PSI - Issue 84

Alessandro Vari et al. / Procedia Structural Integrity 84 (2026) 975–982

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1. Introduction and Regulatory Framework Infrastructure asset management has undergone a critical paradigm shift in recent decades, moving from a purely reactive approach to a predictive one. This transition aims to prevent structural failures and ensure user safety, a requirement formalized by the Superior Council of Public Works (CSLLPP) in the “Guidelines for Risk Classification and Management, Safety Assessment, and Monitoring of Existing Bridges” (D.M. 578/2020 as amended). The guidelines establish a multi-level framework to maintain the "consistency of performance" for strategic assets, relying on an analytical triad of census/inspection, risk classification (Levels 1-2), and accurate assessment (Level 4). The Italian inventory of engineering structures—comprising bridges, viaducts, and overpasses built largely between the 1960s and 1970s—is characterized by advanced aging. These assets, heterogeneous in typology (R.C./P.R.C. beam decks, arch, frame, or cable-stayed schemes) and materials, exhibit widespread degradation that compromises both durability and load-bearing capacity, necessitating urgent and targeted retrofitting strategies. 2. Vulnerabilities of R.C. and P.R.C. Structures and Traditional SHM Limitations Structural typologies and static schemes inherently possess critical zones subject to stress concentrations or environmental exposure. Current maintenance practices, however, frequently reveal a dichotomy between reinforcement interventions and control systems: • Reinforcement Techniques: Engineers typically employ consolidated technologies to restore load-bearing capacity (e.g., FRP plating, steel jacketing like CAM ® System), yet these are often designed as passive elements that remain static throughout their service life. • Structural Health Monitoring (SHM): While the deployment of transducer networks (accelerometers, inclinometers, strain gauges) is increasing, these systems are often installed as add-ons to structures that have already degraded or undergone reinforcement.

(a) (b) Fig. 1. (a) Retrofitting of Beam Concrete using the CAM ® System; (b) Retrofitting of halved joints using the CAM ® System.

A significant integration gap exists in this approach. The SHM system rarely monitors the efficacy of the applied reinforcement directly, nor does the reinforcement address all global vulnerabilities. For instance, relying on instrumented bearings or global deck deformation monitoring generates complex Big Data sets. These datasets often fail to facilitate the timely identification of local decay or the triggering of effective early warnings without complex post-processing. Moreover, direct stress monitoring within reinforcement elements (e.g., post-tensioning bars or cables) remains uncommon, limiting the assessment of prestress losses over time.