Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age

Year 2016, , 76 - 79, 01.11.2016

Ilker Ali Ozkan , Mustafa Altın

https://doi.org/10.18201/ijisae.263977

Abstract

Compressive strength of concrete is one of the most important elements
for an existing building and a new structure to be built. While obtaining the
desired compressive strength of concrete with an appropriate mix and curing
conditions for a new structure, with non-destructive testing methods for an
existing structure or by taking core samples the concrete compressive strength
are determined. One of the most important factors that affects the concrete
compressive strength is age of concrete. In this study, it is attempted to
estimate compressive strength, modelling Artificial Neural Networks (ANN) and
using different mixture ratios and compressive strength of concrete samples at
different ages. In accordance with obtained data’s in the estimation of
concrete compressive strength, ANN could be used safely.

Keywords

Concrete strength, Prediction, Artificial neural networks