Interpretation of undrained shear strength observed in confined triaxial compression tests on compacted clay

Wong, Chee K.; Lun, Martin C.H.; Wong, R.C.K.

doi:10.1139/cgj-2020-0355

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…Despite the potential for studying matric suction in unsaturated soil provided by the triaxial testing apparatus using the axis translation technique, the slow loading rate required to maintain equilibrium between pore water pressure and pore air pressure leads to extended test cycles. Additionally, measurements of pore air pressure and pore water pressure at the boundaries may not fully capture the characteristics of the entire specimen [18]. In cases of rapid loading application without sufficient time for pore water pressure to stabilize, the matric suction of the soil alters, deviating from the desired controllable suction state usually maintained in laboratory experiments [19,20].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, many scholars have attempted to study the shear strength characteristics with constant water content during the shear process of unsaturated soils through undrained and unconsolidated (UU) tests. Wong [18] estimated the change in matric suction during the shear process by measuring matric suction before and after a UU test and using a soil water characteristic curve (SWCC) with equilibrium soil suction, explaining the characteristics of the undrained shear strength of compacted clay. Pujiastuti [21] measured the matric suction using the filter paper method and conducted a series of UU tests to measure the shear strength of unsaturated sandy clay, obtaining the relationship between shear strength, cohesion, internal friction angle, and matric suction.…”

Section: Introductionmentioning

confidence: 99%

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Deformation and Strength of Unsaturated Loess—Hydraulic Coupling Effects under Loads

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et al. 2024

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The volumetric change in unsaturated loess during loading causes serious damage to the foundation and structure, accompanied by changes in hydraulic conditions. Therefore, quantifying the change in the load effect of loess under hydraulic coupling is of great significance for revealing the mechanism of hydraulic interaction. This study conducts isotropic compression and undrained shear tests on unsaturated compacted loess, simultaneously introducing the strength parameter η to enhance the Glasgow coupled model (GCM). The objective is to elucidate the hydraulic and mechanical coupling mechanism, where saturation increases under mechanical effects lead to strength degradation. The results show that saturation increases under mechanical effects improve the compressibility of the sample, and saturation has a direct impact on the stress–strain relationship. The increase in water content and confining pressure increases the trend of the critical state stress ratio M decreasing, and the strain softening trend increases. The compression of volume during shear tests increases the saturation, changes the hydraulic characteristics of loess, and affects the deformation and strength of loess. The modified GCM improves the applicability and prediction accuracy of unsaturated loess under the same initial state. The research results are of great significance for revealing the hydraulic and mechanical behavior of loess.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deformation and Strength of Unsaturated Loess—Hydraulic Coupling Effects under Loads

Chai,

Li,

Qin

et al. 2024

Water

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The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction

Demir,

Sahin

2024

Stoch Environ Res Risk Assess

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In the field of data engineering in machine learning (ML), a crucial component is the process of scaling, normalization, and standardization. This process involves transforming data to make it more compatible with modeling techniques. In particular, this transformation is essential to ensure the suitability of the data for subsequent analysis. Despite the application of many conventional and relatively new approaches to ML, there remains a conspicuous lack of research, particularly in the geotechnical discipline. In this study, ML-based prediction models (i.e., RF, SVR, Cubist, and SGB) were developed to estimate the undrained shear strength (UDSS) of cohesive soil from the perspective of a wide range of data-scaling and transformation methods. Therefore, this work presents a novel ML framework based on data engineering approaches and the Cubist regression method to predict the UDSS of cohesive soil. A dataset including six different features and one target variable were used for building prediction models. The performance of ML models was examined considering the impact of the data pre-processing issue. For that purpose, data scaling and transformation methods, namely Range, Z-Score, Log Transformation, Box-Cox, and Yeo-Johnson, were used to generate the models. The results were then systematically compared using different sampling ratios to understand how model performance varies as various data scaling/transformation methods and ML algorithms were combined. It was observed that data transformation or data sampling methods had considerable or limited effects on the UDSS model performance depending on the algorithm type and the sampling ratio. Compared to RF, SVR, and SGB models, Cubist models provided higher performance metrics after applying the data pre-processing steps. The Box-Cox transformed Cubist model yielded the best prediction performance among the other models with an R2 of 0.87 for the 90% training set. Also, the UDSS prediction model generally yielded the best performance metrics when it was used with the transformed-based models (i.e., Box-Cox, Log, and Yeo-Johnson) than that of scaled-based (i.e., Range and Z-Score) models. The results show that the Cubist model has a higher potential for UDSS prediction, and data pre-processing methods have impacts on the predictive capacity of the evaluated regression models.

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Effect of pipe installation and external load on buried steel pipe responses: Experimental and numerical investigations

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Chen

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Interpretation of undrained shear strength observed in confined triaxial compression tests on compacted clay

Cited by 3 publications

References 21 publications

Deformation and Strength of Unsaturated Loess—Hydraulic Coupling Effects under Loads

Deformation and Strength of Unsaturated Loess—Hydraulic Coupling Effects under Loads

The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction

Effect of pipe installation and external load on buried steel pipe responses: Experimental and numerical investigations

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