TY - JOUR
T1 - Dynamic safety assessment of natural gas stations using Bayesian network
AU - Zarei, Esmaeil
AU - Azadeh, Ali
AU - Khakzad, N.
AU - Mirzaei Aliabadi, Mostafa
AU - Mohammadfam, Iraj
PY - 2017
Y1 - 2017
N2 - Pipelines are one of the most popular and effective ways of transporting hazardous materials, especially natural gas. However, the rapid development of gas pipelines and stations in urban areas has introduced a serious threat to public safety and assets. Although different methods have been developed for risk analysis of gas transportation systems, a comprehensive methodology for risk analysis is still lacking, especially in natural gas stations. The present work is aimed at developing a dynamic and comprehensive quantitative risk analysis (DCQRA) approach for accident scenario and risk modeling of natural gas stations. In this approach, a FMEA is used for hazard analysis while a Bow-tie diagram and Bayesian network are employed to model the worst-case accident scenario and to assess the risks. The results have indicated that the failure of the regulator system was the worst-case accident scenario with the human error as the most contributing factor. Thus, in risk management plan of natural gas stations, priority should be given to the most probable root events and main contribution factors, which have identified in the present study, in order to reduce the occurrence probability of the accident scenarios and thus alleviate the risks.
AB - Pipelines are one of the most popular and effective ways of transporting hazardous materials, especially natural gas. However, the rapid development of gas pipelines and stations in urban areas has introduced a serious threat to public safety and assets. Although different methods have been developed for risk analysis of gas transportation systems, a comprehensive methodology for risk analysis is still lacking, especially in natural gas stations. The present work is aimed at developing a dynamic and comprehensive quantitative risk analysis (DCQRA) approach for accident scenario and risk modeling of natural gas stations. In this approach, a FMEA is used for hazard analysis while a Bow-tie diagram and Bayesian network are employed to model the worst-case accident scenario and to assess the risks. The results have indicated that the failure of the regulator system was the worst-case accident scenario with the human error as the most contributing factor. Thus, in risk management plan of natural gas stations, priority should be given to the most probable root events and main contribution factors, which have identified in the present study, in order to reduce the occurrence probability of the accident scenarios and thus alleviate the risks.
KW - Dynamic risk analysis
KW - Bayesian network
KW - Bow-tie approach
KW - City gate station
KW - FMEA
UR - http://resolver.tudelft.nl/uuid:056bae80-5ec5-4df9-be6a-5ad461d72823
U2 - 10.1016/j.jhazmat.2016.09.074
DO - 10.1016/j.jhazmat.2016.09.074
M3 - Article
VL - 321
SP - 830
EP - 840
JO - Journal of Hazardous Materials
JF - Journal of Hazardous Materials
SN - 0304-3894
ER -