Prediction of Mechanical Properties of Local Concrete in Compression Using Artificial Neural Networks

  • Baylasan Mohamad Al-Baath University, Homs, Syria
  • Soleman Alamoudi Assistant Professor in structural engineering department, Al-Baath University, Homs, Syria
  • Abd alrahman Issa Professor in structural engineering department, Al-Baath University, Homs, Syria
Keywords: stress- strain, modulus of elasticity, artificial neural networks

Abstract

Mechanical properties of concrete are highly dependent on the local materials used in its preparation. experiments on ready mix concrete in our region illustrate the actual behavior of concrete produced by local materials. Six standard cylinders (D=150mm, H=300mm) were casted of most ready mix concrete in central area in Syria (13 of them) covering a wide range of compressive strength . Tests were carried out using a testing machine which gives the applied force values and the corresponding displacement simultaneously until failure. The mean curves representing the (stress-strain) relationship of concrete in compression are drawn, from which the mechanical properties of each mixture were derived, such modulus of elasticity compressive strength ,  and the corresponding strain . Artificial neural networks were trained on experimental test results (using MATLAB). The laws of concrete behaviour were well assimilated by Artificial neural networks, which is possible to be used as an alternative method of available models of stress-strain relationship, by predicting the curve directly for various concrete mixtures prepared using local materials with different mixing ratios, or a complementary method through the adoption of an appropriate mathematical model and then predict its parameters ( ، ، ). ANNs proved their ability to predict mechanical properties of concrete better than linear regression equations, which promises a more accurate and comprehensive prediction.

Published
2020-03-31
How to Cite
Mohamad, B., Alamoudi, S., & Issa, A. alrahman. (2020). Prediction of Mechanical Properties of Local Concrete in Compression Using Artificial Neural Networks. Association of Arab Universities Journal of Engineering Sciences, 27(1), 105-121. Retrieved from https://jaaru.org/index.php/auisseng/article/view/369
Section
Articles