Computers and Concrete

  • 제24권5호
  • /
  • Pages.469-488
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  • 2019
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  • 1598-8198(pISSN)
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  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Predicting the shear strength of reinforced concrete beams using Artificial Neural Networks

  • Asteris, Panagiotis G. (Computational Mechanics Laboratory, School of Pedagogical and Technological Education) ;
  • Armaghani, Danial J. (Institute of Research and Development, Duy Tan University) ;
  • Hatzigeorgiou, George D. (School of Science and Technology, Hellenic Open University) ;
  • Karayannis, Chris G. (Department of Civil Engineering, Democritus University of Thrace) ;
  • Pilakoutas, Kypros (Department of Civil and Structural Engineering, University of Sheffield)
  • 투고 : 2019.08.23
  • 심사 : 2019.10.22
  • 발행 : 2019.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, surrogate approaches, such as artificial neural network models, have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the predicted values with the corresponding experimental ones, as well as with available formulas from previous research studies or code provisions highlight the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, for the first time, the (quantitative) values of weights for the proposed neural network model, are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.

키워드

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