Significance of Measurement Data for the Probabilistic Assessment of New and Existing Infrastructure on the Example of the Pilot Project Bridge Schwindegg

Bridge maintenance is an essential task to establish a strong and efficient infrastructure. Due to the even more increasing shortage of qualified personnel in the future the development of concepts for a semi-automated bridge inspection is necessary. Especially for the large number of small and medium span bridges in the municipal road network, there is often no specialized personnel available for the tasks of structural inspection and maintenance. An individual on-site condition assessment in defined and regular time intervals is the current state of the art. This assessment includes a close inspection of the bridge but usually not an end-to-end documentation or continuous measurement since its time of construction. Measurement data contains important information about the actions and resistance of the structures. This information gives a proposition about the structure’s condition. Digital twins can be a concept for the use of this information. While full probabilistic methods deliver exact information about the reliability of the examined structure, they require representative input data. Measurement data is best suited to provide this input, otherwise the stochastic parameters from literature may not necessarily match for the specific structure. In the future, the acquisition of measurement data can be performed from digital twins or the actual structure. This article presents the concept of digital twins for medium span concrete bridges. The large amount of collected data over the entire lifespan of the structure will significantly enhance knowledge and calculation models. Especially in the construction of new bridge structures, where the installation of the measurement technology can be performed simultaneously with the actual construction, the advancement of digital twins provides many advantages for the quality of a reliability assessment.