Development of a Dynamical Egress Behavioural Model under Building Fire Emergency

Download files
Access & Terms of Use
open access
Copyright: Cao, Ruifeng
Abstract
Building fire accidents, as a continuing menace to the society, not only incur enormous property damage but also pose significant threats to human lives. More recently, driven by the rapid population growth, an increasing number of large-capacity buildings are being built to meet the growing residence demands in many major cities globally, such as Sydney, Hong Kong, London, etc. These modern buildings usually have complex architectural layouts, high-density occupancy settings, which are often filled with a variety of flammable materials and items (i.e., electrical devices, flammable cladding panels etc.). For such reasons, in case of fire accidents, occupants of these buildings are likely to suffer from an extended evacuation time. Moreover, in some extreme cases, occupants may have to escape through a smoke-filled environment. Thus, having well-planned evacuation strategies and fire safety systems in place is critical for upholding life safety. Over the last few decades, due to the rapid development in computing power and modelling techniques, various numerical simulation models have been developed and applied to investigate the building evacuation dynamics under fire emergencies. Most of these numerical models can provide a series of estimations regarding building evacuation performance, such as predicting building evacuation time, visualising evacuation dynamics, identifying high-density areas within the building etc. Nevertheless, the behavioural variations of evacuees are usually overlooked in a significant proportion of such simulations. Noticeably, evacuees frequently adjust their egress behaviours based on their internal psychological state (i.e., the variation of stress) and external stimulus from their surrounding environments (i.e., dynamical fire effluents, such as high-temperature smoke). Evidence suggests that evacuees are likely to shift from a low-stress state to a high-stress state and increase their moving speed when escaping from a high-temperature and smoke-filled environment. Besides, competitive behaviours can even be triggered under certain extremely stressful conditions, which can cause clogging at exits or even stampede accidents. Without considering such behavioural aspects of evacuees, the predicted evacuation performance might be misinterpreted based on unreliable results; thereby, misleading building fire safety designs and emergency precautions. Therefore, to achieve a more realistic simulation of building fire evacuation processes, this research aims to advance in modelling of human dynamical behaviour responses of each evacuee and integrating it into building fire evacuation analysis. A dynamical egress behaviour-based evacuation model that considering the evacuee’s competitive/cooperative egress movements and their psychological stress variation is developed. Furthermore, a fire hazard-integrated evacuation simulation framework is established by coupling with the fire dynamics simulator (i.e., FDS). By means of tracking dynamical interactions between evacuees and the evolutionary fire dynamics within the building space, evacuees’ local fire risks and stress levels under the impacts of locally encountered fire hazards (i.e., radiation, temperature, toxic gas, and visibility) can be effectively quantified. In this study, the developed simulation tool can provide a further in-depth building fire safety assessment. Thus, it contributes to performance-based fire safety engineering in designs and real applications, including reducing budgets and risks of participating in evacuation drills, supporting emergency evacuation strategy planning, mitigating fire risks by identifying risk-prone areas associated with building fire circumstances (e.g., putting preventative measures in place beforehand to intervene or mitigate safety risks, such as mass panic, stampede, stress evoked behaviours).
Persistent link to this record
Link to Publisher Version
Additional Link
Creator(s)
Editor(s)
Translator(s)
Curator(s)
Designer(s)
Arranger(s)
Composer(s)
Recordist(s)
Conference Proceedings Editor(s)
Other Contributor(s)
Corporate/Industry Contributor(s)
Publication Year
2022
Resource Type
Thesis
Degree Type
PhD Doctorate
UNSW Faculty
Files
download public version.pdf 11.44 MB Adobe Portable Document Format
Related dataset(s)