Prediction of dynamic shear modulus of saturated coral sand based on explainable artificial intelligence

Construction and Building Materials, Год журнала: 2025, Номер 461, С. 139878 - 139878

Опубликована: Янв. 1, 2025

Язык: Английский

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Application of natural and synthetic fibers in bio-based earthen composites: A state-of-the-art review

Results in Engineering, Год журнала: 2024, Номер unknown, С. 103732 - 103732

Опубликована: Дек. 1, 2024

Язык: Английский

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Geotechnical and microstructural analysis of high-volume fly ash stabilized clayey soil and machine learning application

Case Studies in Construction Materials, Год журнала: 2024, Номер 21, С. e03628 - e03628

Опубликована: Авг. 10, 2024

The weak soil stabilization using solid wastes is one of the most common solutions for improving geotechnical characteristics as well problematic waste dumping in landfills. present experimental study aims to examine effect high-volume Class-F fly ash on and microstructural properties clayey by adding them ranges between 5 % 50 %. results show that amount increases, like specific gravity, plasticity index, permeability, optimum moisture content, maximum dry density free swelling index improves. Moreover, these were analyzed develop machine learning models three different algorithms, namely K-nearest neighbor regression, random forest, support vector obtaining contents expansive soils. predicted found be close-relation predicting behavior modified soil. Furthermore, performance ML degrades number components reduces, with KNN regression consistently outperforming SVR RF but suffering significantly fewer components. testing set case four are MSE 77, R² 0.896, RMSE 0.846, MAE 0.327, SEE 0.858, indicating precise consistent predictions. However, prediction accuracy considering lesser shows 262, 0.648, 5.606, 16.707, GPI 1.056, confirming elevated error rates. Overall, it has been concluded combining comprehensive work techniques outperforms enhancing data processing, optimized soils, improves sustainability construction, saves resources, reduces possibility human mistakes, increases reliability.

Язык: Английский

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A comprehensive review on the application of microbially induced calcite precipitation (MICP) technique in soil erosion mitigation as a sustainable and environmentally friendly approach

Results in Engineering, Год журнала: 2024, Номер 24, С. 103235 - 103235

Опубликована: Окт. 25, 2024

Язык: Английский

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A comparison of temperature and freeze-thaw effects on high-swelling and low-swelling soils stabilized with xanthan gum

Results in Engineering, Год журнала: 2024, Номер 25, С. 103719 - 103719

Опубликована: Дек. 10, 2024

Язык: Английский

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Research of Enzyme-Induced Carbonate Precipitation on Strength Behavior of Reinforced Sand

Applied Sciences, Год журнала: 2025, Номер 15(7), С. 3558 - 3558

Опубликована: Март 25, 2025

Stabilizing sandy soil with inadequate engineering properties is essential for constructing infrastructure systems in all regions, especially desertification-prone areas. Enzymatically Induced Carbonate Precipitation (EICP) offers an innovative solution, advantages over conventional reinforcement methods due to its low energy consumption and carbon emission. This emerging technique has proven effective enhancing strength, yet the effects of variables such as curing time cementation solution concentration, their micro-mechanistic implications on soil, remain understudied. study conducted a series unconfined compressive strength (UCS) tests microstructural analyses EICP-treated sand. The results showed that optimal EICP-reinforced sand seven days, being contingent upon density. maximum UCS value was observed at relative density 0.7 concentration 1 mol/L. Mechanistically, EICP strengthens integrity through calcium carbonate-mediated particle bridging, thereby boosting strength. Micro-CT imaging fractal dimension reveal precipitation process decreases both size connectivity pores, while simultaneously increasing surface heterogeneity overall toughness. research establishes foundational framework advancing applications stabilization engineering.

Язык: Английский

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Leveraging ML for predicting UCS of soil stabilised with one-part alkali-activated binder

Proceedings of the Institution of Civil Engineers - Ground Improvement, Год журнала: 2025, Номер unknown, С. 1 - 11

Опубликована: Апрель 16, 2025

The transition to sustainable construction materials has driven interest in alternatives Portland cement. Soil stabilisation with alkali-activated binders is a promising approach, yet its widespread application requires reliable predictive tools for assessing unconfined compressive strength (UCS). This study explores the use of machine learning algorithms predict UCS soil stabilised one-part binder. An experimental data set was compiled train and validate multiple models, including random forests, artificial neural networks, support vector machines. Despite set’s limited size, models demonstrated strong accuracy, forest achieving an R 2 exceeding 0.80. Sensitivity analysis revealed that water content were most influential parameters, aligning established geotechnical principles. These findings highlight potential as tool optimising techniques. By enhancing capabilities, this approach supports more efficient material selection, reducing reliance on extensive laboratory testing. underscores value integrating data-driven methods into engineering advance high-performance treatment solutions.

Язык: Английский

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The role of particle shape in the mechanical behavior of granular soils: A state-of-the-art review

Results in Engineering, Год журнала: 2024, Номер 24, С. 103572 - 103572

Опубликована: Ноя. 29, 2024

Язык: Английский

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Performance assessment of a foundation resting on reinforced collapsible Sabkha soil by deep soil mixing columns using machine learning analyses

Alexandria Engineering Journal, Год журнала: 2025, Номер 118, С. 591 - 605

Опубликована: Янв. 28, 2025

Язык: Английский

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Dust suppression performance and dust suppression mechanism of microbial induced struvite precipitation technology

Powder Technology, Год журнала: 2025, Номер unknown, С. 120905 - 120905

Опубликована: Март 1, 2025

Язык: Английский

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