Construction of a Digital Twin Environment for Bridges Aimed at Structural Health Monitoring Applications

In a society where the deterioration of infrastructure has become a pressing issue, reducing the labor required for maintenance is critically important. Within the broader context of optimal control in the physical domain—such as labor reduction—the concept of a digital twin, in which simulations are performed based on real-world information and then fed back to control the physical system, has proven highly valuable. In this study, with future applications to structural health monitoring in mind, we developed a digital twin environment that integrates the physical and digital spaces of a bridge. For an actual roadway bridge, we established a real-time measurement system in the physical space using GNSS, temperature sensors, and cameras to capture the displacement field, member-wise temperature distribution, and traffic flow. In parallel, we constructed a full-scale 3D finite element model of the same bridge in the digital space. We then designed a bidirectional operational framework that (i) maps physical measurements from the real world into the digital space and (ii) estimates real-world structural states based on simulations conducted in the digital space. Using this framework, we discuss the effectiveness of the proposed digital twin environment for structural health monitoring.