Applied mixture optimization techniques for paste design of bonded roller-compacted fibre reinforced polymer modified concrete (BRCFRPMC) overlays

The overall composite performance of concrete is generally contingent on achieving the right proportion of blend. The use of mixture experiments provides a flexible, easy, and quick way of optimizing multi-component materials of this nature. This paper describes the use of optimization techniques within the concept of material mixture experiments for proportioning and designing the paste (P) component of a bonded roller compacted fibre reinforced polymer modified concrete. By constraining the range of variability of the paste constituents, a feasible design space was created with 13 experimental points treated based on the required structural and elastic properties of the overlay. The optimum consistency-time for full consolidation and composite behaviour with the substrate ordinary Portland cement concrete (OPCC) was established between 34.1 and 34.9 s, while the resulting apparent maximum density achieves between 97.1 and 98.0 % of the theoretical air-free density. The tensile and shear interfacial tests performed on the optimum mixture overlay also exhibited good bonding capability with the substrate OPCC. The combined effects of curing age and surface texture on bonding were also underlined

Prediction model for hardened state properties of silica fume and fly ash based seawater concrete incorporating silicomanganese slag

Growing concrete consumption has gradually depleted conventional resources. This research incorporates silicomanganese (SiMn) slag, marine sand and seawater as alternative concreting materials. The use of SiMn slag to replace limestone as coarse aggregate enhances sustainability, though reducing strength and durability of concrete. This research aims to enhance the SiMn slag concrete by incorporating silica fume (SF) and fly ash (FA). The interaction of SF and FA on strength, durability and workability of concrete is investigated by statistically evaluating the experimental result. In this regard, the polynomial function prediction model is developed using the Response Surface Method (RSM) for the optimization of SF and FA contents. Analysis of variance (ANOVA) using p-value at significance level of 0.05 showed that the models were statistically significant and had marginal residual errors. All models had high fitness with R2 value ranging from 0.853 to 0.999. Adequate precision of models was above 4, indicating that the models had a low prediction error and were fit for optimization. Optimization indicated that a combination of 11.5% SF and 16.3% FA produced concrete that met the optimization criteria. Experimental validation showed that the highest prediction error was 3.4% for compressive strength, 3.2% for tensile strength, 4.9% for sorptivity and 18% for chloride permeability. The optimized concrete exhibited compact microstructure with good bonding between aggregate and cement paste. By using the established linear equation with SiMn slag concrete, the models also predicted the compressive strength of limestone concrete containing SF and FA with an error of between 0.9% and 5.4%