Dynamic risk investigation of urban natural gas pipeline accidents using Stochastic Petri net approach

Abstract

The safety of urban gas pipelines is challenged by a series of adverse factors, and the unexpected accidents may pose a catastrophic threat to humans, the environment and assets. The existing studies mainly focused on causation investigation of natural gas pipeline accident, the dynamic evolution process of urban natural gas pipeline accident is still challenging task for accident prevention. To find out the unfavorable factors that cause accidents, this study presents a dynamic risk modeling of urban natural gas pipeline accidents using Stochastic Petri net (SPN). An SPN model of an accident evolution process is constructed based on the discrete events in an accident flowchart, and the critical places and transitions are evaluated through this model. Considering the slow development of the early events leading to accidents, the delay time of the transitions at this stage cannot be determined, Bayesian theory is used to dynamically update SPN model. Critical accident nodes and their occurrence probabilities are estimated, which are used to support the efficient risk management strategies. The gas explosion accident in Shiyan, Hubei, as a representative case is investigated, and the results show that pipeline corrosion, ignition sources, inefficient information feedback and unreasonable solutions are critical accident causations. The probabilities of critical accident nodes increase over time, which means that these factors need to be managed efficiently to prevent the accidents. The application shows that the model can be used as a tool for gas companies and governments to investigate urban gas pipeline accidents.