PSI - Issue 84

Tommaso Pivetta et al. / Procedia Structural Integrity 84 (2026) 1286–1293 T. Pivetta et al. / Structural Integrity Procedia 00 (2026) 000–000

1293

8

material survey, which enabled the construction of a reliable numerical model. Subsequently, an experimental campaign involving controlled crossing of heavy vehicles under a structural health monitoring system was carried out. The vibration monitoring system enabled an accurate calibration of the numerical model through an iterative procedure acting on the elastic modulus of the structural components. Finally, the reliability of the calibrated model was assessed by performing linear dynamic analyses under the same moving-load conditions as those adopted during the experimental campaign, confirming a very good agreement and thus the effectiveness of the calibration process. The outcomes of this study provide a validated high-fidelity numerical model of the existing bridge, which may serve as a reference framework for further numerical investigations under different traffic scenarios and, eventually, for the assessment of potential damage conditions to evaluate the structural robustness and performance over time. Acknowledgements This study was carried out within the RETURN Extended Partnership and received funding from the European Union Next Generation EU (National Recovery and Resilience Plan – NPPR, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005). Acknowledgement is also made to FABRE – “Research consortium for the evaluation and monitoring of bridges, viaducts and other structures” (www.consorziofabre.it/en) within the activities of the FABRE-ANAS 2021-2024 research program. Any opinion expressed in the paper does not necessarily reflect the view of the funder. References Chen B, Starman B, Halilovič M, Berglund LA, Coppieters S. Finite Element Model Updating for Material Model Calibration: A Re view and Guide to Practice. Archives of Computational Methods in Engineering 2025;32:2035–112. https://doi.org/10.1007/s11831-024-10200-9. Frangopol DM, Asce F, Strauss A, Kim S. Bridge Reliability Assessment Based on Monitoring. Journal of Bridge Engineering 2008:258–70. https://doi.org/10.1061/ASCE1084-0702200813:3258. García-Macías E, Ruccolo A, Zanini MA, Pellegrino C, Gentile C, Ubertini F, et al. P3P: a software suite for autonomous SHM of bridge networks. J Civ Struct Health Monit 2023;13:1577–94. https://doi.org/10.1007/s13349-022-00653-6. Li H, Xia H, Soliman M, Frangopol DM. Bridge stress calculation based on the dynamic response of coupled train-bridge system. Eng Struct 2015;99:334–45. https://doi.org/10.1016/j.engstruct.2015.04.014. Mccrum DP, Obrien EJ, Khan M. Bridge Health Monitoring Using an Acceleration-Based Bridge Weigh-in-Motion System. 2018. MIDAS Information Technology Co. L. MIDAS CIVIL NX 2025. Sanayei M, Khaloo A, Gul M, Necati Catbas F. Automated finite element model updating of a scale bridge model using measured static and modal test data. Eng Struct 2015;102:66–79. https://doi.org/10.1016/j.engstruct.2015.07.029. Sekiya H, Kubota K, Miki C. Simplified Portable Bridge Weigh-in-Motion System Using Accelerometers. Journal of Bridge Engineering 2018;23. https://doi.org/10.1061/(asce)be.1943-5592.0001174. Sipple JD, Asce M, Sanayei M. Full-Scale Bridge Finite-Element Model Calibration Using Measured Frequency-Response Functions 2014. https://doi.org/10.1061/(ASCE)BE.1943. Cantero D. Moving point load approximation from bridge response signals and its application to bridge Weigh-in-Motion. Eng Struct 2021;233. https://doi.org/10.1016/j.engstruct.2021.111931.