Resumen
Carbonation of concrete can lead to corrosion, one of the most frequent damage processes of reinforced concrete structures. Climate change is accelerating carbonation of concrete structures, so there is an urgent need to focus more attention on this issue because it is the only way to avoid high repair costs and even catastrophic collapses of bridges. Carbonation decreases the alkalinity of the concrete and, thus, depassivates the passive layer of steel reinforcement, so it corrodes easily. When structural damage due to reinforcement corrosion becomes visible, deterioration is at a very late stage, and it may be too late to take any preventive or protection countermeasures.
Traditionally, the assessment of carbonation depth is usually performed by a semi-destructive test consisting in spraying a coloured indicator (Phenolphthalein) on a core sample extracted from the structure. When the structure is large, this test must be reproduced many times if an assessment of the variability of carbonation depth is required. In this case, the extraction of multiple samples may be technically and economically unfeasible.
At present there is no research or development in the state of the art at national or international level that has been able to develop a technology capable of quantifying the depth of carbonation and predicting its evolution accurately in real time as part of an overall system that also can introduce the effect of this type of deterioration into the assessment of the overall health and stability of the structure and the estimation of the bridge service life.
This interdisciplinary proposal called CAREC intends to overcome this existing market need through the development and demonstration in operational environment (TRL7) of a system prototype of an innovative solution consisting of several modules, including an innovative multi-sensor unit coupled to advanced data processing based on artificial neural networks to accurately determine the depth of carbonation from continuous registers from the bridge surface, the development of a probabilistic approach for the prediction of the evolution of carbonation, and also a specific algorithm for coupling these developments to existing vibration-based technology for structural heath diagnosis of bridges.
