Torsion Strength Prediction of Reinforced Concrete Beams

Ahmed Faleh Al-Bayati

doi:10.15866/irece.v14i2.22853

Torsion Strength Prediction of Reinforced Concrete Beams

Ahmed Faleh Al-Bayati^(1*)

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/irece.v14i2.22853

Abstract

This study aims to investigate the torsion strength of Reinforced Concrete (RC) beams using an Artificial Neural Network (ANN) in association with a comprehensive database consisting of the results of 232 solid and hollow beams collected from the literature. The input layer has considered the influence of concrete strength and those of the longitudinal and transverse reinforcements, while the corresponding output layer has been the torsion strength. The developed ANN model has achieved an excellent agreement with the available test results, with an R of 0.99 with testing, validating, and testing sets. The ANN model has been employed to conduct a parametric study to assess the influence of the input variables. Furthermore, the contribution and the significance of input variables have been evaluated using the Garson and connecting weight algorithms. Finally, a code-like model has been proposed to calculate the torsion strength of solid and hollow sections, which is correlated well with the test results.
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Keywords

Artificial Neural Network; Torsion; Reinforced Concrete; Garson and Connecting Weight Algorithms; Regression Analysis

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