In a pilot project carried out with DNIT, PhDsoft applied the Web Digital Twin to structural integrity management for an in-service road bridge. The work brought together information from four complementary sources in a single digital environment, linking evidence to the structure model and its history to support engineering assessment.

Three-dimensional model of a road bridge in the Web Digital Twin environment.
Digital model used as a reference to organize the pilot information.
Three-dimensional model of a road bridge in the Web Digital Twin environment.

The challenge of bringing different evidence together

Assessing a bridge involves information produced by different methods, at different times and scales. The pilot aimed to bring this evidence together in the context of the same asset and make its combined interpretation useful for integrity management.

Satellite
InSAR monitoring histories integrated through SAW (Satellite Advanced Warning) to follow displacement trends over time.
GPR
Measurements incorporated at selected points to demonstrate the integration of information about the interior of concrete elements.
Visual inspections
Photographs collected by an operator-controlled drone in the field and subsequently incorporated into the Web Digital Twin.
Structural sensors
Data from accelerometers and strain gauges linked to the instrumented regions for consultation and analysis of vibration and strain.
SAW interface showing a satellite view of the bridge, with monitored sections highlighted on the map.
Pilot project bridge displayed in SAW — Satellite Advanced Warning.
SAW interface showing a satellite view of the bridge, with monitored sections highlighted on the map.

Access SAW — Satellite Advanced Warning

From monitoring the bridge to examining each element

The Web Digital Twin connected the asset view to local inspection and instrumentation evidence. This integration across scales made it possible to consult the history and relate complementary information in the 4D digital model, which includes the time dimension.

Photographs remained linked to inspection records, while measurements and monitoring data were organized in the context of the structure. The team gained a common information base for interpreting the data and following its evolution.

Inspection photograph linked to the bridge digital model, with a representation of the capture position.
Photograph collected in the field by drone and linked to the digital model after the flight.
Inspection photograph linked to the bridge digital model, with a representation of the capture position.

Configurable criteria to prioritize actions

The different evidence sources were related to a common risk assessment through criteria configured within the platform. For the data types covered by the pilot, this adaptation used configuration features already available in the Web Digital Twin.

Using these criteria, the solution demonstrated the automatic prescription of actions, such as directing inspections, increasing monitoring or requesting further assessments. The recommendations support the engineering team in setting priorities.

In the pilot, the rules and actions were configured for demonstration purposes, showing how the solution can be adapted to each organization’s management strategies.

Accelerometer and strain gauge positions identified on the bridge digital model.
Instrumentation located on the model to contextualize vibration and strain data.
Accelerometer and strain gauge positions identified on the bridge digital model.
Acceleration charts in the time and frequency domains displayed over the bridge digital model in the Web Digital Twin.
Accelerometer data presented in the context of the digital model, with time and frequency views.
Acceleration charts in the time and frequency domains displayed over the bridge digital model in the Web Digital Twin.

Integration validated within the pilot scope

The pilot technically validated the integration of the four data sources in the Web Digital Twin and demonstrated their combined use to support risk assessment and action prescription. The result was a traceable information base connecting evidence, structural context and engineering recommendations.

The experience showed the potential of this approach to support more integrated, preventive management of bridges and other infrastructure structures. Expansion can be planned according to the available data, asset characteristics and each manager’s criteria.