Research on the temporal dynamic risk assessment of hybrid hydrogen-gasoline fueling stations
As a new type of energy infrastructure,hybrid hydrogen-gasoline fueling stations face many new safety problems in the process of obtaining traditional oil refilling and hydrogen fuel operation,and a detailed and comprehensive risk assessment model is an important theoretical support for the safety management of hybrid hydrogen-gasoline fueling stations.In this paper,we proposed a dynamic risk assessment model based on a complex network analysis of hybrid hydrogen-gasoline fueling stations'temporal sequence,and apply it to the fire and explosion accident of hybrid hydrogen-gasoline fueling stations.Firstly,the complex network structure of hybrid hydrogen-gasoline fueling stations constructed by the disaster chain was characterized,and the causal chain of accidents was drawn to explore the path of accidents and the intrinsic causal mechanism.Secondly,considering the differences in the risk development trend patterns in different periods,the Time-Ordered Weighted Averaging(TOWA)and Time-Ordered Weighted Geometric Averaging(TOWGA)operators were introduced to combine the seasonal dimensions to conduct a dynamic as well as static assessment of hybrid hydrogen-gasoline fueling stations.The static assessment should focus on degree centrality values in the spring period,meso-centrality results in the summer period,and near-centrality values in the autumn and winter periods.Through dynamic evaluation,it is demonstrated that the results are consistent regardless of using TOWA,TOWGA,and TOWA-TOWGA.Specifically,the combined assessment of the three causality analyses indicates that degree centrality yields the most favorable overall assessment result,followed by the results respectively with the use of meso-centrality and proximity centrality.Therefore,more attention should be paid to the assessment results of degree centrality in all aspects of accident prevention.The method constructed in this paper can intuitively reveal the degree of influence of each risk indicator on the overall risk of the system under the difference of each period,providing a useful exploration for the prevention and control of high-risk disaster events from the seasonal perspectives.
万方数据
维普
