Document Type : Article
Faculty of Civil Engineering, Semnan University, Semnan, Iran
The application of fiber-reinforced polymer bars is rapidly rising in concrete structures because of corrosion resistance and high tensile strength. By contrast, concrete structures reinforced with FRP bars illustrate less ductility and brittle failure without warning than reinforced concrete structures with conventional steel bars. Hybrid concrete structures with the combination of FRP and steel bars can simultaneously increase strength and ductility. This paper aims to estimate the effective moment of inertia in hybrid concrete beams by using ANFIS and Artificial Neural networks. A new equation has been proposed for hybrid beams with attention to the importance of calculating the effective moment of inertia in concrete beams. The proposed equation has been considered the effect of elastic modulus and hybrid reinforcement ratio on this parameter for hybrid reinforced concrete beams having GFRP and AFRP bars. This equation has been presented based on the neural networks and experimental data conducted by other researchers on the simple beams to calculate the effective moment of inertia for hybrid RC beams. The result shows that both soft computing models are highly precise compared to experimental data.