Abstract
The demand on using industrial by-products and waste materials in the construction industry has increased in recent years. This study focused on the feasibility of using Electric Arc Furnace Steel slag (EAFS) as a replacement to the natural aggregates (Limestone, LS) in both Hot Mix Asphalt (HMA) and granular base layers. Four HMAs were investigated, two mixes were prepared using proportions of the EAFS/LS of 0/100 and 100/0% of the total aggregate weight, while for the other two mixes, the coarse limestone aggregate fractions were replaced by 60 and 80% coarse EAFS aggregates. The granular base EAFS/LS blends were (0/100, 20/80, 40/60, 60/40, 80/20, and 100/0%) of the total aggregate weight. EAFS, LS aggregates and asphalt binder were first characterized in the laboratory, and then the performance of the investigated asphalt mixtures in terms of Marshall stability, loss of stability, indirect tensile strength and tensile strength ratio was evaluated. On the other hand, the granular base blends were characterized through routine tests and static and Repeated Load Triaxial (RLT) tests to evaluate the behaviour of these blends under traffic loading. RLTT results showed that as the EAFS increases, the stiffness generally increases. A new revised universal model is proposed to incorporate the EAFS effect on the resilient modulus (Mr) prediction having an excellent accuracy. The (E*) values for the investigated HMA were predicted using Witczak NCHRP 1-37A model. While, the Mr values for the investigated granular base blends were predicted by the universal model at the anticipated field stress, which were obtained by “ANSYS” Finite Element Analysis software. Moreover, the field pavement performance in terms of Asphalt Concrete (AC) rutting and fatigue cracking was predicted for different typical sections using the Quality-Related Specifications Software (QRSS). Results showed better performance for HMA mixes and unbound aggregate bases containing EAFS compared with the control section containing only natural aggregates.
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