Bridge infrastructure has great economic, social and cultural value. Nevertheless, many of the infrastructural assets are in poor condition as has been recently evidenced by the collapse of several bridges. The objective of this systematic review is to collect and synthesise state-of-the-art knowledge and information about how bridge information modelling, finite elements, and bridge health monitoring are combined and used in the creation of digital twins (DT) of bridges, and how these models could generate damage scenarios to be used by anomaly detection algorithms for damage detection on bridges, especially in those bridges with cultural heritage. A total of 76 relevant studies from 2017 up to 2022 are included in this review. The synthesis results show a general consensus towards the future adoption of DT for bridge design, management and operation among the scientific community and bridge practitioners. The main gaps identified are related to the lack of software interoperability, the required improvement of the performance of anomaly-detection algorithms and the approach definition to be adopted for the integration of DT at the macro scale. Other potential developments are related to the implementation of Industry 5.0 concepts and ideas within DT frameworks.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 101066739.