Abordagens resilientes para pontes metálicas através de estratégias verdes e digitais inclusivas

Climate change and environmental degradation pose an existential threat to Europe and the rest of the World. To overcome these challenges, the EU aims to be climate neutral by 2050, which means an economy with net-zero greenhouse gas emissions. Iron and steel have been the most polluting commodity material produced on Earth in 2023. Large-scale structures are responsible for approximately half of the total demand for steel and iron, accounting for about 8% of global final energy demand and 7% of CO2 emissions from the energy sector. The demand for metal structural elements is expected to increase continuously until 2050, however, at the same time, the metal industry must cut 50% of its CO2 emissions by 2050, compared to 2019, to meet the net-zero requirements. Thus, giving a second or third life to metal structures is essential. Around 38% of structural damage in metallic bridges occurs due to fatigue, with the aggravating factor of being a structural phenomenon unknown until some decades ago, which leads to a large number of existing structures designed without addressing this process of structural degradation. Due to economic and environmental reasons, many metallic railway bridges see their operating time extended, leading to the accumulation of fatigue damage that can be significant and responsible for putting the safety of these structures at risk. Reliable fatigue analysis is then mandatory in this context. Due to time and cost considerations, as well as constraints on test equipment, the fatigue assessment of large-scale structures is often derived from the notch properties of standardized samples tested on a small scale. Also, normative design approaches usually predict fatigue life from the average results of the most heavily loaded points on the component, plus safety factors that account for scatter bands, size effects, stress field uncertainties, and different environments. However, this approach mainly leads to conservative predictions. Thus, achieving the transformation between the fatigue properties of small-scale samples to the structural strength of engineered components through multiscale modelling, loading and environment effects, and advanced probabilistic analysis, has emerged as an increasingly urgent task in fatigue assessment to make the structures resilient and sustainable. AI-assisted statistical methods and multiscale modelling must be used to overcome this problem and establish practical solutions to reliably analyze fatigue, with these advances prepared for integration into digital twin models. Given these context and goals, the Green4Bridges project is intended to fill these gaps by building innovative multiscale methodologies for fatigue damage assessment applied to metallic railway bridges, considering size effect, various loading and environment conditions. Experimental and industrial investigation of smooth and notched components of current, additively manufactured and “green” steels, where are included hybrid steel/CFRP specimens, will be considered. The methodologies to be proposed (products with high TRL) are expected to rely on AI-assisted tools for accurate prediction and optimal service life extension of resilient and sustainable metallic railway bridges, contributing to “green” and “digital” maintenance and strengthening through sustainable repair, remanufacture, and reuse, offering beneficial effects with significant social and economic impact.