Dynamic risk assessment of hybrid hydrogen-gasoline fueling stations using complex network analysis and time-series data

Since hybrid hydrogen-gasoline fueling stations store two types of hazardous chemicals, the number of victims might be substantially higher than at gas or hydrogen fueling stations during a leakage or explosion. Therefore, it is crucial to conduct an in-depth analysis and risk assessment of hybrid hydrogen-gasoline fueling stations. We establish a time series risk assessment model and use complex network analysis to analyze potential fire and explosion events in hybrid hydrogen-gasoline fueling stations. The complex network model is used to assess the structural characteristics of the complex hybrid hydrogen-gasoline fueling stations, extract the accident causal chain, and explain the relationship between the accident causal factors and the system's risk from a multi-dimensional perspective. Subsequently, time-ordered weighted averaging (TOWA) and time-ordered weighted geometric averaging (TOWGA) operators are incorporated into the complex network model. The TOWA-TOWGA hybrid operator combines the evaluation values of the summer and winter periods to obtain the dynamic risk assessment results. The static and dynamic assessment results are used to determine the degree of influence of the accident causal factors on the system risk in different periods and dimensions. The information is suitable for developing highly targeted measures to prevent/control high-risk disaster events in hybrid hydrogen-gasoline fueling stations.