Estimating fracture energy of concrete (GF) using adaptive neuro-fuzzy inference system (ANFIS)

Fracture energy of concrete is one of the basic parameters of fracture that present the concrete cracking resistance and also is one of the important characteristics in considering design of concrete engineering structures. In recent years، fracture parameters of concrete have been investigated using various experimental methods; and the role of these parameters in design of structures is an important issue. In this paper، a fracture model based adaptive neuro-fuzzy inference system (ANFIS) has been implicated to estimate the fracture parameter of concrete GF (specific fracture energy i. e. the area under the stress- displacement curve) using a three-point bending (3PB) specimen. The results showed that the adaptive neuro-fuzzy inference system and its proper training can be used in order to create an optimal model for each series of data and can be applied to evaluate the adaptive neuro-fuzzy inference system reliability as an effective tool to estimate the fracture energy of concrete.