Cause factors in emergency process of fire accident for oil–gas storage and transportation based on fault tree analysis and modified Bayesian network model
Restricted accessResearch articleFirst published online August, 2018
Cause factors in emergency process of fire accident for oil–gas storage and transportation based on fault tree analysis and modified Bayesian network model
From the perspective of the safety of emergency process, in this paper, we put forward a new analysis method of cause factors based on fault tree analysis and modified Bayesian network in emergency process of fire accident for oil–gas storage and transportation. Nineteen cause factors are found based on the statistical analysis of actual accident cases. We adopt fault tree analysis method and Bayesian network model to analyze cause factors qualitatively and quantitatively. In order to more accurately determine the quantitative influencing degree of each cause factor, the conditional probabilities in Bayesian network are modified by using expert scoring method and modified Bayesian network model is established. Finally, the proposed method is applied to analyze cause factors in emergency process of two practical accident cases. Research results have an important scientific significance to reveal evolution mechanism of secondary accidents in emergency process and ensure system safety in whole life cycle.
EckhoffRK.Explosion hazards in the process industries. 2nd ed.
Oxford:
Gulf Professional Publishing, 2016.
3.
MorenoVCCozzaniV. Hazard identification in process technology. In: Reedijk J (ed) Reference Module in Chemistry. Molecular Sciences and Chemical Engineering. Waltham, MA: Elsevier, 2017, pp. 1–8.
4.
HaeriA.Comprehensive plan for assessing and improving safety level of commercial centers towards the prevention of social and economical consequences of accidents. Safety Sci2016;
89: 263–273.
5.
LiuHCYouJXChenSMet al.
An integrated failure mode and effect analysis approach for accurate risk assessment under uncertainty. IIE Trans2016;
48: 1027–1042.
6.
LiuHCChenYZYouJXet al.
Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach. J Intell Manuf2016;
27: 805–816.
7.
AlilecheNOlivierDEstelLet al.
Analysis of domino effect in the process industry using the event tree method. Safety Sci2017;
97: 10–19.
8.
AlkhaledKAlrushaidSAlmansouriJet al.
Using fault tree analysis in the Al-Ahmadi town gas leak incidents. Safety Sci2015;
79: 184–192.
9.
NezamodiniZSRezvaniZKianK.Dow’s fire and explosion index: a case-study in the process unit of an oil extraction factory. Electr Phys2017;
9: 3878–3882.
10.
ZhouTQWuCZZhangJYet al.
Incorporating CREAM and MCS into fault tree analysis of LNG carrier spill accidents. Safety Sci2017;
96: 183–191.
11.
IsimiteJRubiniP.A dynamic HAZOP case study using the city refinery explosion. J Loss Prevent Process Industr2016;
40: 496–501.
12.
XiaoGQFengMYXiaoRJ.ISM analysis of blowout accident causes for oil and gas fields. Technol Supervis Petrol Ind2015;
7: 53–57.
13.
HuangPXuJJLaiYSet al.
Human factors analysis of leakage explosion of oil and gas pipeline based on HFACS and AHP. Safety Environ Eng2016;
23: 114–118.
14.
ZengH.Study on quantitative analysis of effect factors and prevention intervention of major industrial accident.
Guangzhou:
South China University of Technology, 2012, pp. 43–48.
15.
FuGCaoJLWangXM.Relationship analysis of causal factors in coal and gas outburst accidents based on the 24Model. Energy Proced2017;
107: 314–320.
16.
LavasaniSMZendeganiACelikM.An extension to fuzzy fault tree analysis (FFTA) application in petrochemical process industry. Process Safety Environ Protect2015;
93: 75–88.
17.
LavasaniSMRamzaliNSabzalipourFet al.
Utilisation of fuzzy fault tree analysis (FFTA) for quantified risk analysis of leakage in abandoned oil and natural-gas wells. Ocean Eng2015;
108: 729–737.
18.
GonzálezJRArnaldosDJDarbraRM.Introduction of the human factor in the estimation of accident frequencies through fuzzy logic. Safety Sci2017;
97: 134–143.
19.
WuJSZhouRXuSDet al.
Probabilistic analysis of natural gas pipeline network accident based on Bayesian network. J Loss Prevent Process Ind2017;
46: 126–136.
20.
HuangYMMaGWLiJD.Grid-based risk mapping for gas explosion accidents by using Bayesian network method. J Loss Prevent Process Ind2017;
48: 223–232.
21.
ZhangQL.Analysis of typical oil tank fire accidents in China and abroad.
Tianjin:
Tianjin University Press, 2013.
22.
WangYX.Save and emergency rescue for petroleum and chemical fire.
Beijing:
Chinese People’s Public Security University Press, 2016.
23.
KabirS.An overview of fault tree analysis and its application in model based dependability analysis. Expert Syst Appl2017;
77: 114–135.
24.
SmithDVeitchBKhanFet al.
Understanding industrial safety: comparing fault tree, Bayesian network, and FRAM approaches. J Loss Prevent Process Ind2017;
45: 88–101.
25.
JunHBKimD.Bayesian A. Network-based approach for fault analysis. Expert Syst Appl2017;
81: 332–348.
26.
LiXHChenGMZhuHW.Quantitative risk analysis on leakage failure of submarine oil and gas pipelines using Bayesiannetwork. Proc Safety Environ Protect2016;
103: 163–173.
27.
ZhaoNNZhaoYT.Risk analysis of the runway excursion and overrun event based on the fault tree and Bayesian networks. J Safety Environ2014;
14: 141–145.
28.
NassajABarabadyJ. Fault tree analysis of oil and gas distillation tower and application of Bayesian networks. In: 2016 IEEE international conference on industrial engineering and engineering management (IEEM). 4–7 December 2016, Bali, Indonesia, pp. 1669–1673.
29.
XinPWKhanFAhmedS.Dynamic hazard identification and scenariomapping using Bayesian network. Process Safety Environ Protect2017;
105: 143–155.
30.
Office of the State Council Security Committee of China. Report on the results of investigation and handling of four accidents of “7.16” oil pipeline explosion fire in Dalian-owned enterprises owned by China National Petroleum Corporation, http://www.esafety.cn/law/67499.html (accessed 25 November 2011).
31.
LiJC.Talk about the tactical application on firefighting in Qingdao petroleum company fire accident. Shandong Fire Prevent Contr1996;
10: 18–21.
