Abstract
Generalized neural network is applied to establish the network model of steel corrosion amount after the concrete cracking due to corrosion expansion, crack width along the ribs, bar diameter, concrete compressive strength and concrete cover thickness are used as the neurons of the input layer of network, and the loss rate of steel corrosion section is used as the output layer of network. The research results show that the predicted results of generalized neural network are in good agreement with the measured data, and the precision can meet the requirement of engineering practice, which provides an effective solution for the prediction of steel corrosion amount after the concrete cracking due to corrosion expansion.
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