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Prediction of Concrete Cubic Compressive Strength Using ANN Based Size Effect Model

Q.W. Yang1, S.G. Du1,2

Department of Civil Engineering, Shaoxing University, Shaoxing, 312000, P.R. China
Corresponding author. E-mail:; Tel: +86-575-88326229; Fax: +86-575-88341503

Computers, Materials & Continua 2015, 47(3), 217-236.


Size effect is a major issue in concrete structures and occurs in concrete in any loading conditions. In this study, size effect on concrete cubic compressive strength is modeled with a back-propagation neural network. The main advantage in using an artificial neural network (ANN) technique is that the network is built directly from experimental data without any simplifying assumptions via the self-organizing capabilities of the neural network. The proposed ANN model is verified by using 27 experimental data sets collected from the literature. For the large specimens, a modified ANN is developed in the paper to further improve the forecast accuracy. The results demonstrate that the ANN-based size effect model has a strong potential to predict the cubic compressive strength of concrete


Cite This Article

Q. . Yang and S. . Du, "Prediction of concrete cubic compressive strength using ann based size effect model," Computers, Materials & Continua, vol. 47, no.3, pp. 217–236, 2015.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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