Predicting the Compressive Strength of Concrete Containing Metakaolin With Different Properties Using ANN
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The advantages of using Metakaolin (MK) as a supplementary cementitious material have led this highly active pozzolan to be widely used in the concrete industry. Awareness of the parameters affecting the mechanical properties of concrete containing MK, determining the effectiveness of each parameter, and also the ability to estimate the compressive strength of concrete containing MK can pave the way for further implementation of this type of concrete. In the present paper, ANN models for estimating the compressive strength of concretes containing MK with various properties have been developed based on the available experimental results. The results of sensitivity analysis indicated that the compressive strength of concrete containing MK is mostly influenced by its specific surface area, and SiO2/Al2O3 ratio. The predicted results are in good agreement with the experimental ones. An empirical equation is proposed to determine the 28-day compressive strength of concrete containing MK.
Concrete; Metakaolin; Mechanical property; Neural network; Empirical equation
Construction Engineering and Management | Materials Science and Engineering
Moradi, M. J.,
Ramezanianpour, A. M.
Predicting the Compressive Strength of Concrete Containing Metakaolin With Different Properties Using ANN.