Resilience-Based Performance Metrics for Urban Infrastructure Using Structural Health Monitoring and Digital Twins: A Case Study of Tehran

Urban infrastructure systems are increasingly exposed to diverse hazards and long-term stressors that challenge not only their structural integrity but also their ability to maintain functionality and recover after disruption. While structural health monitoring and digital twin technologies have enhanced condition assessment and performance prediction, most existing applications remain focused on damage or risk metrics rather than resilience-oriented performance. This study proposes a resilience-based performance assessment framework that integrates structural health monitoring data with digital twin models to quantify infrastructure resilience in a dynamic and data-informed manner. The framework defines resilience metrics that capture functional degradation, recovery capacity, and post-event performance evolution, moving beyond static condition indicators. Structural health monitoring provides real-time evidence of performance changes, while digital twins enable interpretation and projection of resilience trajectories under different disturbance scenarios. The proposed framework is demonstrated through a case study of representative urban infrastructure assets in Tehran. The results show that resilience-based metrics reveal performance vulnerabilities and recovery limitations that are not apparent from conventional condition-based assessment. By embedding resilience explicitly within digital twin-supported monitoring, the framework provides actionable insight for proactive planning, maintenance prioritization, and resilience-oriented urban infrastructure management.

کلیدواژه ها:

Infrastructure resilience ، Performance metrics ، Structural health monitoring ، Digital twin ، Urban infrastructure ، Recovery assessment ، Case study of Tehran