CIMNE Coffee Talk: "Probabilistic traffic load assessment of prestressed girder bridges considering corrosion evolution" by Alessandro Nettis

Recently, in Italy, many catastrophic events have involved bridges and viaducts in transportation networks, with significant losses of human lives and disruption of functionality. A large number of these structures are simply supported, girder-type, prestressed concrete bridges with more than 50 years of service life and today material degradation and functional obsolescence problems are emerging. The present study is focused on the structural assessment of different typologies belonging to this bridge class considering traffic loads. The entire workflow is carried out through an automated procedure in programming language. Geometric and material random variables are assumed to simulate intra-class variability. Many realizations are generated for each typology using statistical sampling techniques. Each realization is subjected to an incremental traffic load model (TLM) proposed by the current Italian building code and a simplified traffic load analysis is carried out to get the structural response. The evolution of degradation over time is simulated considering incremental critical corrosion scenarios for post-tensioned tendons. Results compare traffic demand with structural capacity and are presented through fragility curve construction, which represents an efficient tool for risk mitigation strategies. Looking at the variations in fragility over time can be of great interest with a view to prioritization in large-scale assessment of the analysed bridge class.

Alessandro Nettis holds a Bachelor's degree in Building Engineering from Polytechnic University of Bari (Italy), awarded in 2018. He later earned his Master's degree in Civil Engineering from the same university in 2021, particularly, in the specific field of Structural Engineering. Since 2021, Alessandro has been pursuing his Ph.D. as a candidate in Bari, and is currently spending a visiting period in UPC in Barcelona of three months, to complete his PhD program.

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