  In April 2021 Stava bridge, a main bridge on E6 in Norway, was abruptly
closed for traffic. A structural defect had seriously compromised the bridge
structural integrity. The Norwegian Public Roads Administration (NPRA) closed
it, made a temporary solution and reopened with severe traffic restrictions.
The incident was alerted through what constitutes the bridge Digital Twin
processing data from Internet of Things sensors. The solution was crucial in
online and offline diagnostics, the case demonstrating the value of
technologies to tackle emerging dangerous situations as well as acting
preventively. A critical and rapidly developing damage was detected in time to
stop the development, but not in time to avoid the incident altogether. The
paper puts risk in a broader perspective for an organization responsible for
highway infrastructure. It positions online monitoring and Digital Twins in the
context of Risk- and Condition-Based Maintenance. The situation that arose at
Stava bridge, and how it was detected, analyzed, and diagnosed during virtual
inspection, is described. The case demonstrates how combining physics-based
methods with Machine Learning can facilitate damage detection and diagnostics.
A summary of lessons learnt, both from technical and organizational
perspectives, as well as plans of future work, is presented.
