Review of the effect of sand on the behavior of expansive clayey soils

Alnmr, Ammar; Ray, Richard P.

doi:10.14513/actatechjaur.00611

Cited by 8 publications

(7 citation statements)

References 25 publications

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“…Balancing the sand fraction is critical in engineering applications because it improves soil performance and reduces the negative impacts of cracking in expansive soil [19]. The addition of sand to expansive soils has been extensively investigated by many researchers to determine its effect on the soil parameters [10,[20][21][22][23][24][25][26]. Previous studies have confirmed that increasing the percentage of sand increases the unconfined compressive strength (UCS) of expansive soils.…”

Section: Sand As An Additive Materials and Its Impact On Soil Parametersmentioning

confidence: 99%

Novel Insights in Soil Mechanics: Integrating Experimental Investigation with Machine Learning for Unconfined Compression Parameter Prediction of Expansive Soil

Alnmr,

Hosamo,

Lyu

et al. 2024

Applied Sciences

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This paper presents a novel application of machine learning models to clarify the intricate behaviors of expansive soils, focusing on the impact of sand content, saturation level, and dry density. Departing from conventional methods, this research utilizes a data-centric approach, employing a suite of sophisticated machine learning models to predict soil properties with remarkable precision. The inclusion of a 30% sand mixture is identified as a critical threshold for optimizing soil strength and stiffness, a finding that underscores the transformative potential of sand amendment in soil engineering. In a significant advancement, the study benchmarks the predictive power of several models including extreme gradient boosting (XGBoost), gradient boosting regression (GBR), random forest regression (RFR), decision tree regression (DTR), support vector regression (SVR), symbolic regression (SR), and artificial neural networks (ANNs and proposed ANN-GMDH). Symbolic regression equations have been developed to predict the elasticity modulus and unconfined compressive strength of the investigated expansive soil. Despite the complex behaviors of expansive soil, the trained models allow for optimally predicting the values of unconfined compressive parameters. As a result, this paper provides for the first time a reliable and simply applicable approach for estimating the unconfined compressive parameters of expansive soils. The proposed ANN-GMDH model emerges as the pre-eminent model, demonstrating exceptional accuracy with the best metrics. These results not only highlight the ANN’s superior performance but also mark this study as a groundbreaking endeavor in the application of machine learning to soil behavior prediction, setting a new benchmark in the field.

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Section: Sand As An Additive Materials and Its Impact On Soil Parametersmentioning

confidence: 99%

Novel Insights in Soil Mechanics: Integrating Experimental Investigation with Machine Learning for Unconfined Compression Parameter Prediction of Expansive Soil

Alnmr,

Hosamo,

Lyu

et al. 2024

Applied Sciences

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“…Uji pengembangan dilakukan untuk membandingkan dengan nilai awalnya untuk meneliti variasi perilaku pengembangan tanah ekspansif pada kedalaman yang berbeda setelah pengujian model selesai (She dkk, 2019). Beberapa cara untuk mengurangi tingkat aktivitas suatu mineral dalam ekspansive soil yaitu seperti penelitian yang dilakukan oleh (Alnmr & Ray, 2021), penelitian tersebut menyajikan tinjauan perilaku pengembangan campuran pasir-lempung serta pengaruh pasir terhadap karakteristik fisik dan mekanik tanah ekspansif.…”

Section: Hasil Dan Pembahasanunclassified

POTENSI KEMBANG SUSUT TANAH EKSPANSIF DI WILAYAH SOLO RAYA (Studi Kasus di Trucuk, Pedan, dan Nogosari)

Fitri

2021

MATEKSI JTS UNS

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Expansive soil has commonly found in several areas around infrastructure projects such as; highways, irrigation systems, buildings, and bridges. The behavior of expansive soils affects the strengths and durability of the upper structure. The main characteristic of expansive soil is the swell-shrinkage influenced by water content. Moreover, the negative trait harms the structure. For example, the cracks of the highway pavement and building wall and differential settlements in bridges abutment are the damage phenomena caused by expansive soil. The soil spread in several area near Surakarta residency namely Nogosari, Boyolali , Cawas Pedan, Klaten Regency, Bendosari Gentan, Sukoharjo and Purwodadi. Therefore, these areas have high vulnerability damage of Expansive soil. The study for determining and collecting data on the potential for shrinkage, which is a characteristic of expansive soil, is necessary conduct. This research aims to identify the swell-shrinkage potential in laboratory tests. The test had carried out with property index(water content and Atterberg limit) following code standards (SNI and ASTM). The liquid limit values for the Trucuk, Padan, and Nogosari areas are 84.75%, respectively; 73.56% and 49.05%. The plasticity index values for the Trucuk, Padan, and Nogosari regions are as follows: 66.97%; 45.72%; and 28.74%. Activity (AC) values for the 3 Pedan, Trucuk, and Nogosari locations are as follows: 1.61; 1.67; and 1.28. The value results are based on laboratory tests output, were 3 locations in the Klaten area, namely Trucuk, Pedan, and Nogosari. In summary, the zones have high susceptibility area damage by expansive soil. The result of this study is expected to be preliminary mapping guidance surround the Surakarta Residency

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“…The design of the targeted model is illustrated in Figs. 14. As for the soil reinforced with CSV, 20 columns were used; each column consists of 20 cm in diameters and 10 m in length, separated from each other by 1m.…”

Section: Numerical Modelingmentioning

confidence: 99%

“…For this reason, three percentages (25%, 50% and 75%) of soft soil contents in CSV materials are studied. Authors [10][11][12][13][14], have noticed that the added cement triggered a sudden fall in the residual strength. To tackle this problem, PP fiber is purposefully used, as it can greatly enhance the residual strength [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Reinforced Soft Soil by CSV with/without Polypropylene fibres: Experimental and Numerical analysis.

Souadeuk

Boudaoud

2021

Frattura Ed Integrità Strutturale

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Columns of mixed soil-sand-cement (CSV), is one of the most unknown used methods for soft soil stabilization that has not been studied before. To this end, in this paper, consolidated drained (CD) triaxial compression tests after have been cured for 28 days, were carried out to investigate the effectiveness of CSV, which is mainly used to reinforce soft soil. Then, the influence of soft soil content (25%, 50%, 75%) on materials of CSV with/without polypropylene (PP) fibers is established. The percentages of soft soils (50%, 75%) are experimentally doable and the remaining percentage (25%) was not successfully experimented; for this exact reason, an empirical formula is established based on the design of experiments (DOE) for calculating the soft soil’s characteristics. Then a numerical study using PLAXIS 3D is developed for studying the embankment building on soil which is reinforced by CSV. It is found that the efficacy of the reinforcement of the soft soil by CSV with/without PP fibers provides with satisfying results. Moreover, the less amount of soft soil on CSV materials the better for deviatoric stress, axial strain, the effective cohesion, the effective friction angle and modulus of elasticity E50. Additionally, when PP fibers is added to CSV material, experimental results were strongly affected. As far as the numerical study, the embankment building on the soil that is reinforced by the CSV shows an improvement in the level of displacement in the three directions, the total displacement and security factor. The variation of materials of CSV content with/without PP fibers, a diverse combination with a relatively lower effect can be easily remarked on the achieved results.

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Review of the effect of sand on the behavior of expansive clayey soils

Cited by 8 publications

References 25 publications

Novel Insights in Soil Mechanics: Integrating Experimental Investigation with Machine Learning for Unconfined Compression Parameter Prediction of Expansive Soil

Novel Insights in Soil Mechanics: Integrating Experimental Investigation with Machine Learning for Unconfined Compression Parameter Prediction of Expansive Soil

POTENSI KEMBANG SUSUT TANAH EKSPANSIF DI WILAYAH SOLO RAYA (Studi Kasus di Trucuk, Pedan, dan Nogosari)

Reinforced Soft Soil by CSV with/without Polypropylene fibres: Experimental and Numerical analysis.

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