Development of a Constitutive Model to Predict the Behavior of Cement-Treated Clay during Cementation Degradation: C3 Model

Nguyen, Lam; Fatahi, Behzad; Khabbaz, Hadi

doi:10.1061/(asce)gm.1943-5622.0000863

Cited by 39 publications

(4 citation statements)

References 33 publications

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“…As a result, cement‐treated soft clay will show quasi‐brittle stress–strain relationships with obvious stress peaks followed by strain softening. The final strength is close to that of ordinary remodeled soft clays though 50,57–60 …”

Section: Evaluation Of Model Performancesmentioning

confidence: 57%

“…Experimental studies on cement‐treated kaolin and Ballina clays have been carried out by Nguyen et al 50 . The kaolin clay (KC2) is treated with 0, 5, and 10% cement, respectively, and the Ballina clay is treated with 0, 10, and 12% cement, respectively.…”

Section: Evaluation Of Model Performancesmentioning

confidence: 99%

“…The final strength is close to that of ordinary remodeled soft clays though. 50,[57][58][59][60] Experimental studies on cement-treated kaolin and Ballina clays have been carried out by Nguyen et al 50 The kaolin clay (KC2) is treated with 0, 5, and 10% cement, respectively, and the Ballina clay is treated with 0, 10, and 12% cement, respectively. The undrained triaxial compression responses of the two clays with different initial isotropic consolidation pressure 𝑝 ′ 0 are examined in the experiment.…”

Section: Cement Treatmentmentioning

confidence: 99%

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A multifidelity neural network (MFNN) for constitutive modeling of complex soil behaviors

Su,

Guo,

Yang

2023

Num Anal Meth Geomechanics

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The development and calibration of soil models under the framework of plasticity is notoriously challenging given the prismatic features in soil's shear behaviors. Data‐driven deep neural networks (DNNs) offer an alternative approach to this formidable task. However, classical DNN models struggle to accurately capture soil mechanical responses using limited training data. To address this issue, a unified multifidelity neural network (MFNN) is proposed to leverage the accuracy of high‐fidelity experimental datasets and the abundance of low‐fidelity datasets synthesized using the modified Cam‐clay (MCC) model. The MFNN model can automatically learn the correlation between the low‐fidelity and high‐fidelity datasets, and has been applied to predicting the mechanical responses of over‐consolidated and anisotropically consolidated clays, cement‐treated clays, silts sheared under varying temperatures, and suction‐controlled unsaturated soils. The results demonstrate significantly improved prediction capabilities of MFNN compared to purely data‐driven DNNs. The proposed MFNN framework holds encouraging promise to revolutionize constitutive modeling of complex soil behaviors.

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Section: Evaluation Of Model Performancesmentioning

confidence: 57%

Section: Evaluation Of Model Performancesmentioning

confidence: 99%

Section: Cement Treatmentmentioning

confidence: 99%

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A multifidelity neural network (MFNN) for constitutive modeling of complex soil behaviors

Su,

Guo,

Yang

2023

Num Anal Meth Geomechanics

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“…On the other hand, parameters for clayey soil are contingent upon different constitutive models, encompassing the φ, c, E, ν, and compression characteristics (λ, κ, etc.) (Nguyen, 2016). Moreover, soil stiffness parameters, notably E and ν, inflict substantial influence over pile settlement, particularly within sandy soil.…”

Section: Literature Reviewmentioning

confidence: 99%

Finite Element Analysis on Load-Settlement Behavior of Axially Loaded Pile on Sand

Gupta,

Dahal

2023

J. Engin. Technol. Planning

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The analysis of geoengineering problems using various constitutive models necessitates substantial field and laboratory research, which entails a significant investment of time and money. As a result, the application of Finite Element Analysis in geoengineering projects is limited. This research focuses on numerically examining the behavior of a pile in a sandy soil layer. The study employs different relationships to estimate soil parameters from standard penetration tests and simple lab tests. These derived parameters, required for the Mohr-Coulomb & Hardening Soil constitutive model and the linear elastic model of the pile, are implemented in the PLAXIS 3D software. This software is used to simulate the settlement of the pile in sandy soil incorporating factors like mesh density and soil-pile interaction. The results of the study reveal that employing a finer mesh size leads to more precise results. Additionally, an interface strength of 67% proves to be more accurate for this study. Furthermore, the correlation introduced by Papadopoulos (1982) exhibits a close relation with field settlement values. In contrast, other correlations either overestimate or underestimate the results. Moreover, the study conclude that Mohr-Coulomb constitutive model satisfactorily predicts the behavior of the pile for the study area.

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Use of Advanced Constitutive Models for the Mechanical Behavior of Soft Soils With Diatoms From Bogotá (Colombia)

Mendoza,

de Farias

2024

Num Anal Meth Geomechanics

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Most constitutive models did not initially consider special behaviors in some soils with singular characteristics (e.g., soft soils with diatom content). For example, at first, these models did not consider the effect of soil structure and viscosity. However, in the last decades, these variables have been incorporated into several constitutive models to describe the mechanical behavior of the soil in its natural state. Structure and viscosity laws that adequately reproduce the soil behavior had to be developed to include these variables. This paper compares the mechanical behavior of soft soils in Bogotá with different constitutive models. Bogotá’s soft soils are lacustrine deposits with a high content of diatoms in their structure. Natural soil samples with intact structures show a high‐water content, which can be higher than 300%, liquid limits of up to 400%, void ratios higher than five, and friction angles of almost 40°. In addition, the model validations were made through the simulations of triaxial tests in compression and shear paths. Modified Cam Clay (MCC), hypoplastic (HP), and subloading Cam Clay (SCC) were the constitutive models used. Two models are based on an elastoplastic framework, and the third uses a HP framework. Several lessons were learned from the simulations regarding the strengths and weaknesses of the models compared to the tests carried out. Finally, the extensive discussion revolves around determining the most suitable model for simulating the mechanical behavior of soft soils containing diatoms in Bogotá.

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Development of a Constitutive Model to Predict the Behavior of Cement-Treated Clay during Cementation Degradation: C3 Model

Cited by 39 publications

References 33 publications

A multifidelity neural network (MFNN) for constitutive modeling of complex soil behaviors

A multifidelity neural network (MFNN) for constitutive modeling of complex soil behaviors

Finite Element Analysis on Load-Settlement Behavior of Axially Loaded Pile on Sand

Use of Advanced Constitutive Models for the Mechanical Behavior of Soft Soils With Diatoms From Bogotá (Colombia)

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