The Statistics Law Of Fire Response Time And Its Correlation With The Scale Of Urban Fire

Urban fire is one of fatal disasters which affect human life and property security and socio-economic development seriously. With rapid economic development and deepening of urbanization of China, the number of fire in the city was increasing constantly besides total fire losses are ascending greatly. City Fire Station is the backbone of the fire prevention and rescue. However when face to the severe fire situation, the fire brigade takes measures to reduce the response time (the first response time and combat time)in order to improve the efficiency. So that it can effectively control the spread of fire and reduce fire losses.Traditional urban fire researches are based on statistical analysis of the time, location and size of fire. It emphasizes the character of fire and focuses on the hazard risk assessment of occurrence and consequences. While most of the other academic researches about rescue of fire brigade are discuss the planning and allocation problem. They take the fixed fire time as a parameter in the fire station allocation problem. But they do not involve the correlation between the fire response time and fire scale (fire size and fire losses).However we must comprehend the city fire laws and fire brigade rescue features in order to obtain a scientific and rational planning project when we do urban fire station resource planning and allocation.In this article we study on the statistics law of fire response time and its correlation with the scale of urban fire (burned area and direct losses) by the means of qualitative and quantitative which is on the basis of existing research work and according to the urban fire data of Japan and China. Through statistical data and simulation results we found that both the first response time and fighting time accord with log-normal distribution law and the probability of occurrence of the burned area with the first response time has the power function relationship. At the same time we can calculated that with the first response time increased the probability of small fire decreased and the probability of medium-sized fire increase while the probability of major fire occurred relatively stable from the first response time. In addition both the average of burned area and direct losses have positive relationship with the first response time and fight time. Through the fire data, this article also gives the quantitative function. By the above rules and conclusions, this paper randomly generated the first response time firstly then combined with the cumulative probability function of burned area with Monte Carlo simulation method. By repeating test we finally got the occurrence probability map of burned area which has strong consistency with the real situation. Using this method we can calculate the actual city regional fire probability although we only grasp the overall urban fire distribution and regional fire bridge response law.Although fire is uncertainty, but through this article we can obtain quantitatively that fire response time and fire size has a strong consistency at the macro level. The conclusions and methods can strengthen the city disaster preparedness capacity.