• Computers and Concrete
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• 제34권2호
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• pp.213-230
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• 2024

The use of waste tires and industrial wastes such as fly ash (FA) and ground granulated blast furnace slag (GGBS) in concrete is an important issue in terms of sustainability. In this study, the effect of parameters affecting the physical, mechanical and microstructural properties of FA/GGBS-based geopolymer concretes with waste rubber fiber was investigated. For this purpose, the effects of rubber fiber percentage (0.6%, 0.9%, 1.2%), binder (75FA25GGBS, 50FA50GGBS, 25FA75GGBS) and curing temperature (75 ℃, 90 ℃ and 105 ℃) were investigated. The Taguchi-Grey Relational Analysis (TGRA) method was used to obtain optimum parameter levels of rubber fiber geopolymer concrete (RFGC). The slump, fresh and hardened density, compressive strength, flexural strength, static and dynamic modulus of elasticity, ultrasonic pulse velocity (UPV) tests and scanning electron microscopy (SEM) analysis were performed on the produced concretes. The analysis of variance (ANOVA) method was used to statistically determine the effects of the parameters on the experimental results. A confirmation test was performed to test the accuracy of the optimum values found by the TGRA method. With the increase of GGBS percentage, the compressive strength of RFGC increased up to 196%. The increase in rubber fiber percentage and curing temperature adversely affected the mechanical properties of RFGC. As a result of TGRA, the optimum value was found to be A1B3C1. ANOVA results showed that the most effective parameter on the experimental results was the binder with 99% contribution percentage. It is understood from the SEM images that the optimum concrete had a denser microstructure and less capillary cracks and voids. For this study, the use of the TGRA method in multiple optimization has proven to provide very useful and reliable results. In cases where many factors are effective on its strength and durability, such as geopolymer concrete, using the TGRA method allows for finding the optimum value of the parameters by saving both time and cost.