TOWARDS A NEW VISION OF CIVIL ENGINEERING: DIGITAL INNOVATION APPLICATIONS FOR THE STRUCTURAL HEALTH MANAGEMENT OF EXISTING BRIDGE PORTFOLIOS

Bridges are one of the most critical components of road networks and their safety and preservation represent pivotal topics for management companies and scientific community. Bridges are usually subjected during their life to different phenomena provoking a continuous increment of vulnerability, such as aging, environmental aggressive conditions, natural hazards, which can result in the worst-case scenario in the occurrence of structural collapses. Taking as reference the Italian case, after the collapse of the Polcevera Viaduct, the Italian Ministry of Transportation proposed a multi-level safety evaluation procedure to apply on the entire national existing bridge stock, with the aim to provide a methodology for assessing critical cases to act on with risk mitigation interventions. For this scope, several phases should be processed, starting from the collection of the original documentation, passing for the performance of periodic onsite surveys to evaluate defects and degradation signs, up to the definition of a risk class that account for different hazard sources. To carry out the above phases, several problems arise, such as the unavailability of documentation for the older structures, the time- and cost-consuming phase of onsite inspections, the lack of objectivity in the visual definition of defects, the high demand for qualified personnel. To limit the above issues, traditional techniques could be supported by the possibilities provided from the world of digital innovation, whose goal is to develop new and reliable tools to support road management companies in safeguarding the heritage infrastructural asset. This paper addresses these topics, firstly proposing a panoramic about the multi-level approaches proposed by the Italian government and after by reporting the recent developments and new methodologies for assessing the health state of existing bridge portfolios. The use of costeffective techniques, such as artificial intelligence, satellite data, and automated analytical models are explored, in order to assess bridge health state towards service conditions and to provide new means to exploit for purpose of risk assessment and priorization.