Dynamic probability assessment of urban natural gas pipeline accidents considering integrated external activities

Urban gas pipelines usually have high structural vulnerability due to long service time. The locations across urban areas with high population density make the gas pipelines easily exposed to external activities. Recently, urban pipelines may also have been the target of terrorist attacks. Neverthel...

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Bibliographic Details
Main Authors: Abbassi, R. (Author), Chen, G. (Author), Li, X. (Author), Yang, M. (Author), Zhang, R. (Author), Zhang, Y. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2021
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02965nam a2200481Ia 4500
001 10.1016-j.jlp.2020.104388
008 220427s2021 CNT 000 0 und d
020 |a 09504230 (ISSN) 
245 1 0 |a Dynamic probability assessment of urban natural gas pipeline accidents considering integrated external activities 
260 0 |b Elsevier Ltd  |c 2021 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1016/j.jlp.2020.104388 
520 3 |a Urban gas pipelines usually have high structural vulnerability due to long service time. The locations across urban areas with high population density make the gas pipelines easily exposed to external activities. Recently, urban pipelines may also have been the target of terrorist attacks. Nevertheless, the intentional damage, i.e. terrorist attack, was seldom considered in previous risk analysis of urban gas pipelines. This work presents a dynamic risk analysis of external activities to urban gas pipelines, which integrates unintentional and intentional damage to pipelines in a unified framework. A Bayesian network mapping from the Bow-tie model is used to represent the evolution process of pipeline accidents initiating from intentional and unintentional hazards. The probabilities of basic events and safety barriers are estimated by adopting the Fuzzy set theory and hierarchical Bayesian analysis (HBA). The developed model enables assessment of the dynamic probabilities of consequences and identifies the most credible contributing factors to the risk, given observed evidence. It also captures both data and model uncertainties. Eventually, an industrial case is presented to illustrate the applicability and effectiveness of the developed methodology. It is observed that the proposed methodology helps to more accurately conduct risk assessment and management of urban natural gas pipelines. © 2021 Elsevier Ltd 
650 0 4 |a Accidents 
650 0 4 |a Bayesian network 
650 0 4 |a Bayesian networks 
650 0 4 |a Contributing factor 
650 0 4 |a Density of gases 
650 0 4 |a External activities 
650 0 4 |a Fuzzy set theory 
650 0 4 |a Gases 
650 0 4 |a Hierarchical Bayesian analysis 
650 0 4 |a High population density 
650 0 4 |a Integrated risk assessment 
650 0 4 |a Model uncertainties 
650 0 4 |a Natural gas 
650 0 4 |a Natural gas pipelines 
650 0 4 |a Pipeline accidents 
650 0 4 |a Population statistics 
650 0 4 |a Probability assessments 
650 0 4 |a Risk analysis 
650 0 4 |a Risk assessment 
650 0 4 |a Risk assessment and managements 
650 0 4 |a Structural vulnerability 
650 0 4 |a Terrorism 
650 0 4 |a Uncertainty analysis 
650 0 4 |a Urban gas pipeline 
700 1 |a Abbassi, R.  |e author 
700 1 |a Chen, G.  |e author 
700 1 |a Li, X.  |e author 
700 1 |a Yang, M.  |e author 
700 1 |a Zhang, R.  |e author 
700 1 |a Zhang, Y.  |e author 
773 |t Journal of Loss Prevention in the Process Industries