Use of Bagasse Ash and Coconut Fiber in Stabilization of Black Cotton Soil

Singh, Nisha; Kalita, Ajanta

doi:10.1007/978-981-33-4590-4_33

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…The tests carried out are liquid limit, plastic limit, free swelling index, and UCS. Maximum results are obtained in soil mixed with 10% bagasse ash and 0.5% coir fiber [30].…”

Section: U Karstmentioning

confidence: 97%

Increasing Unconfined Compressive Strength of Soft Clay Stabilized with Coir Fiber and Bagasse Ash Mix

Widianti,

Sundi,

Rahmawati

et al. 2024

U Karst

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Increasing coir fiber and bagasse ash waste can cause environmental degradation. Utilization of this waste in construction work is still rarely done. Coir fiber is a natural material with the highest coefficient of friction and tensile strength. Bagasse ash has a high silica content and is suitable for use as pozzolan. Soil stabilization with a combination of both is expected to improve the geotechnical properties of soft soil. This research aims to analyze the unconfined compressive strength (UCS) and secant modulus of soft clay stabilized with coir fiber-bagasse ash mix. Coir fiber as much as 0.75% and ash with varying contents: 0%, 2%, 4%, 6%, 8%, and 10% of the total weight of the mixture. The specimens were cured for 28 days. UCS tests were conducted according to ASTM D2166-16 with the axial stress and strain relationship curve results to determine the UCS and secant modulus. The results showed that the UCS value and secant modulus value increased along with increasing bagasse ash content. The maximum value was achieved at 8% ash variation with a UCS value of 472.45 kPa (an increase of 382% from a soil-coir fiber mix) and a secant modulus value of 21.94 MPa (an increase of 571% from a mixture of soil and coir fiber). The research results show that this mixed soil is classified as hard soil, which can withstand high loads. It is hoped that the results of this research can become a reference for stabilizing soft soil in the field.

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“…The tests carried out are liquid limit, plastic limit, free swelling index, and UCS. Maximum results are obtained in soil mixed with 10% bagasse ash and 0.5% coir fiber [30].…”

Section: U Karstmentioning

confidence: 97%

Increasing Unconfined Compressive Strength of Soft Clay Stabilized with Coir Fiber and Bagasse Ash Mix

Widianti,

Sundi,

Rahmawati

et al. 2024

U Karst

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“…Agro-based environmentally friendly pozzolanic materials, such as rice husk ash, palm oil fuel ash, bagasse ash, coconut shell ash, coconut husk ash, corn cob ash, almond shell ash, etc., have gained considerable attention in soil stabilisation given the ever-growing costs of their disposal [7][8][9][10][11][12][13][14][15][16][17][18]. The major chemical composition of these plant-based pozzolans are alumino-silicates [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Strength Predictive Modelling of Soils Treated with Calcium-Based Additives Blended with Eco-Friendly Pozzolans—A Machine Learning Approach

2022

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The unconfined compressive strength (UCS) of a stabilised soil is a major mechanical parameter in understanding and developing geomechanical models, and it can be estimated directly by either lab testing of retrieved core samples or remoulded samples. However, due to the effort, high cost and time associated with these methods, there is a need to develop a new technique for predicting UCS values in real time. An artificial intelligence paradigm of machine learning (ML) using the gradient boosting (GB) technique is applied in this study to model the unconfined compressive strength of soils stabilised by cementitious additive-enriched agro-based pozzolans. Both ML regression and multinomial classification of the UCS of the stabilised mix are investigated. Rigorous sensitivity-driven diagnostic testing is also performed to validate and provide an understanding of the intricacies of the decisions made by the algorithm. Results indicate that the well-tuned and optimised GB algorithm has a very high capacity to distinguish between positive and negative UCS categories (‘firm’, ‘very stiff’ and ‘hard’). An overall accuracy of 0.920, weighted recall rates and precision scores of 0.920 and 0.938, respectively, were produced by the GB model. Multiclass prediction in this regard shows that only 12.5% of misclassified instances was achieved. When applied to a regression problem, a coefficient of determination of approximately 0.900 and a mean error of about 0.335 were obtained, thus lending further credence to the high performance of the GB algorithm used. Finally, among the eight input features utilised as independent variables, the additives seemed to exhibit the strongest influence on the ML predictive modelling.

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Use of Bagasse Ash and Coconut Fiber in Stabilization of Black Cotton Soil

Cited by 2 publications

References 4 publications

Increasing Unconfined Compressive Strength of Soft Clay Stabilized with Coir Fiber and Bagasse Ash Mix

Increasing Unconfined Compressive Strength of Soft Clay Stabilized with Coir Fiber and Bagasse Ash Mix

Strength Predictive Modelling of Soils Treated with Calcium-Based Additives Blended with Eco-Friendly Pozzolans—A Machine Learning Approach

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