Bio-inspired predictive models for shear strength of reinforced concrete beams having steel stirrups

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In this article, three bio-inspired predictive models are proposed with the aim of estimating the shear capacity of reinforced concrete (RC) beams having steel stirrups. For this purpose, 194 experimental tests of this type of RC beams were gathered from the literature. Then, the structures of the artificial neural network models are trained and validated using seven parameters including concrete compressive strength, width of the member, effective depth of the member, the yielding strength of transverse reinforcement, area of the reinforcement as a proportion of the beam area, the yielding strength of longitudinal reinforcement and also the transverse reinforcement ratio to determine the observed shear capacity in the experimental tests. It was concluded that the proposed mathematical frameworks could determine the shear capacity with a satisfactory level of precision in comparison with the obtained results of ACI-318.

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