Abstract
Despite extensive in-depth research into high calcium fly ash geopolymer concretes and a number of proposed methods to calculate the mix proportions, no universally applicable method to determine the mix proportions has been developed. This paper uses an artificial neural network (ANN) machine learning toolbox in a MATLAB programming environment together with a Bayesian regularization algorithm, the Levenberg-Marquardt algorithm and a scaled conjugate gradient algorithm to attain a specified target compressive strength at 28 days. The relationship between the four key parameters, namely water/solid ratio, alkaline activator/binder ratio, Na2SiO3/NaOH ratio and NaOH molarity, and the compressive strength of geopolymer concrete is determined. The geopolymer concrete mix proportions based on the ANN algorithm model and contour plots developed were experimentally validated. Thus, the proposed method can be used to determine mix designs for high calcium fly ash geopolymer concrete in the range 25–45 MPa at 28 days. In addition, the design equations developed using the statistical regression model provide an insight to predict tensile strength and elastic modulus for a given compressive strength.
Highlights
Concrete is the most widely utilised construction material in the world
Experimental observations were in good agreement with the predicted and actual compressive strength for high calcium fly ash geopolymer concrete indicating the reliability of the mix design procedure described in this paper
The algorithm for the predictive model for high calcium fly ash geopolymer concrete mix design was developed using artificial neural networks in order to determine the relationship between the four key parameters identified, namely water/solid ratio, alkaline activator/binder ratio, Na2 SiO3 /NaOH ratio and NaOH molarity, and the
Summary
Concrete is the most widely utilised construction material in the world. It is essential in the urbanisation of society in order to improve human living standards [1]. The manufacture of one ton of cement can generate 0.6 to 1.0 ton of CO2 depending on the manufacturing method employed [4,5,6], and is responsible for the 5−9%. Of global CO2 emission [7,8,9,10]. Many researchers have been exploring alternative sustainable cementitious binders that can reduce the dependence on Portland cement (PC) in construction [11,12,13]. Fly ash geopolymer concrete is a promising alternative that can reduce CO2 emissions by
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