Abstract:
Concrete generally is brittle material and having low tensile strength. These
undesirable properties have greater effect on the shear behavior of concrete. The
shear behavior, shear strength and shear failure mechanism of nonFIBER and
FIBER reinforced concrete Beams without shear reinforcement (RC and FRC
Beams) were investigated. The use of FIBER in concrete modifies shear behavior
to be more ductile and enhances shear strength by resisting formation and growth
of cracks. Shear strength is a quite complex system to be predicted and analyzed
accurately as there are several factors affecting it. And yet, there is no agreed
rational procedure to design of shear of RC and FRC Beams, although, several
empirical and theoretical models have been proposed to attempt acquiring adequate
equations with good accuracy for designing engineers.
Artificial Neural Networks (ANNs) modeling technique was used in this research
to predict shear strength of RC and FRC Beams. One ANN Model was built of
three layers feed-forward with back propagation system and consists of nine input
nodes, nine hidden layer nodes and one output node. The ANN Model was
developed by the Optimization Modeling System "Solver" in the Microsoft Office
Excel (2007) and using 177 set of actual and reliable data collected from previous
studies. The developed ANN Model gave better performance when was evaluated
and compared with: (1) current design codes equations (ACI 318-08, EC2-04,
BS8110-97 and Spanish EHE-99) and (2) The proposed empirical/theoretical
equations for shear strength of FRC Beams (Sharma-86, Narayanan and Darwish-
87, Ashour et al -92, Imam et al.-97 and Khuntia et al.- 99). The developed ANN
Model was also used to evaluate the effect of the parameters governing shear
strength of the RC and FRC Beams.
