پديد آورندگان :
Rashad A. M. نويسنده , Farag N. O. نويسنده , Hodhod O. نويسنده , Razik M. M. نويسنده
چكيده لاتين :
An artificial neural network-based model is developed to predict the loss in capacity of reinforced concrete columns subjected to elevated temperature. A series .of RC column models have been tested. The process of increasing the temperature is performed while the
model columns carrying the service loads, thus simulating the actual condition taking place during real fire event. Different column sections; and aggregate, plaster and admixture types are used. To study the effect of these factors on the residual strength. Results of experimental model tests are then analyzed, clustered and used to train a specially designed
artificial neural network (ANN) to be capable of predicting reduced concrete strength. ANN estimations, when compared to model test results, showed very good agreement. Such observation indicates that ANN could be effectively used to accurately predict strength reduction due to exposed to elevated temperaturel.
