TY - JOUR
T1 - An Integrated Quantitative Risk Assessment Method for Urban Underground Utility Tunnels
AU - Wu, Jiansong
AU - Bai, Yiping
AU - Fang, Weipeng
AU - Zhou, Rui
AU - Reniers, Genserik
AU - Khakzad, Nima
PY - 2021
Y1 - 2021
N2 - With the rapid urbanization, urban underground utility tunnels have seen fast growth in China in the past few years. Urban utility tunnels can house various kinds of city ‘lifelines’ such as natural gas pipeline, heat pipeline, water supply system, sewer pipeline, electricity and telecommunication cables, which are of great significance to guarantee essential flows of energy, information and logistics for urban life. If a utility tunnel accident occurs, the consequences could be catastrophic. Risk assessment has been an important tool to examine the safety performance of industrial facilities and the effectiveness of safety measures. In this study, an integrated model based on dynamic hazard scenario identification (DHSI), Bayesian network (BN) modeling and risk analysis is proposed for risk assessment of urban utility tunnels. The worst-case scenario of urban utility tunnel accidents is identified by DHSI and modelled by BN. Meanwhile, risk analysis is conducted based on the results of BN considering casualties and economic losses. Finally, the integrated method is applied to evaluate the risk level of a real-world utility tunnel. The results indicate that the integrated quantitative risk assessment framework is an alternative and effective tool for safety assessment and land-use planning of urban utility tunnels.
AB - With the rapid urbanization, urban underground utility tunnels have seen fast growth in China in the past few years. Urban utility tunnels can house various kinds of city ‘lifelines’ such as natural gas pipeline, heat pipeline, water supply system, sewer pipeline, electricity and telecommunication cables, which are of great significance to guarantee essential flows of energy, information and logistics for urban life. If a utility tunnel accident occurs, the consequences could be catastrophic. Risk assessment has been an important tool to examine the safety performance of industrial facilities and the effectiveness of safety measures. In this study, an integrated model based on dynamic hazard scenario identification (DHSI), Bayesian network (BN) modeling and risk analysis is proposed for risk assessment of urban utility tunnels. The worst-case scenario of urban utility tunnel accidents is identified by DHSI and modelled by BN. Meanwhile, risk analysis is conducted based on the results of BN considering casualties and economic losses. Finally, the integrated method is applied to evaluate the risk level of a real-world utility tunnel. The results indicate that the integrated quantitative risk assessment framework is an alternative and effective tool for safety assessment and land-use planning of urban utility tunnels.
KW - Bayesian network
KW - Delphi method
KW - Dynamic hazard scenario identification
KW - Risk assessment
KW - Urban underground utility tunnels
UR - http://www.scopus.com/inward/record.url?scp=85107127325&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2021.107792
DO - 10.1016/j.ress.2021.107792
M3 - Article
AN - SCOPUS:85107127325
SN - 0951-8320
VL - 213
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
M1 - 107792
ER -