Stabilization of black cotton soil subgrade using sawdust ash and lime

This present study optimizes multiadditives for the improvement of the properties of expansive soil by integrating min‐max fuzzy goal programming model, a variant of fuzzy goal programming, into Taguchi optimization method. The multiadditives, which included ordinary Portland cement (OPC), quarry dust (QD), and sawdust ash (SDA), had various levels assigned to them in the Taguchi designed experiment, and they were all added by air‐dried weight of the expansive soil. Responses that included differential free swell, California bearing ratio, and unconfined compressive strength were determined using the Taguchi designed experiment. Concurrent analysis of the data obtained from the responses was performed using the min‐max fuzzy goal programming and the optimum combinations of additives that resulted in the significant improvement of the soils were obtained at 20% SDA, 20% QD, and 8% OPC. In addition, scanning electron micrograph analysis for the expansive soil that was combined with the optimum combination of additives showed cementitious compound formation in the soil‐additives mixtures and this confirmed lucidly that min‐max fuzzy goal programming can be integrated in Taguchi method to optimize additives for the improvement of expansive soil properties.

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“…This enabled a very high value of UCS to be achieved in the present study. The result is in consonance with that obtained by Ikeagwuani et al 89 …”

Section: Resultssupporting

confidence: 93%

“…The cementitious compounds formed help to bind the soil particles through flocculation and agglomeration, thereby imparting denser aggregation to improve the microstructure of the treated soil. The result is similar to that obtained in previous studies 4,89 …”

Section: Resultssupporting

confidence: 93%

Min‐max fuzzy goal programming ‐ Taguchi model for multiple additives optimization in expansive soil improvement

Ikeagwuani

Nwonu

Onah

2020

Num Anal Meth Geomechanics

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“…The mixtures were hand mixed thoroughly to ensure homogeneous mixture. The stabilization of soil with 4%lime and 16%SDA was chosen since it has proven to give the best results for compaction, CBR, Atterberg's limits and differential free swell tests [17,18]. The ASTM D559 [1] was used in this study for assessing the wetting and drying durability of the cured samples with the exception of wire brush application.…”

Section: Methodsmentioning

confidence: 99%

Stability and durability of sawdust ash-lime stabilised black cotton soil

Obeta¹,

Ikeagwuani²,

Attama³

et al. 2019

Nig. J. Tech.

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The assessment of the durability of twelve cylindrical samples of black cotton soil, a well-known problem soil, stabilized with a combination of 4%lime and 16% sawdust ash were carried out in laboratory using the methods of [1] and that recommended by [2] and [3]. The results showed that the unconfined compressive strength of the samples under varying curing and soaking conditions ranged from 1217kPa to 265kPa while the durability indices were 59.51% and 59% respectively. Thus, the stabilizers have elevated the otherwise non-durable soil into the marginally durable zone.

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“…(2) At the junction between important and redundant eigenvectors, the influencing factors of important eigenvectors are much larger than those of redundant eigenvectors. The serial numbers at the junction can be determined by: (25) The constraint on the gap between important and redundant eigenvectors in formula (25) ensures that the influence of redundant eigenvectors on network output is less than the mean influence of all input eigenvectors. This clearly elevates the judgement accuracy of important input eigenvectors.…”

Section: Optimization Of Characteristic Parametersmentioning

confidence: 99%

“…In terms of solving differential settlement by widening subgrade, Ikeagwuani et al [25] analyzed the mechanism and effect of subgrade widening technique in reconstruction and expansion projects, highlighting the importance of mitigating and controlling differential settlement of subgrade according to pile-soil interaction, and pavement deformation mechanism.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation Model of Subgrade Stability Based on Artificial Neural Network

Yao¹,

Shi²,

Zu³

2020

IJSSE

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In special areas, the highways may suffer from such diseases as deformation, cracking, subsidence, and potholes, making highway maintenance a complex and difficult task. To obtain the law-term deformation law of the subgrade and accurately evaluate the subgrade and pavement stability, this paper establishes a subgrade stability evaluation model based on artificial neural network (ANN). Firstly, the law of unstable subgrade deformation in highways of special areas was derived by analyzing the influencing factors on subgrade stability, namely, temperature field, moisture field, and traffic load. Next, the correlations between input and output characteristic quantities were extracted, and used to construct the nonredundant mapping function between influencing factors of subgrade unstable deformation and the levels of subgrade stability. Finally, a fuzzy neural network (FNN) was constructed based on Takagi-Sugeno model, realizing the evaluation of subgrade stability. The proposed model was proved effective and accurate through experiments.

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Stabilization of black cotton soil subgrade using sawdust ash and lime

Cited by 82 publications

References 14 publications

Min‐max fuzzy goal programming ‐ Taguchi model for multiple additives optimization in expansive soil improvement

Min‐max fuzzy goal programming ‐ Taguchi model for multiple additives optimization in expansive soil improvement

Stability and durability of sawdust ash-lime stabilised black cotton soil

An Evaluation Model of Subgrade Stability Based on Artificial Neural Network

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