PSI - Issue 84
Mirko Calò et al. / Procedia Structural Integrity 84 (2026) 392–400
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cannot be mistaken for the result of a numerical analysis, but overall, the set of predictions can be used to derive fragility curves within the input parameter space. Hence, the ML-taxonomy-based is designed for large-scale analysis providing a quantitative measure of fragility under different hazards, to be used for supporting transportation management authorities in the task of prioritizing bridge portfolios. Acknowledgements Andrea Dall’Asta was supported by the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for Tender No. 3138 of 16 December 2021 of the Italian Ministry of University and Research, funded by the European Union—NextGenerationEU; Project code: CN00000013, Concession Decree No. 1031 of 17 February 2022 adopted by the Italian Ministry of University and Research, CUP: H93C22000450007, Project title: National Centre for HPC, Big Data and Quantum Computing within the Project “ abrich”. The other authors acknowledge the support of Fabre - “Research Consortium for the evaluation and monitoring of bridges, viaducts, and other structures” (www.consorziofabre.it) through the project “ ABRE-ANAS 2021–2024”. The manuscript reflects only the authors’ views and opinions; neither the European Union nor the European Commission or FABRE Consortium can be considered responsible for them. References Abarca, A., Monteiro, R., O’Reilly, G.J., 2022. Exposure knowledge impact on regional seismic risk assessment of bridge portfolios. Bulletin of Earthquake Engineering 20, 7137–7159. https: doi.org 10.1007 s10518-022-01491-z. CEN, 2003. EN 1991-2: Eurocode 1: Actions on structures - Part 2: Traffic loads on bridges. CEN, 2004. EN 1992-1-1: Eurocode 2: Design of concrete structures - Part 1-1: General rules and rules for buildings. De Domenico, D., Lamberto, G., Messina, D., Recupero, A., 2023. Seismic vulnerability assessment of reinforced concrete bridge piers exposed to chloride-induced corrosion. Procedia Structural Integrity 44, 633–640. https: doi.org https: doi.org 10.1016 j.prostr.2023.01.083. Di Mucci, V.M., Cardellicchio, A., Ruggieri, S., Nettis, A., Renò, V., Uva, G., 2025. Computer vision-based seismic assessment of RC simply supported bridges characterized by corroded circular piers. Bulletin of Earthquake Engineering (2025). https: doi.org 10.1007 s10518-025 02291-x. Hambly, E.C., 1991. Bridge Deck Behaviour. CRC Press. https: doi.org 10.1201 9781482267167. Iman, R.L., Conover, J.W., 1982.A distribution-free approach to inducing rank correlation among input variables. Communications in Statistics - Simulation and Computation 11, 311–334. https: doi.org 10.1080 03610918208812265. Jacinto, L., Pipa, M., Neves, L.A.C., Santos, L.O., 2012. Probabilistic models for mechanical properties of prestressing strands. Construction Building Materials 36, 84–89. https: doi.org 10.1016 j.conbuildmat.2012.04.121. Li, Y., Sun, Z., Mangalathu, S., Li, Y., He, W., Xue, X., 2025. Machine learning-based full-life-cycle seismic response assessment for in-service bridge piers: Comprehensive analysis of interpretability and seismic fragility. Structures 80, 110050. https: doi.org 10.1016 j.istruc.2025.110050. Lundberg, S., Lee, S.-I., 2017. A Unified Approach to Interpreting Model Predictions. https: doi.org 10.48550 arXiv.1705.07874. Mangalathu, S., Heo, G., Jeon, J.S., 2018. Artificial neural network based multi-dimensional fragility development of skewed concrete bridge classes. Engineering Structures 162, 166–176. https: doi.org 10.1016 j.engstruct.2018.01.053. Meoni, A., García-Macías, E., Venanzi, I., Ubertini, ., 2025. A procedure for bridge visual inspections prioritisation in the context of preliminary risk assessment with limited information. Structure and Infrastructure Engineering 21, 394–420. https: doi.org 10.1080 15732479.2023.2210547. Miluccio, G., Losanno, D., Parisi, ., Cosenza, E., 2021. Traffic-load fragility models for prestressed concrete girder decks of existing Italian highway bridges. Engineering Structures 249, 113367. https: doi.org 10.1016 j.engstruct.2021.113367. Miluccio, G., Losanno, D., Parisi, ., Cosenza, E., 2022 ragility analysis of existing prestressed concrete bridges under traffic loads according to new Italian guidelines. Structural Concrete 24, 1053–1069. https: doi.org 10.1002 suco.202200158. MIT, 2018. Aggiornamento delle norme tecniche per le costruzioni [Italian version]. MIT, 2020. Linee guida per la classificazione e gestione del rischio, la valutazione della sicurezza ed il monitoraggio dei ponti esistenti [Italian version]. Natali, A., Cosentino A., Morelli, ., Salvatore, W., 2023. Multilevel Approach for Management of Existing Bridges: Critical Analysis and Application of the Italian Guidelines with the New Operating Instructions. Infrastructures 8, 70. https: doi.org 10.3390 infrastructures8040070. Nettis, Al., Nettis, A., Ruggieri, S., Uva, G., 2024. Corrosion-induced fragility of existing prestressed concrete girder bridges under traffic loads. Engineering Structures 314, 118302. https: doi.org 10.1016 j.engstruct.2024.118302. Pitilakis, K., ranchin, P., Khazai, B., Wenzel, H., et al., 2014. SYNER-G: Systemic Seismic Vulnerability and Risk Assessment of Complex Urban, Utility, Lifeline Systems and Critical acilities. Springer Netherlands.
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