Quantifying urban seismic rescue difficulty: a policy-oriented assessment methodology based on building collapse patterns

Post-earthquake rescue efficiency is crucial for urban seismic resilience. However, building collapse patterns, which critically determine rescue difficulty, remain inadequately addressed in urban disaster policies. This study proposes a policy-oriented methodology for quantifying seismic rescue difficulty in urban areas based on building collapse patterns. First, a code-compliant parametric rapid modeling algorithm was developed, integrating a hybrid simulation approach that combines the multi-degree-of-freedom (MDOF) model with the Discrete Element Method (DEM) to enable building cluster collapse simulation. Furthermore, a multi-dimensional analysis model integrating both qualitative and quantitative metrics was established to analyze collapse patterns. The reliability of this approach was validated through Wenchuan earthquake case studies. Based on this validated approach, a rescue difficulty assessment model incorporating the Survival Space Index (SSI) and the Rescue Route Complexity Index (RRCI) was developed to quantify post-earthquake rescue difficulty. Finally, a case study was conducted in Beijing's Tongzhou District that categorized collapsed buildings into four rescue difficulty levels, and corresponding rescue strategies were subsequently discussed. These findings provide valuable insights for optimizing post-earthquake rescue strategies and resource allocation, thereby enhancing urban disaster response capabilities and contributing to seismic-resilient city development.