Phase Transitions in Collective Damage of Civil Structures under Natural Hazards

2026-02-18

AI Summary

This study addresses the poorly understood mechanisms of systemic structural damage in urban systems under natural hazards, particularly the collective damage behavior and phase-transition characteristics. By modeling building ensemble damage as a phase transition in statistical physics, the work employs a random-field Ising model, mapping hazard intensity, structural heterogeneity, and modeling uncertainty to external field, disorder strength, and temperature parameters, respectively. It reveals for the first time that urban damage exhibits critical phenomena akin to first-order phase transitions and Griffiths phases. The study proposes a novel paradigm for urban risk assessment grounded in phase transition theory and demonstrates that conventional engineering modeling approaches can induce spurious shifts between synchronized and highly volatile system states, leading to up to 50% bias in risk metrics under moderate earthquakes—equivalent to several-fold differences in estimated repair costs.

Technology Category

• Reasoning under Uncertainty: Uncertainty Representations
• Multiagent Systems: Multiagent Systems under Uncertainty
• Game Theory and Economic Paradigms: Cooperative Game Theory

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

The fate of cities under natural hazards depends not only on hazard intensity but also on the coupling of structural damage, a collective process that remains poorly understood. Here we show that urban structural damage exhibits phase-transition phenomena. As hazard intensity increases, the system can shift abruptly from a largely safe to a largely damaged state, analogous to a first-order phase transition in statistical physics. Higher diversity in the building portfolio smooths this transition, but multiscale damage clustering traps the system in an extended critical-like regime (analogous to a Griffiths phase), suppressing the emergence of a more predictable disordered (Gaussian) phase. These phenomenological patterns are characterized by a random-field Ising model, with the external field, disorder strength, and temperature interpreted as the effective hazard demand, structural diversity, and modeling uncertainty, respectively. Applying this framework to real urban inventories reveals that widely used engineering modeling practices can shift urban damage patterns between synchronized and volatile regimes, systematically biasing exceedance-based risk metrics by up to 50% under moderate earthquakes ($M_w \approx 5.5$--$6.0$), equivalent to a several-fold gap in repair costs. This phase-aware description turns the collective behavior of civil infrastructure damage into actionable diagnostics for urban risk assessment and planning.

Problem

• phase transition
• collective damage
• urban risk assessment
• structural diversity
• natural hazards

Innovation

• phase transition
• collective damage
• random-field Ising model
• urban risk assessment
• Griffiths phase