BIM-driven digital risk twins for tunnel reinforcement maintenance

Maintaining the structural integrity of tunnels is crucial, yet assessing embedded reinforcements such as rock bolts remains difficult with conventional methods. This paper proposes a digital risk twin (DRT) framework to operationalize risk-based maintenance (RBM). Unlike conventional digital twins (DT) that focus on state visualization, the DRT visualizes risk as the primary output by converting rock-bolt measurements into failure-mode risk metrics with uncertainty propagation and rendering a tiered 3D risk map. The framework couples a Building Information Model (BIM) with sensor streams. Through visual programming, strain data are automatically mapped to the model and color-coded by risk which enables rapid localization and prioritization of at-risk areas. Laboratory tests on instrumented rock bolts validate the end-to-end reliability of the system. The proposed approach is expected to provide a transparent and efficient basis for RBM decisions, reducing uncertainty and minimizing risk and life cycle costs.