Bridges are exposed to high environmental actions, which could affect their structural capacities. Additionally, many existing concrete bridges were not designed for current traffic demands. This means that structural verifications of current standards are often not verified, putting structural integrity at risk. Data-informed structural-assessment methodologies are essential to ensure structural safety. Structural health monitoring aims to detect damage by monitoring the structural response over time. This approach generates large datasets over the years that renders data processing and interpretation challenging. Moreover, only the relative variation of the structural behavior is usually monitored, meaning that initial structural deficiencies cannot be seen. On the opposite, structural performance monitoring (SPM) aims to evaluate current bridge conditions using a data-informed framework. This study proposes a new methodology for SPM based on distributed fiber-optic datasets during static load tests for concrete girder bridges. The datasets provide information to understand both global and local structural behavior, such as load distribution between girders, support conditions, impacts on secondary elements, and extrapolate displacements. Applied to the Ferpècle Bridge, a prestressed concrete structure in Switzerland, built in 1958 and strengthened with ultra-high-performance fiber-reinforced cementitious composite in 2023, distributed fiber-optic sensor with a low spatial resolution (strain measurements every 2.6 mm) reveals detailed information on three-dimensional girder responses, support conditions, and load distribution and enables accurate data-driven deflection predictions. The methodology provides new insights into structural behavior, allowing for more refined structural safety assessments.
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