| description abstract | Most biopolymers used as additives for the improvement of expansive subgrade soils are ecofriendly but highly uneconomical and unsustainable. Even the traditional additives such as cement, lime, and fly ash that are used widely for most soil improvement schemes are highly notorious for their carbon footprint. This necessitated the motivation in the present study to utilize an economical, ecofriendly and highly sustainable biopolymer, known as pregelatinized corn starch (PGCS), to improve the strength properties of an expansive subgrade soil. The PGCS was admixed with quarry dust (QD), an industrial waste additive, before blending with the expansive subgrade soil in different mix ratios generated with a 32 full factorial design experiment. The California bearing ratio (CBR) samples were subjected to 7 day curing while that of the unconfined compressive strength (UCS) were subjected to 1, 7, and 28 day curing. Shortly after the improvement of the expansive subgrade soil, the PGCS and QD were used as predictors in the development of two regression models for the two strength parameters (CBR and UCS) of the expansive subgrade soil considered in the study. Next, multiobjective salp swarm optimization algorithm (MOSSA), a bioinspired algorithm, was employed to optimize the additives in order to obtain optimal values of the strength properties of the expansive subgrade soil blended with the additives. The developed models were set as fitness functions in the slightly modified MOSSA technique. Thereafter, nondominated solutions were determined after the implementation of the optimization analysis. The results obtained from laboratory experiments and the optimization process showed that there was significant improvement in the UCS and CBR of the expansive subgrade soil. Optimal improvement in the UCS (1,326.241 kN/m2) and CBR (36.8%) were observed when an optimum mix ratio of the additives, 0.3117% PGCS and 10% QD, was blended with the expansive subgrade soil. | |
