This paper presents the results and interpretations of static and dynamic tests that were executed on a newly built cable-stayed steel-concrete composite bridge during the final proof testing. A brief description of the structure, the testing methodology, and the used instrumentation are presented. Then, the test results are widely discussed and interpreted in order to evaluate the bridge performance during the proof test and also to understand the usefulness of each performed test in a proof test framework. All the collected experimental data are also compared to the numerical ones that were obtained through a refined finite element model, in order to check the behavior of the structure. The outcomes of the present work can offer references for the proof testing and monitoring of cable-stayed bridges.

Many transportation infrastructures all around the world are facing new challenges in terms of ageing and loss of performance. The infrastructural asset managers are required to perform scrupulous control of the health condition of the infrastructures over time and to execute the required maintenance works. In this context, digital twin models of the infrastructures should have a key role to simplify and speed up the procedures for proper maintenance. This paper discusses the advantages of developing digital twin models for the management of infrastructures, with a focus on bridges. In particular, the role of dynamic tests performed on bridges for the development of digital twin models is addressed, paying attention to test procedures and requirements. Issues such as the quality of instrumentation, the numerosity, and layout of sensors, and the acquisition and post-processing procedures are addressed through applications to two real bridge case studies. Both infrastructures are multi-span pre-stressed RC bridges that were dynamically tested after the restoration and seismic upgrading works. Results of ambient vibration tests and operational modal analyses are described, providing an idea of dynamic test requirements, as well as their use within the framework of the digital twin model creation.

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