Structural Redundancy Metrics for Progressive Collapse in High-Rise Frames

Abstract

Progressive collapse in high-rise structures represents a catastrophic failure mode wherein localized damage propagates disproportionately, leading to partial or total structural failure. As urbanization accelerates the construction of increasingly complex tall buildings, evaluating their resilience against abnormal loads has become paramount. This paper investigates the predictive capacity of structural redundancy metrics in forecasting progressive collapse probabilities using advanced reliability testing frameworks. By synthesizing topological, geometric, and load-path redundancy indicators, this study develops a comprehensive framework to quantify structural robustness without relying on computationally prohibitive nonlinear dynamic simulations for every design iteration. The research employs probabilistic reliability methods, including extensive Monte Carlo simulations, to analyze multi-story steel and reinforced concrete frames under various column-removal scenarios. The findings demonstrate a strong correlation between specific redundancy indices and structural survival rates, suggesting that optimized redundancy metrics can serve as reliable preliminary predictors for collapse resistance. The integration of these metrics into standard design protocols offers a proactive approach to mitigating disproportionate collapse, enhancing occupant safety, and establishing more resilient urban infrastructures.