Predicting The Carbonated Concrete Depth Based On Artificial Neural Network And Probability Statistcs

Carbonization is one of the main factors, which cause durability damage to reinforced concrete structure. The aim of the present paper is the development of models to predict the carbonation of concrete structures.Taking into account more influencing factors in this paper, the theoretical of max-carbonization depth is proposed. The max-carbonization of concrete structure is analyzed through adaptive probability statistics method, resonance theory networks, back propagation (BP) networks, which make the best of the one method.It is concluded that a satisfactory result can be acquired by adopting all that methods.