PSI - Issue 62

Luigi Pallante et al. / Procedia Structural Integrity 62 (2024) 268–275 Pallante L. et al../ Structural Integrity Procedia 00 (2019) 000 – 000

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1. Introduction Bridges are essential components of global infrastructure, serving as critical links for mobility, transit, and the growth of national economies. Bridges age and deteriorate over time, just like any other civil infrastructure, which increases the danger to public safety. Due to these structural issues, effective methods for managing and maintaining bridges have become necessary. As a result, numerous bridge management systems (BMSs), such as the optimization and network information systems, have been developed [1, 2]. The 2018 catastrophic collapse of the Polcevera Bridge in Genoa, Italy, provided a powerful incentive for the creation of policies and procedures for bridge safety. The National Computer Archive of Public Works (AINOP) was established in the same year, and the Guidelines for Risk Classification and Management, Safety Assessment, and Monitoring of Existing Bridges were released by the Ministry of Infrastructure and Transport (MIT) two years later [3-5]. Moreover, the possession of a digital database for bridge management has become mandatory for all administrators of infrastructure, even those operating at the regional level. Most of the Bridge Management Systems (BMSs) are founded on data-driven methodologies and depend on employing a unified database (DB) that offers accurate and uniform data organization [6,7]. This DB is essential for introducing semi-automated processes and guiding managers towards the adoption of cutting-edge technologies for bridge monitoring and maintenance. Structured databases are effective tools in this industry for managing, organizing, and storing vast amounts of data pertaining to bridge upkeep, inspection, and repair. Within this framework, the paper suggests a multi-level strategy for the safety management of existing bridges as described in the guidelines published by the Italian MIT. This strategy is consistent with the integrated data-driven approach for bridge management digitalization at the regional scale. Using pre-existing techniques, a unified structured database is utilized to extract queries, and basic data for Building Information Modeling (BIM) [8-10], design, Geographic Information System (GIS) [11], cataloguing, and computations. Specifically, the data from the database is automatically accessible in the GIS, enabling the automatic creation of initial BIM models that may be enhanced with multi-source data obtained from utilizing the newest technologies. Compared to previous research, the methodology aims to enhance BIM models and GIS representation by adding data on the attention class of the entire structure and the defect level of individual structural elements of a bridge. This is achieved through an algorithm where the structured database is a key component. The first beneficiary of the study, the Lazio region in Italy, is the focus of the suggested approach's bridge assets. 2. Aim and Objective The main objective of this study is to provide a thorough approach for the safety management of current bridges, especially in the Lazio area of Italy. The study suggests a multi-level approach that is in line with the recommendations of the Italian Ministry of Infrastructure and Transport (MIT), placing a focus on infrastructure network management, risk assessment, and static and seismic concerns. The creation of parametric Building Information Modeling (BIM) models for dynamic representation, integration of MIT guidelines for attention classes, development of a structured database to track bridge characteristics, implementation of a Geographic Information System (GIS) for georeferencing and visualization of defect levels in the BIM environment are some of the specific goals. The study aims to contribute significantly to bridge management systems, offering a data-driven approach for safety enhancement and providing infrastructure managers with tools for informed decision-making in bridge maintenance and risk assessment.