Light-weight Self-Compacting Concrete (LWSCC) might be the answer to the increasing construction requirements of slenderer and more heavily reinforced structural elements. However there are limited studies to prove its ability in real construction projects. In conjunction with the traditional methods, artificial intelligent based modeling methods have been applied to simulate the non-linear and complex behavior of concrete in the recent years. Twenty one laboratory experimental investigations on the mechanical properties of LWSCC; published in recent 12 years have been analyzed in this study. The collected information is used to investigate the relationship between compressive strength, elasticity modulus and splitting tensile strength in LWSCC. Analytically proposed model in ANFIS is verified by multi factor linear regression analysis. Comparing the estimated results, ANFIS analysis gives more compatible results and is preferred to estimate the properties of LWSCC.

This study investigates the effects of Nano SiO ₂ (NS) and Silica fume (SF) on the mechanical properties and durability of Portland cement concrete. On specimens with varying NS and SF concentrations, compressive strength, flexural strength, abrasion resistance, elastic modulus, and chloride ion penetration were all tested. All specimens were subjected to the proposed method/technique cured at the ages of 3, 7, 28, and 60 days. NS particles were added to cement concrete at various replacements of 0, 0.5, 1.0, 1.5, and 2.0% by the mass of the binder. The water/binder ratio has remained at 0.37 for all mixes. Then, for cement-concrete were prepared 45 MPa (C45) with NS and SF. The specimens confirm the new method effectiveness evaluation were prepared under two different categories: (1) Portland cement replacement with NS of 0%, 0.5%, 1.0%, 1.5%, and 2.0%, by weight for adhesives; (2) Portland cement replacement with NS of 0.5%, 1.0% and each NS content in combination with SF of 5%, 10%, and 15%, respectively, by weight for adhesives. The results indicated that the abrasion resistance and Chloride ion penetration of concrete containing NS and SF are improved. Finally, an analytical model for forecasting the Elastic modulus, flexural strength, and compressive strength of cement concrete was established from obtained data.