Search Results for fiber-prestress

Abstract

The aim of this work is to experimentally study the influence of fiber prestress and curing temperature on the tensile and flexural properties of carbon fiber-epoxy composite. Adaptive Neuro-Fuzzy Inference System model was used to predict the effect of fiber prestress and curing temperature on the tensile strength, tensile modulus, flexural strength and flexural modulus of carbon fiber-epoxy composite. It was found that, the best membership functions for predicting the tensile strength, tensile modulus and flexural modulus are Gaussian membership functions with 4 number of membership function, and for predicting the flexural strength are generalized bell membership functions with 4 number of membership functions. From the comparison between the experimental and predicted results of carbon fiber-epoxy composite properties, it is found that the prediction results of this model show a good agreement with experimental results.