%0 Journal Article
%T Artificial neural network model for performance evaluation of RC rectangular beams with externally bonded glass fibre reinforced polymer reinforcement
%A N. Pannirselvam
%A V. Nagaradjane
%A K. Chandramouli
%A M. Ravindrakrishna
%J Journal of Engineering and Applied Sciences
%D 2010
%I Asian Research Publishing Network (ARPN)
%X The effect of glass fibre reinforced polymer laminates on the performance of reinforced concrete rectangular beams having different internal steel reinforcement ratios was investigated. The parameters of investigation included yield load, ultimate load, yield deflection, ultimate deflection, maximum crack width, deflection ductility and energy ductility. Artificial Neural Network model was generated to predict the performance characteristics taking percentage of steel reinforcement, thickness of glass fibre reinforced polymer and the type of fibre used in glass fibre reinforced polymer as parameters.
%K model
%K reinforced concrete beams
%K glass fibre reinforced polymer
%K performance evaluation
%K ANN
%K ductility
%K strength.
%U http://www.arpnjournals.com/jeas/research_papers/rp_2010/jeas_0310_317.pdf