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    Bioinspired Algorithm for Performance Evaluation of Biopolymerized Expansive Subgrade Soil Blended with Industrial Waste Additive

    Source: International Journal of Geomechanics:;2024:;Volume ( 024 ):;issue: 012::page 04024298-1
    Author:
    Chijioke Christopher Ikeagwuani
    ,
    Chibuzo Joseph Nnonyelu
    ,
    Idorenyin Ndarake Usanga
    DOI: 10.1061/IJGNAI.GMENG-9397
    Publisher: American Society of Civil Engineers
    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.
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      Bioinspired Algorithm for Performance Evaluation of Biopolymerized Expansive Subgrade Soil Blended with Industrial Waste Additive

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4304175
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    • International Journal of Geomechanics

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    contributor authorChijioke Christopher Ikeagwuani
    contributor authorChibuzo Joseph Nnonyelu
    contributor authorIdorenyin Ndarake Usanga
    date accessioned2025-04-20T10:11:22Z
    date available2025-04-20T10:11:22Z
    date copyright10/11/2024 12:00:00 AM
    date issued2024
    identifier otherIJGNAI.GMENG-9397.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4304175
    description abstractMost 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.
    publisherAmerican Society of Civil Engineers
    titleBioinspired Algorithm for Performance Evaluation of Biopolymerized Expansive Subgrade Soil Blended with Industrial Waste Additive
    typeJournal Article
    journal volume24
    journal issue12
    journal titleInternational Journal of Geomechanics
    identifier doi10.1061/IJGNAI.GMENG-9397
    journal fristpage04024298-1
    journal lastpage04024298-15
    page15
    treeInternational Journal of Geomechanics:;2024:;Volume ( 024 ):;issue: 012
    contenttypeFulltext
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