PSI - Issue 78

Domenico Cefalì et al. / Procedia Structural Integrity 78 (2026) 1358–1365

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efficiency and supports sustainable maintenance. A quality control index survey for railway bridge health monitoring uses risk analysis for prioritization, cost reduction, and maximizing information value from measurements and inspections, focusing on important elements (Lajevardi et al., 2019). Despite the benefits of BMS, many nations face challenges in identifying high-risk bridges due to data scarcity, mixed ownership, diverse management platforms, varying rating schemes, and absent risk-based assessment. Addressing these gaps is crucial for effective national policies (Chávez et al., 2024). The BHI is paramount for sustainable and safe global bridge infrastructure management, providing a standardized metric beyond subjective visual inspections, incorporating objective data from advanced sensing, analytical techniques, statistical analysis (Otake et al., 2012), and novel damage indices (Quqa et al., 2024). The integration of AI, data-driven models, BIM, PdM, and prioritization methodologies like AHP, reliability-based approaches (Dissanayake and Karunananda, 2008), and the GFI (Patjawit and Kanok-Nukulchai, 2005) enhances prediction accuracy and optimizes resource allocation. Despite data quality and standardization challenges, BHI enables effective intervention prioritization, failure prevention, cost reduction, and ensures long-term functionality and safety of critical transportation networks, making its continued development vital. 3. The Italian bridge guidelines: a retrospective evaluation The conservation, maintenance, and monitoring of bridges have gained significant global attention, especially in Italy, due to numerous aging structures and a history of catastrophic collapses (Andriulo, 2023; Principi et al., 2024). To address these issues, the Italian Ministry of Transport and Infrastructure issued comprehensive Guidelines in 2020 (Italy, 2020). These Guidelines adopt a multi-level and multi-risk approach for classifying, managing risk, assessing safety, and monitoring existing bridges (Grieco et al., 2024; Principi et al., 2024; Rossi et al., 2024). The assessment process within these Guidelines involves six levels. The initial three levels (0-2) are mandatory for all bridges, encompassing data collection from census, visual inspections, and a risk-based classification to assign a "Class of Attention" (CoA). Practical applications of these guidelines, such as on a large number of bridges in the Sicilian region, have facilitated the creation of experimental databases, aiding in the critical evaluation of their effectiveness (Rossi et al., 2023). The primary goal of these Guidelines is to standardize bridge safety management across Italy, thereby unifying previously disparate regional approaches. This new framework centers on determining an "Overall Attention Class" for each bridge. This class is derived from the combination of four partial attention classes, which cover structural, foundational, seismic, landslide, and hydraulic risks, offering a holistic risk assessment (Capogna et al., 2023; Cutrone et al., 2023; De Matteis et al., 2022; Di Fluri et al., 2024; Furinghetti et al., 2023; Hamidpour et al., 2024; Lipari et al., 2024; Miano et al., 2023; Perilli et al., 2024; Renzi et al., 2023; Salciarini et al., 2024; Salvatore et al., 2024; Stacul et al., 2024). 3.1. Criticalities Despite their comprehensive nature, the Italian Guidelines for bridge management exhibit several criticalities. A significant challenge lies in their qualitative approach to structural assessment, combining hazard, vulnerability, and exposure classes (Lipari et al., 2024). This contrasts with more quantitative methods, such as those in the UK, leading to potential limitations in precision and consistency of risk classification (Hamidpour et al., 2024; Lipari et al., 2024). In another study, a conceptual analysis of the Guidelines was carried out to perform statistical evaluations of the partial Attention Classes and the overall Attention Class in recurring bridge cases. The analysis highlighted a tendency of the regulatory framework to assign classifications within the higher risk classes (Ciminelli et al., 2024). Specific hazards, like landslides and hydraulic risks, pose particular difficulties. The Guidelines require landslide hazard evaluation during field surveys, but the extent of areas to be investigated is often unclear (Perilli et al., 2024). Practical applications have revealed gaps and uncertainties in data collection workflows, leading to inconsistencies (Perilli et al., 2024). Furthermore, the Italian Landslide Hazard Map may not provide sufficient detail for comprehensive assessment at all levels, necessitating more geological and geotechnical data (Cutrone et al., 2023; Stacul et al., 2024). Similarly, for hydraulic risk, missing project documentation can lead to an overestimation of risk, highlighting the need for procedural refinements to ensure homogeneous assessments (De Matteis et al., 2022; Di Fluri et al., 2024). The data acquisition and elaboration for the initial assessment levels (0-2) can be cumbersome (Rapicavoli et al., 2024). Moreover, the current method for calculating the Class of Attention regarding structural defects does not