Research on Fire Risk Assessment of Subway Stations Based on Mathematical Modeling and Simulation

This article conduct a multi subway station pedestrian psychological scale survey and analysis the mechanism of individual attributes, environmental factors, and fire products on panic emotions. At the same time, Pearson correlation analysis method and multi factor variance test are used to scientifically solve the value of pedestrian panic level, avoiding the bias of single factor impact on pedestrian panic in traditional methods. Furthermore, previous studies have mostly focused on the degree of harm to human health caused by fires, neglecting the changing patterns of the emotional impact of fires on pedestrians. Therefore, this article analyzes the differences in the impact of different levels of fire products on pedestrian panic, and quantifies the differential impact thresholds of temperature, visibility, and CO concentration on the degree of panic. To further validate the rationality of the model, this paper sets different fire conditions in PyroSim software to simulate the impact of different levels of fire on pedestrian panic, proving that higher levels of fire will have a more serious impact on pedestrian panic emotions.