Research On Fire Scenario Evolution Of Subway Station

Metro stations are significant nodal points of passenger flow.Once conflagration occurs,it will cause immeasurable losses.Reasearch on the evolution of fire scenarios in subway stations can accurately grasp the entire development process of fires,predict the possible development direction of fires.Optimize the treatment effect and improve the effectiveness of emergency response by rationally allocate resources at key nodes of the scenario evolution network.The main research content of the paper is divided into the following parts:(1)Analyze the disaster body,affected body and anti-damaged body in the fire situation of the subway station.Construct the scenario evolution primitive,and analyze the logical relationship between the attributes of the scenario evolution primitive.Combining the scenario evolution primitive with the stochastic network and using the fire scenario to evolve the random network nodes and their connection relationships,this paper proposes a method for constructing a random network for the fire scene evolution of a subway station.(2)According to the time and space factors of subway station fire,analyze the different types of fire characteristics.Divide the corresponding fire evolution disposal stage.Construct a fire scenario evolution simulation network with different fire types and phases by using the fire scenario evolutionary random network construction method.(3)Deduce the subway fire scenario evolutionary simulation network.Bayesian network is used to analyze the evolution probability of the nodes in the fire scenario evolution simulation network;the impact of the fire source on the fire products,the impact of the fire products on the pedestrians in the station,the impact of the emergency resources on the fire source and the station pedestrians are quantified,and the fire scenarios are constructed.Fire state function under the combined effect of three elements.(4)Taking the fire accident of a subway train as an example,a fire scene evolution simulation network model is established,a Bayesian network of key scene node evolution in the simulation network is constructed,and the evolution probability between scene nodes is analyzed.There are a total of 91 path-state evolution path of key scenario nodes in the fire scenario evolution simulation network.The probability of the most favorable evolution path is 5.11 ×10-4.The probability of the most unfavorable evolutionary path is 4.35×10-4.Using FDS simulation software,the fire accident simulation was used to obtain the fire heat release rate and related data of temperature,co concentration and visibility.The relational formula was obtained by fitting with Mtlab,and the fire state function was solved by using Python3.6 to obtain the optimal personnel distribution mode of the key scene nodes in the simulation network.The evacuation effect is optimized compared with the real personnel distribution approach.