Increased maturity level of digital twins for bridges

Project data 

Short description

Digital twins for infrastructure are currently normally used to represent their actual condition. This makes it possible to perform diagnostic analyses on the structures. However, in order to predict the future condition of the structure and enable predictive maintenance, digital twins must advance to the next maturity level through forecasting. This requires existing forecasting models to be further developed, combined, or analyzed in interaction with each other in order to model complex damage mechanisms.

DTwinPro is further developing physical, mechanical, data-based, and hybrid prediction models for assessing the durability and load-bearing capacity of bridges. The necessary measurement data will be obtained from the “openBridgeLAB” demonstration structure of the IDA-KI research project and supplemented with existing datasets. The development of the various prediction models and their integration into the digital twin enable, for the first time, a comprehensive condition prediction within a detailed structural analysis.

The goal of the subproject at TU Dresden is to develop hybrid prediction models that, by incorporating physical knowledge and data-driven approaches, enable realistic predictions of the fatigue behavior of reinforced concrete structural elements and the corrosion of the reinforcement. This approach takes also into account the influence of combined long-term effects such as creep and shrinkage and the uncertainty of the measurement data. The reliability of the approach will be validated by conducting durability and fatigue tests. The hybrid prediction models will be integrated into the digital twin of the demonstration structure.