Measurement-based condition assessment, load identification, and service life prediction of prestressed concrete bridges with low shear reinforcement ratios using the 2D-FOS-methode

• Applicant: Professor Dr.-Ing. Martin Claßen
• Subject Area: Structural Engineering, Building Informatics and Construction Operation
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 501771082

Germany’s infrastructure is aging and subject to continuously increasing traffic loads. Since the rapid construction of thousands of new bridges poses an immense challenge, the preservation of existing structures is of crucial importance. A significant portion of older bridges is constructed from prestressed concrete, designed for combined shear, torsion, and bending loads based on the principal stress criteria. These structures exhibit high prestressing levels but only minimal shear reinforcement. When deficiencies are identified during recalculations or visual inspections, these bridges are often downgraded to a lower class or taken out of service. Previous studies and the current state of the art indicate that such structures retain substantial load-bearing reserves, even after the occurrence of fatigue-induced macro-cracks. To safely utilize these reserves for extended bridge operation, the project focuses on developing an autonomous method for continuous monitoring and evaluation of strain and damage states, including micro- and macro-cracking, in highly shear-stressed structural sections. During the first funding phase, the 2D-FOS measurement concept was developed. In the second phase, the focus shifts from data acquisition and processing to the practical application of the data. The proposed method aims to identify the time-variant state of the structure, analyze traffic loads, predict the remaining service life, and visualize all relevant information within a digital environment. To achieve these objectives, the second funding phase will implement a coordinated work program consisting of four interrelated work packages. The complexity of this task necessitates the close integration of expertise in measurement technology for generating the time-variant condition status, efficient data organization, mathematical and graphical processing in a digital representation, and advanced knowledge of physical-engineering-based load identification and service life prediction. The coordinated development of innovative measurement, evaluation, and prediction methods, combined with their integration into a digital twin, will provide high-density information for predictive and intelligent structural management, significantly extending the service life of infrastructure. To test the 2D-FOS system and the developed methods under real-world conditions, the system will be installed on the Nibelungen Bridge in Worms and the openLAB research bridge. The project aligns seamlessly with the research areas outlined for the second funding phase of SPP2388 and makes a methodological contribution to mitigating the current infrastructure crisis.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2388: Hundred plus - Extending the Lifetime of Complex Engineering Structures through Intelligent Digitalization
• Co-Investigator: Professor Dr.-Ing. Josef Hegger