Predicting the 28 Days Compressive Strength of Concrete Using Artificial Neural Network

Faezehossadat Khademi*, Sayed Mohammadmehdi Jamal**
* Research Scholar, Department of Civil Engineering and Structural Engineering, Illinois Institute of Technology, Chicago, IL, USA.
** Post Graduate, Department of Civil Engineering, University of Hormozgan, Bandar Abbas, Iran.
Periodicity:March - May'2016
DOI : https://doi.org/10.26634/jce.6.2.5936

Abstract

Predicting the compressive strength of concrete has always been a difficulty, since the concrete is sensitive to its mixture components, methods of mixing, compaction, curing conditions, etc. Scientists have proposed different methods for predicting the compressive strength of concrete. Some of these methods have been successful, however, some others were not suitable enough to predict the compressive strength of concrete. The aim of this study is to evaluate the capability of Artificial Neural Network Model (ANN) in predicting the 28 days compressive strength of concrete. Therefore, considering the specific concrete characteristics as input variables, Artificial Neural Network Model is constructed and the compressive strength of concrete is predicted. Results show that ANN is a suitable model to predict the 28 days compressive strength of concrete.

Keywords

Concrete, Artificial Neural Network (ANN), 28 days Compressive Strength.

How to Cite this Article?

Khademi,F., and Jamal,S,M. (2016). Predicting the 28 Days Compressive Strength of Concrete Using Artificial Neural Network. i-manager’s Journal on Civil Engineering, 6(2), 1-7. https://doi.org/10.26634/jce.6.2.5936

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