Modeling study demonstrates rapid fire spread path prediction in dense urban building clusters, enabling real-time emergency management and risk assessment.
This study addresses the critical need for accurate and efficient large-scale urban fire spread path prediction in dense urban areas by proposing a new gravitational framework-based theory. Its core innovation is the “characteristic attractive force” model, which mechanistically quantifies fire spread as a dynamic interaction between buildings, integrating factors like spacing, height, area and density effects to predict trajectories from the initially ignited building. This study adopts a GIS-based rapid prediction framework that circumvents the dependence on complex physical parameters. It utilizes high-precision spatial data and optimized algorithms to streamline prediction processes while retaining favorable prediction accuracy. Validated on two real-world clusters, the proposed approach enables effective visualization of dynamic propagation trajectories and pathway spectra that characterize the detailed propagation routes and ignition sequences. Notably, the framework achieves exceptional efficiency, completing predictions for large clusters in tens of seconds per scenario, making it suitable for real-time risk assessment. Overall, this work advances urban fire modeling with an innovative, efficient, and practical tool to support fire safety engineering and emergency management decision-making.
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Bin Sun (2026) studied this question.
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