Forecasting bridge damage within a predictive Structural Reliability-based DSS

Nowadays there is urgent need for expeditious and efficient approaches to assess the structural reliability of widespread aging bridge stocks. As such, a shift towards predictive maintenance measures is required. This paper addresses such pressing necessity for efficient methods to assess the structural state of aging bridges, centring its research question on developing a Decision Support System (DSS) that integrates an innovative reliability model with Markov Chain projections to prioritize bridge interventions. The proposed DSS effectively forecasts structural risks and computes a Priority Index to guide maintenance decisions. This tool empowers infrastructure managers with timely insights, enhancing bridge safety and optimizing resource allocation. The study's practical example underscores the DSS's applicability, demonstrating its capacity to streamline decision-making in real-world scenarios. By providing a sophisticated yet accessible approach to structural reliability assessment, this research lays the groundwork for future enhancements, including the incorporation of additional risk factors and refined calibration methods.

The studies presented here were supported by Fondazione CARITRO Cassa di Risparmio di Trento e Rovereto (grant number 2021.0224), MIUR PON RI 2014-2020 Program (Project MITIGO, ARS01_00964), the Agreement between the High Council of Public Works (CSLLPP) and the ReLUIS Consortium implementing Ministerial Decree 578/2020 and Ministerial Decree 240/2022, and the Agreement between the Italian Department of Civil Protection (DPC) and the ReLUIS Consortium. The contents of this paper represent the authors' ideas and do not necessarily correspond to the official opinion and policies of CSLLPP and DPC.

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Postprint (published version)