Large-scale Public Building Fire Evacuation Environmental Risks Measurement And Navigation Paths Optimization

We are living in a marvelous world. Thousands of years of human society development created abuandence of substantial civilization and spiritual civilization. And we are living in an unpeaceful world. Numerous of natural disasters, technological accidents, public security emergencies and increasing terrorist attacks bring huge lost and take away tens of thousands of precious lives every year. Public security problems and emergency managment have been generally regarded serious by both governments and scholars.Buildings are symbols of human civilization, and they are also the majority space for modern activities. Compared with normal buildings, large-scale public buildings are characterized by complex structure, dense of population and wealth concentration. So emergencies happen in large scale-public undoubtedly buildings broad and seriously economical, environmental, and social influence. Fire accidents are much more common compared with other types of public security events, and they are the typical and majority dangerous emergencies happened in large-scale public buildings. And human lives are much more precious than any other treasures and wealth. How to help occupants safely and quickly evacuate from the complex large-scacle public building fire environment is the main content of this research.Building fire is a dynamic ruinous process, which threats the evacuees so much with its environmental risks caused by fire propagation. In such changeable and dangerous condition, it would be challenge for all occupants to chose a safe and quick way to escape out.In this paper, large-scale public building fir dynamic environment and evacuees'interaction performance has been analysed first. In chapter two, general building fire features and interaction performance of active and passive building fire defence systems in large-scale public buildings has been expatiated. By building fire evacuation safety analysis, the majority types of building fire environmental risks (heat, toxic gas, smoke, and structure collapse) have been summarized with Fractional Effective Dose models expression. Evacuees'psychology analysis and interaction performance understanding in building fire environment provides necessary theoretical basis for path choice and evacuation navigation study.In order to objectively and accurately evaluate environmental risks caused by the dynamic ruinous process of building fire propagation, relationships and associations among types of risks should be confirmed. Spatial cluster algorithm has been modeled based on spatial data mining theories in chapter three to fulfil building fire environmental risks mining function of large-scale public building fire navigation intelligence navigation system: IENS Fire Guide.Exploratory Spatial Data Analysis (ESDA) technology has been employed in chapter four to discover hidden relationships among types of risks and associations between risks and evacuees dynamic flow. Univariate spatial risks independence evaluation model and bivariate risks association evaluation model has been proposed to estimate relativities of those relations and associations. In chapter four, large-scale public building evacuation origin-determination (O-D) path environmental risks evaluation has been also proposed to calculate escape probability P and time cost T of each section on the O-D paths.In chapter five, optional minimal cost network optimization technology has been employed to model up an escape probability based shortest time cost network optimization models to find out the most reliable and fast way to escape out. These models can not only be able to provide optimal scheme for individual evacuation, but also could provide n-level dynamic evacuation optimal strategies for group evacuation.To realized large-scale public building fire evacuation navigation, chapter six illustrates how to build up an intelligent space and evacuation navigation system for large-scale public building fire safe and quick evacuation. Finally, a fire scenario case study has been proposed to validate intelligent large-scale public building fire evacuation navigation system IENS Fire Guide use.