The evolution from reactive to proactive infrastructure management is being led by the integration of Digital Twins and Artificial Intelligence. This post explores how creating a dynamic virtual replica of a physical bridge, powered by continuous sensor data and AI models, enables unprecedented foresight into structural health. Unlike traditional methods that rely on periodic inspections, a digital twin operates in real-time, simulating responses to various stressors like traffic loads, wind, and temperature fluctuations. AI algorithms analyze this simulation data alongside historical patterns to predict fatigue points and potential failure modes years in advance. This paradigm shift allows for optimized maintenance schedules, targeted repairs, and significantly extended asset lifespans. We examine a case study where this approach identified a critical deck joint degradation on a major viaduct, enabling intervention before any service disruption occurred.
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