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Shear capacity assessment of steel fiber reinforced concrete beams using artificial neural network

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Abstract

Incorporating steel fibers to the concrete members enhances the shear capacity. The shear capacity of steel fiber reinforced concrete (SFRC) beams is an important issue for designing the reinforced concrete structures. Due to numerous parameters that affect the shear capacity of SFRC beams, developing an exact equation to measure the shear resistance of SFRC beams is complicated. To present a more exact equation for shear capacity assessment of SFRC beams, compare to existing formulae the artificial neural networks (ANNs) developed. A series of reliable experimental data collected from the literature. A model-based ANN method for presenting an exact empirical formula developed. The accuracy of the developed formula is verified using several criteria, and a comparison study was carried out between the experimental data and the existing equations. It is understood that the obtained formula gives the most exact result among others. A sensitivity analysis based the Garson’s algorithm was executed to identify the most efficient variables.

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Authors and Affiliations

  1. Department of Civil Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

    Yasser Sharifi & Adel Moghbeli

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  1. Yasser Sharifi
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  2. Adel Moghbeli
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Correspondence to Yasser Sharifi.

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Sharifi, Y., Moghbeli, A. Shear capacity assessment of steel fiber reinforced concrete beams using artificial neural network. Innov. Infrastruct. Solut. 6, 89 (2021). https://doi.org/10.1007/s41062-021-00457-5

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