Artificial neural network for Shear Strength assessment of slender reinforced concrete beams without stirrup

Document Type : Original Article

Authors

1 Civil eng., Eng., Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

2 -

3 Faculty of Engineering, Vali-e-Asr University of Rafsanjan, Iran.

Abstract

In reinforced concrete beams, as the main weakness of concrete is in tension, rate of tension near support is less and it increases near the middle of span and leads to more ductility in this area. Artificial neural network has been developed as a reliable method to simulate and determine ultimate shear strength of slender concrete beams without stirrup. A numerical study was carried out to investigate shear capacity of slender reinforced concrete beams without stirrup subjected to simply support. For this purpose the effect of several parameters on shear strength of slender concrete beams without stirrup such as effective depth, shear span, compressive strength of shear reinforcement was considered. A numerical study was done in order to analyze and study results of artificial neural networks and finally an empirical formulae with suitable accuracy was obtained to determine ultimate shear capacity of slender reinforced concrete beams. Artificial neural networks and the obtained formulae were compared with several code recommendations. The results show that the model suggested by artificial neural network gives a suitable and exact formulae than other code recommendations formula.

Keywords


Volume 21, Issue 55
April 2020
Pages 54-63
  • Receive Date: 01 September 2018
  • Revise Date: 06 December 2018
  • Accept Date: 10 February 2020