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Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino , Turin , Italy
Major infrastructure failures rarely originate from a single defect, but emerge when deterioration, unfavorable load paths, limited redundancy, increasing operational demand, and incomplete knowledge interact. This paper synthesizes forensic and life-cycle evidence from two collapses: the 2018 Polcevera Viaduct in Genoa and the 2021 Champlain Towers South in Surfside, Florida. High-fidelity simulations reproduced the transition from local damage to large-displacement collapse. For Viaduct, progressive degradation analyses identified the prestressed-concrete stay system as the failure-critical subsystem. For Champlain Towers South, scenario analyses showed that localized deterioration and pool-deck system failure could overload perimeter columns, initiating progressive collapse. The paper proposes a predictive maintenance framework combining forensic digital twins, probabilistic deterioration models, structural-health information, Bayesian network risk updating, and resilience-based intervention optimization. Ultimately, collapse prevention requires explicit modeling of how local damage changes load paths and redundancy. Sustainable maintenance should prioritize interventions based on time-dependent failure probability, propagation potential, recovery consequences.
progressive collapse, Applied Element Method, structural robustness, corrosion-fatigue, digital twin, predictive maintenance, resilience, life-cycle assessment
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