Evaluation of the mechanical performance of concrete containing calcium carbide residue and nano silica using response surface methodology

Calcium carbide residue (CCR) is generated from acetylene gas production, and it is highly alkaline and contains a very high amount of calcium. Nano silica (NS), on the other hand, is mostly used in combination with other pozzolanic materials in concrete to ignite the reactivity of the material and to improve the properties of the concrete. This study investigated the effect of CCR incorporated in concrete mixtures to partially replace cement content at 0 to 30% (interval of 7.5%). NS was used as an additive by weight of binder at levels 0 to 4% in increment of 1%. Thus, response surface methodology (RSM) was employed to investigate the effects of CCR and NS on the properties of the concrete, including compressive strength, flexural strength, splitting tensile strength, modulus of elasticity (MoE), and water absorption. The RSM was used for model development predicted concrete's properties and carried out mixture multi-objective optimization by maximizing strengths, MoE, and minimizing water absorption. The results showed that using up to 15% CCR improved the strengths, MoE, and water absorption of the concrete. Adding up to 3% NS further enhanced the strengths, MoE, and water absorption significantly. The developed models for predicting the properties of the concrete using RSM were highly efficient with high degree of correlation. The optimization solutions indicated that the best optimum or best mix combination based on maximum strengths and MoE with minimum water absorption was achieved by replacing 10.6% cement with CCR and adding 1.95% NS by the weight of cementitious materials.

Automated summary

This study investigated the effects of incorporating calcium carbide residue (CCR) and nano silica (NS) on the properties of concrete. The results showed that using a high proportion of CCR and a moderate amount of NS significantly improved the strength, modulus of elasticity, and water absorption of the concrete. The developed models for predicting concrete properties using response surface methodology were highly efficient and correlated well.