ANN-based Shear Capacity of Steel Fiber-Reinforced Concrete Beams Without Stirrups
24 Pages Posted: 2 Oct 2019 Last revised: 18 Nov 2019
Date Written: September 20, 2019
Comparing experimental results on the shear capacity of steel fiber-reinforced concrete (SFRC) beams without mild steel stirrups, to the ones predicted by current design equations and other available formulations, still shows significant differences. In this paper we propose the use of artificial intelligence to estimate the shear capacity of these members. A database of 430 test results reported in the literature is used to develop an artificial neural network-based formula that predicts the shear capacity of SFRC beams without shear reinforcement. The proposed model yields maximum and mean relative errors of 0.0% for the 430 data points, which represents a better prediction (mean Vtest / VANN = 1.00 with a coefficient of variation of 1× 10-15) than the existing expressions, where the best model yields a mean value of Vtest / Vpred = 1.01 and a coefficient of variation of 27%.
Keywords: Experimental Data, Artificial Neural Networks, Design Formula, Concrete Beams, Steel Fiber-Reinforced Concrete, Shear Capacity
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