4.7 Article

Waste tire rubber and pozzolans in concrete: A trade-off between cleaner production and mechanical properties in a greener concrete

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 238, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.117882

Keywords

Greener concrete; Cleaner product; Waste tire rubber; Pozzolans; Mechanical properties; Strength prediction

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This study presents a cleaner production of a concrete by incorporating waste rubber chips and pozzolans to make a greener concrete through partial replacement of aggregates and cement. For this purpose, aggregate was replace by 10 and 15% by graded waste rubber (RB) and cement was partially replaced by pozzolans, namely silica fume (SF) and zeolite (ZE) by 10%. Fresh and hardened properties of the concrete was investigated through slump, compressive strength and elasticity modulus. The effect of RB, SF and ZE addition on fresh properties was assessed which indicated 5% and 14.6% slump reduction for 10% and 15% rubber replacement, 4% increase due to SF addition, and 4% decrease as a result of ZE addition. The microstructure of the pozzolans was also investigated using SEM micrographs. Compressive strengths of the samples were measured at different ages of 3, 7, 28, and 42 days and compared with ACI 318 equation in order to modify the coefficients for the greener concrete. Elasticity moduli of the concrete mixes were determined according to ASTM C469. The results indicated that 10% and 15% rubber replacement led to 30% and 50% strength drop, respectively. The corresponding reduction in elastic modulus was observed as 14% and 32%. The elastic modulus was also estimated using relationships presented in different standards based on compressive strength. It was found that ACI 318 relationship underestimates the elastic modulus for which the correction factors were determined. Three different regression models namely Linear, Logarithmic, and Power were also developed in order to predict the compressive strength of greener concrete. Power regression with R-2 = 0.92 proved to be more powerful among other assessed regression models. (C) 2019 Elsevier Ltd. All rights reserved.

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