PSI - Issue 64

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Available online at www.sciencedirect.com Structural Integrity Procedia 00 (2023) 000 – 000 Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2023) 000 – 000 ScienceDirect

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Procedia Structural Integrity 64 (2024) 2117–2124

SMAR 2024 – 7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures Vibration-based Bayesian FE-model updating of a curved approaching span of the Indiano Bridge Antonino Maria Marra a, *, Salvatore Giacomo Morano b , Bernardo Nicese b , Mario De Stefano a a Department of Architecture, University of Florence, Piazza Brunelleschi, 6, 50121 Firenze, Italy b Department of Civil and Environmental Engineering, University of Florence, Via S. Marta, 3, 50139 Firenze, Italy Abstract The development of accurate finite element (FE) models of existing bridges represents a challenging issue due to the uncertainties on boundary conditions (e.g., friction of the supports and their behavior with the traffic loads, out of plumb of piers, soil-structure interaction, etc.), material properties and damping estimations. Full-scale measurements are usually employed for updating a preliminary FE model through deterministic methods, although probabilistic approaches should be preferable due to the non-negligible uncertainties present in both modeling and measurements. This work deals with the Bayesian FE-model updating of a curved approaching span of the Indiano Bridge (Florence, Italy) through full-scale vibration tests. The case study is represented by a steel/concrete composite deck slab bridge with a span of about 25 m. A procedure based on the Bayes theorem has been developed and tested on the considered case study incorporating both model uncertainties and measurement errors. © 2024 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 SMAR 2024 Organizers SMAR 2024 – 7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures Vibration-based Bayesian FE-model updating of a curved approaching span of the Indiano Bridge Antonino Maria Marra a, *, Salvatore Giacomo Morano b , Bernardo Nicese b , Mario De Stefano a a Department of Architecture, University of Florence, Piazza Brunelleschi, 6, 50121 Firenze, Italy b Department of Civil and Environmental Engineering, University of Florence, Via S. Marta, 3, 50139 Firenze, Italy Abstract The development of accurate finite element (FE) models of existing bridges represents a challenging issue due to the uncertainties on boundary conditions (e.g., friction of the supports and their behavior with the traffic loads, out of plumb of piers, soil-structure interaction, etc.), material properties and damping estimations. Full-scale measurements are usually employed for updating a preliminary FE model through deterministic methods, although probabilistic approaches should be preferable due to the non-negligible uncertainties present in both modeling and measurements. This work deals with the Bayesian FE-model updating of a curved approaching span of the Indiano Bridge (Florence, Italy) through full-scale vibration tests. The case study is represented by a steel/concrete composite deck slab bridge with a span of about 25 m. A procedure based on the Bayes theorem has been developed and tested on the considered case study incorporating both model uncertainties and measurement errors. © 2024 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 SMAR 2024 Organizers © 2024 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 SMAR 2024 Organizers

Keywords: Bayesian FE-model updating; Ambient vibration tests; Curved beam bridge

* Corresponding author. Tel.: +39 0552756837. E-mail address: antoninomaria.marra@unifi.it * Corresponding author. Tel.: +39 0552756837. E-mail address: antoninomaria.marra@unifi.it

2452-3216 © 2024 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 SMAR 2024 Organizers 2452-3216 © 2024 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 SMAR 2024 Organizers

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