Expansive subgrade soils undergo significant swell–shrink cycles due to moisture imbalance (ingress and egress), resulting in low strength and high compressibility. This study examines the effects of freeze–thaw (F-T) cycles on fiber-reinforced expansive soils treated with an alkaline activator stabilizer (AAS). The AAS was prepared using slag and sugarcane bagasse ash (SB) with sodium silicate and sodium hydroxide at a 0.4 water-to-solid ratio. Geotechnical and microstructural properties of AAS-treated (slag/SB: 0/100 and 25/75) soils reinforced with polypropylene (PLF) and glass fibers at dosages of 0.5% and 1% were compared against those of cement-stabilized soils under cyclic temperature conditions. Results demonstrated that the fiber–AAS soil achieved a 22% improvement in geomechanical strength than cement-stabilized mixtures. Moreover, PLF reinforcement effectively minimized tensile cracking after six F-T cycles by enhancing interfacial bonding. Furthermore, an artificial intelligence model using the random forest algorithm was also developed to predict AAS strength under F-T cycles. Validated with experimental data, the model demonstrated high accuracy, reducing the need for extensive testing. This study underscores the potential of fiber-reinforced AAS and AI modeling in improving expansive soil performance under F-T conditions.
Syed et al. (Tue,) studied this question.