PSI - Issue 84

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ScienceDirect

Procedia Structural Integrity 84 (2026) 623–629

© 2026 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Conference Keywords: Operational Modal Analysis; Bending frequencies; Regression formulas; Large-scale assessment Abstract The preservation of Italy’s infrastructural assets, particularly its bridges, represents a considerable challenge due to their aging condition and the recurring structural vulnerabilities they exhibit. In this context, continuous monitoring emerges as a valuable strategy for detecting early warning signs of damage, facilitating timely interventions, and enhancing structural risk management. This study contributes to this framework by analysing experimental data collected from a selection of reinforced concrete bridges involved in a structural health monitoring programme. An initial overview of the monitored structures is provided, followed by an examination of data acquired through ongoing monitoring, aimed at identifying key dynamic parameters and characterizing the structural behaviour of the bridges. This study analysed the natural frequencies identified through continuous monitoring system installed on bridges, with the aim of interpreting their dynamic and structural behaviour. Subsequently, it critically assesses how existing correlation relationships can be used to estimate the first two bending natural frequencies as functions of selected geometric parameters. III Fabre Conference: Existing Bridges, Viaducts, and Tunnels: Research, Innovation, and Applications Interpretation of Operational Modal Analysis results for reinforced concrete bridges Angela Diana a , Corrado Chisari a , Mattia Zizi a , Gianfranco De Matteis a * a Department of Architecture and Industrial Design, University of Campania “Luigi Vanvitelli”, via San Lorenzo, Aversa CE 81031, Italy

* Gianfranco De Matteis. E-mail address: gianfranco.dematteis@unicampania.it

2452-3216 © 2026 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Conference 10.1016/j.prostr.2026.06.080