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《Sichuan Building Science》 2014-01
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Study on the carbonation depth model and simulation of concrete

GAO Panxiang;YU Junqi;DONG Zhenping;LUO Daming;School of Information and Control Engineering,Xi'an University of Architecture and Technology;School of Civil Engineering ,Xi'an University of Architecture and Technology;  
The PSO-BP neural network is applied to establish the model about each factor and the length of the partial carbonation zone which was trained by MATLAB simulation software. Gradually improving the value of the various factors that affect the length of the part carbonation zone,the error and standard deviation of actual output and desired output of the network samples will be minimized. The verisimilitude,feasibility and the healthiness of this model are validated by experiments. The results show that the model can predict the length of the partial carbonation zone of the reinforced concrete,which offers scientific guidance to durability design,assessment of concrete structures and life prediction.
【Fund】: 陕西省“13115”科技创新工程重大科技专项(2010ZDKG-55)
【CateGory Index】: TU528
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