Abstract
The spatial–temporal simulation of fire disasters and evacuation route planning are important research fields for urban emergency responses and are primary tasks that answer complex questions after fires break out. The increasing demand for refined building information models will sharply increase the calculated and analyzed quantity. This demand presents a challenge for fire emergency responses based on massive building information. In this paper, the principle of the realistic worst case (RWC) is introduced into fire simulation and evacuation route planning. Taking the library of the Nanjing Forestry University as the study object, the spatial–temporal characteristics of the influential environmental factors of the fire are simulated, such as the meteorological elements, building structure, and building skin. The scenario zones that are relatively prone to fire are selected using an overlay analysis across the four seasons. Then, the risk threshold for evacuating personnel is analyzed in the fire zone according to international standards and firefighting criteria. Specific parameters are determined based on the analysis of the above. The growing trends for fires across the four seasons are simulated with scenario zones as the starting positions and incorporate factors such as temperature, carbon monoxide, and smoke. Lastly, a life safety assurance path (LSAP) for personnel evacuation is designed based on an indoor road network and path search algorithm. The evacuation planning result is compared with the traditional shortest-time path and shortest-distance path. Based on the study results, fire scenario zones can improve the speed and operating efficiency of spatial–temporal simulation models of fire and can also support path planning and design for emergency responses.
Highlights
Rapid global urbanization has promoted the development of three-dimensional urban spaces, both aboveground and underground
According to the principle of the realistic worst case, this study put forward methods and ideas for fire scenario construction as well as a description of the life safety assurance path via the integration of a building information modeling (BIM) and geographical information system (GIS)
The characteristic parameters of fire scenarios were acquired for the fire simulation model
Summary
Rapid global urbanization has promoted the development of three-dimensional urban spaces, both aboveground and underground. Machine learning is widely used to predict the spatial distributions of fire conditions [20] These studies simulated fire scenarios while considering different complicated factors efficiently and intelligently. Regarding evacuations in fire events, this involves a reasoning and evaluation process of evacuation response behavior This could be modeled based on risk prediction and comprehensive evaluations of evacuation conditions during building fire scenario development [21,22]. With the calculation of percentiles based on the characteristics of environmental factors, the scenarios with a high fire incidence can be selected as priority zones for fire monitoring and prevention; that is to say, if the scenarios are within the safety standards, the level of fire risk is very low and the building can be regarded as being in a safely protected state. Fire scenarios were selected in different seasons and the parameters of fire scenarios were obtained as inputs for the fire simulation model, allowing consistent and reproducible calculations
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