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The aim of this paper is parametrically analyze the main factors that influence on the progress of concrete carbonation front. Therefore, a numerical model was developed using Artificial Neural Networks (ANNs), considering the Multi-Layer Perceptron class, designed in a C++ objectoriented program. The software was fed by experimental degradation data available in the current literature. The results obtained in the parametric analysis, besides adding knowledge to the building pathology area, reinforce concepts already known in the literature, demonstrating the efficiency of ANNs in the investigation of concrete carbonation.

Análise paramétrica da carbonatação em estruturas de concreto armado via Redes Neurais Artificiais