Statistical modeling of strength characteristics of industrial slag waste–based soilcrete

This study presents a statistical-experimental approach to optimise the proportions of Portland cement and ground granulated blast furnace slag (GGBS) for improving the strength characteristics of soft montmorillonitic clay (SMC). Response Surface Methodology (RSM) was employed to investigate the effects of three variables, cement content (10%–30% by dry soil), GGBS replacement ratio (0%–30% of cement), and curing duration (7–28 days), on unconfined compressive strength. A central composite design was adopted to minimise experimental runs while maintaining prediction accuracy. The developed quadratic model exhibited excellent correlation with experimental data (R2 = 0.977; adj. R2 = 0.969), and analysis of variance confirmed the statistical significance of all main, interaction, and quadratic effects. Microstructural investigations using Fourier transform infrared spectroscopy, X-ray diffraction, and X-ray diffraction revealed the formation of hydration products including calcium silicate hydrate, calcium aluminate silicate hydrate, and portlandite (Ca(OH)2), corroborating the strength gain. This study highlights that the incorporation of GGBS as a supplementary cementitious material in deep cement mixing columns is a technically sound and environmentally sustainable solution for ground improvement projects.