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Optimization and Performance Evaluation of Multi-Component Binder-Based Mortars Using Particle Packing Techniques
Vanga Renuka1, Sarella Venkateswara Rao1, Tezeswi Tadepalli1
1Department of Civil Engineering, National Institute of Technology Warangal, Warangal 506004, Telangana, India.
Abstract:
The use of a multi-component binder (MCB), consisting of Ordinary Portland Cement (OPC) combined with one or more supplementary cementitious materials (SCMs), has gained prominence for enhancing sustainability and improving the performance of cementitious systems. This study provides an integrated approach to optimize both binder composition and aggregate gradation through advanced mixture design and particle packing techniques. The MCB system consists of OPC partially replaced with SCMs such as fly ash (FA), Ground Granulated Blast Furnace Slag (GGBFS), metakaolin (MK), and silica fume (SF), with particle sizes ranging from micron to sub-micron scale. The D-optimal mixture design (DOD) method is used to determine the optimal material proportions by evaluating the relation between binder composition and wet packing density measured through the wet packing method (WPM). To further enhance packing efficiency, the Modified Toufar Model (MTM) is employed to optimize fine aggregate gradation. The maximum packing density is considered the primary criterion for identifying the optimal mix design, as it reflects the minimum void ratio and the most efficient particle size distribution. The optimized mortar mixes are evaluated for mechanical strength, pozzolanic reactivity, capillary water sorptivity, and drying shrinkage. Results indicate that the optimized MCB and optimized fine aggregate gradation improve the packing density and pozzolanic activity, significantly enhancing strength and durability performance. The incorporation of SCMs offers an effective strategy to improve performance while mitigating carbon emissions. Compared with C100, CFGMS-based systems achieved energy reductions of 35-40% and CO2 emission reductions of 34-48%.
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