et al. Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters[J]. Safety Science, 2019, 111: 128-143. doi: 10.1016/j.ssci.2018.07.002
[7]	WANG Likun, WANG Jinhui, SHI Mingyang, et al. Critical risk factors in ship fire accidents[J]. Maritime Policy & Management, 2021, 48(6): 895-913.
[8]	TRUCCO P, CAGNO E, RUGGERI F, et al. A Bayesian belief network modelling of organizational factors in risk analysis: a case study in maritime transportation[J]. Reliability Engineering & System Safety, 2008, 93(6): 845-856. doi: 10.1016/j.ress.2007.03.035
[9]	WANG Likun, YANG Zaili. Bayesian network modelling and analysis of accident severity in waterborne transportation: a case study in China[J]. Reliability Engineering & System Safety, 2018, 180: 277-289. doi: 10.1016/j.ress.2018.07.021
[10]	陈克嘉, 毛喆, 吴兵, 等. 基于互信息的长江船舶碰撞险情等级预测方法[J]. 中国安全科学学报, 2018, 28(11):168-175. doi: 10.16265/j.cnki.issn1003-3033.2018.11.027
	CHEN Kejia, MAO Zhe, WU Bing, et al. Mutual information based prediction of level of collision incident in Yangtze river[J]. China Safety Science Journal, 2018, 28(11):168-175. doi: 10.16265/j.cnki.issn1003-3033.2018.11.027
[11]	司东森, 张英俊, 郎坤. 基于改进BN的集装箱船舶碰撞事故致因分析[J]. 中国安全科学学报, 2019, 29(10):31-37. doi: 10.16265/j.cnki.issn1003-3033.2019.10.006
	SI Dongsen, ZHANG Yingjun, LANG Kun. Causation analysis of container ship collision accidents based on improved BN[J]. China Safety Science Journal, 2019, 29(10):31-37. doi: 10.16265/j.cnki.issn1003-3033.2019.10.006
[12]	WENG Jinxian, LIAO Shiguan, WU Bing, et al. Exploring effects of ship traffic characteristics and environmental conditions on ship collision frequency[J]. Maritime Policy & Management, 2020, 47(4): 523-543.
[13]	中华人民共和国交通运输部. 水上交通事故统计办法[L].2014-09-30.
[14]	ZHAO Xiaoyuan, YUAN Haiwen, YU Qing. Autonomous vessels in the Yangtze river: a study on the maritime accidents using data-driven Bayesian networks[J]. Sustainability, 2021, 13(17): DOI: 10.3390/su13179985. doi: 10.3390/su13179985
[15]	国际海事组织. 1972年国际海上避碰规则[L]. 1972-10-20.
	International Maritime Organization. International convention on the rules of collision avoidance by sea in 1972[L]. 1972-10-20.

事故类型	中国海事局	上海海事局	IMO	总计
搁浅	0	0	0	0
触碰	4	2	0	6
碰撞	20	16	0	35
火灾/爆炸	0	2	1	3
沉没	6	3	0	9
其他	1	0	0	1
总计	31	23	1	55

类别	风险因素	报告频次	文献频次	总频数
环境因素	大风	10	17	27
	能见度	14	16	30
	船舶交通流量	21	10	31
船舶因素	操纵设备故障	5	3	8
	货物积载不当	5	2	7
	船型	—	14	14
	船龄	—	7	7
	船舶总吨	—	12	12
人为/ 组织因素	不安全航速	22	7	29
	沟通协作不足	15	2	17
	未履行让路义务	15		15
	未能对危险作出充分估计	31	3	34
	未能尽早采取避险措施	24	2	26
	疏忽瞭望	31	2	33
	未配备适任船员	15	2	17

节点	状态1	状态2	状态3
船型	干散货船、散货船、集装箱船等	油船、液化船、散装化学品船等	挖泥船、多用途船、引航船、渔船等
船龄/a	<10	10~20	>20
船舶总吨	<3 000	3 000~10 000	>10 000

变量1	变量2	P值
船舶交通流量	未对危险作出充分估计	0.061
	疏忽瞭望	0
	未履行让路义务	0.035
	不安全航速	0.034
大风	疏忽瞭望	0.075
	货物积载不当	0.010
	不安全航速	0.036
能见度	未履行让路义务	0.055
疏忽瞭望	沟通协作不足	0.020
沟通协作不足	未能尽早采取避险措施	0.013
未配备适任船员	沟通协作不足	0.068
操纵设备故障	不安全航速	0.059

变量1	变量2	P值
碰撞	船舶交通流量	0
	未对危险作出充分估计	0.002
	疏忽瞭望	0
	未履行让路义务	0.001
	未能尽早采取避险措施	0.073
	不安全航速	0
沉没	大风	0
	疏忽瞭望	0
	货物积载不当	0
触碰	未对危险作出充分估计	0.044
触碰	疏忽瞭望	0.044