A recent article published in Scientific Reports presented an overview of new construction procedures with enhanced robustness and accuracy of stress control in active anchorage and short prestressing units for long-span bridges, specifically targeting probable risks.
Extensometers in the passive reinforcement of the Tajo Bridge arch: (a) extensometer in the reinforcement of the stay piers; (b) extensometer in the reinforcement of the half-arches. Image Credit: https://www.nature.com/articles/s41598-024-61873-y
Background
Cable stays or suspensions are commonly employed in designing long-span bridges. The durability of these solutions is conditioned by fatigue and/or corrosion damage due to dynamic loads such as traffic and wind. This influence of fatigue and corrosion and resulting damage to cables in service are mostly assessed by monitoring axial stress.
Various direct and indirect methods and devices have been developed to measure bridge cables' stress. Direct stress measurement devices include load cells, fiber optic Bragg grating sensors, and elasto-magnetic strain sensors. Alternatively, vibrating wire methods are generally employed for indirect and quick stress assessment in bridge cables.
Auxiliary structural elements used during bridge construction such as temporary stay-cable towers also encounter high instantaneous prestressing losses. Thus, it is crucial to monitor their prestressing stress and the time variation of this stress to ensure that the element is performing as desired.
Methods
The researchers presented a review of the systems currently used for stress monitoring control in bridge stays and prestressing units during the construction phase of Tajo Bridge, a unique high-speed infrastructure in Spain designed and constructed between 2012 and 2016.
The Tajo Bridge has been cautiously planned to meet high-speed, efficiency, and safety standards through advanced engineering and offer modern aesthetics. To experimentally investigate the structural response of the bridge’s central arch span, the researchers designed a structural health monitoring system (SHMS) comprising several devices and systems.
They include a management and unification system with the project (M&USP) containing project databases provided by the design and construction teams of the bridge and a sensor system (SS) comprising 114 sensors installed at different locations on the bridge. For example, load cells in the suspension cables and anchorages of the stay-cable towers and train gauges in the half-arch reinforcements.
A data acquisition and processing system (DA&PS) for different sensor systems was included in the SHMS. Additionally, a data management and processing system (DM&PS) was designed and programmed. It was used for data transmission, visualization, and storage and for establishing early warning systems.
Finally, a structural safety and assessment system (SS&AS) was developed. It consisted of all bodies involved in the bridge construction including technical and management teams. This subsystem helped monitor the instrumentation data and compare them with the project's theoretical data. The comparison results updated the M&USP databases and fed the SHMS.
The proposed SHMS was employed for monitoring the deformation encountered by the reinforcement of the half-arches, stay piers, and stay towers. Furthermore, the acceleration of the northern half-arch, thermal gradient in different structural sections, and wind incident on the structure were monitored.
Results and Discussion
Based on the Tajo Bridge experience, the researchers revisited the new monitoring systems for stress control. The load cells for active anchors must be able to accurately characterize the total axial force transmitted by the bridge stay or prestressing unit and provide a robust solution for extreme environments, shocks, and impacts.
In addition, they must provide direct measurement without the need for signal integrators. Accordingly, the designed load cell consisted of a metal ring that allows the bridge stay or prestressing unit to pass through it. It can be positioned between the anchor and distribution plates on the structure.
Three devices were simultaneously installed to monitor the bridge stays, which include load cells on active anchors, unidirectional strain gauges on a strand composing the stays, and piezoelectric accelerometers on the stays. These helped detect various structural phenomena during the construction including stress variations in the bridge stay, stress variations derived from the concreting of successive segments, analysis of the force variation due to stressing of different cables, and detection of force variations from load readjustment operations in the suspension stay cables.
Furthermore, a new synchronized multi-strain gauge load cell network was proposed in each stay tower for monitoring short prestressing units. It ensured the correct prestressing and accurate quantification of the losses experienced by the prestressed connection.
Conclusion
Overall, this study focused on optimizing stress management for bridge stays, suspension cables, and short prestressing units by emphasizing a unified parameter: stress. Advanced load cells were designed and installed in active anchorages for robust and precise stress control. Moreover, the implementation of a novel synchronized multi-strain gauge load cell network for short prestressing units was crucial in situations where prestressing losses could attain significant magnitudes.
To validate these advancements, the researchers presented practical experience and results obtained from applying these methodologies to monitor the structural response during the construction of the Tajo Bridge using the cable-stayed cantilever technique. These methods can help quantify the prestressing losses, which exceeded 10% in the Tajo Bridge, and plan new stressing operations in such critical structures.
Journal Reference
Gaute-Alonso, A., Garcia-Sanchez, D., Ramos-Gutierrez, Ó. R., & Ntertimanis, V. (2024). Enhancing stress measurements accuracy control in the construction of long-span bridges. Scientific Reports, 14(1), 10961. https://doi.org/10.1038/s41598-024-61873-y, https://www.nature.com/articles/s41598-024-61873-y
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