Abstract
In this study a full factorial design (FFD) based desirability function approach (DFA) was used to the modeling of determined quality criteria of C 40/50 (C50). A FFD based DFA was also applied to determine optimal mixture proportions of C50. The mixture proportion modeled by using FFD was determined as the function of variables such as water to binder materials ratio, coarse aggregate (II) to total aggregate ratio, the percentage of superplasticizer content and fly ash amount. The properties of C50 were identified as that the slump flow and 28th day compressive strength. The model results were tested with experimental runs. The results showed that the determined regression meta-models were useful for prediction of properties of C50 with the mixture parameters. The results also showed that the FFD based DFA are effective in solving the mixture proportions optimization problem.
Highlights
The optimization of a Ready Mixed Concrete (RMC) mixture for determination of the desired quality is an important issue in the field of material and design engineering [1, 2]
The optimization and the modeling of mixture proportions of C 40/50 (C50) were performed by using a full factorial design (FFD) based desirability function approach (DFA)
RMC consists of many conflicting factors; it is critical to use a systematic methodology for determining optimal mixes and modeling quality characteristics of C50 under a set of parameters that make up the concrete
Summary
The optimization of a Ready Mixed Concrete (RMC) mixture for determination of the desired quality is an important issue in the field of material and design engineering [1, 2]. In literature several optimization and modelling methods have been proposed on investigating the optimal mixture proportions for many concrete types. For investigating the effects of parameters on concrete, design of experiment is commonly used in literature. Özbay et al [5] investigated the mix proportions of high strength self compacting concrete by using Taguchi method. Correia et al [6] assessed of the recycling potential of fresh concrete waste using a factorial design of experiments. Santilli et al [8] applied a factorial design study to determine the significant parameters of fresh concrete lateral pressure and initial rate of pressure decay. Alqadi et al [9] developed a self compacting concrete using contrast constant factorial design
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