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ANN-based Shear Capacity of Steel Fiber-Reinforced Concrete Beams Without Stirrups
  • Miguel Abambres ,
  • Lantsoght E
Miguel Abambres
Num3ros, Num3ros

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Lantsoght E
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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%.
12 Mar 2024Submitted to TechRxiv
19 Mar 2024Published in TechRxiv
11 Oct 2019Published in Fibers volume 7 issue 10 on pages 88. 10.3390/fib7100088