Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108016
Title: Optimizing phased-evacuation strategy for high-rise buildings in fire
Authors: Wang, F 
Zhang, Y 
Ding, S 
Huang, X 
Issue Date: 15-Oct-2024
Source: Journal of building engineering, 15 Oct. 2024, v. 95, 110084
Abstract: Evacuation in high-rise buildings is a critical safety issue due to multiple floors and high occupant density. Phased evacuation strategies can mitigate this challenge. This research focuses on developing optimal phased evacuation strategies to enhance occupant safety during high-rise building fires. The study demonstrates these strategies in a 25-story building, housing 2400 individuals, across various scenarios. To simulate fire and smoke development, a two-zone model is employed to analyze behavior within the building. Pedestrian evacuation scenarios are simulated using Pathfinder and a mathematical model, providing insights into individual movements and congestion during evacuation to analyze different phased evacuation strategies. Findings underscore the importance of smoke flow and pedestrian motion in optimizing phased evacuation strategies. The modeling results show that implementing the optimal strategy can lead to a 65 % reduction in staircase congestion time. This study provides a quantitative analysis of high-rise building fires, considering dynamic fire and evacuation evolution. It emphasizes the importance of phased evacuation strategies and advocates for their real-life application. This research enhances the understanding of high-rise building evacuations to improve safety measures and provides a robust framework for optimizing evacuation strategies by integrating fire modeling. This study demonstrates the effectiveness of phased evacuation and paves the way for future applications to ensure occupant safety in fire emergencies.
Keywords: Emergency management
Evacuation strategy
Fire modeling
Smoke exposure index
Tall building
Publisher: Elsevier
Journal: Journal of building engineering 
EISSN: 2352-7102
DOI: 10.1016/j.jobe.2024.110084
Appears in Collections:Journal/Magazine Article

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