Numerical study on the effect of meso-structure on hydraulic conductivity of soil-rock mixtures

Wang, Tie; Yan, Chengzeng; Zheng, Yuchen; Jiao, Yu‐Yong; Zou, Junpeng

doi:10.1016/j.compgeo.2022.104726

Cited by 30 publications

(8 citation statements)

References 81 publications

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“…The pattern of permeability coefficient changes with the increase in rock content described in Reference [36] supports the reliability of the mimicked estimation of penetrability noted in this paper. In any case, it is important to note that the permeability values derived from this paper's mathematical calculations are significantly higher than those derived from experiments in References [22,[36][37][38]. The reason is that the SRM used in the experiment has soil and rock particles that are mostly attached, whereas the SRM made by the mathematical model has sandy particles that do not have a bond, so the permeability is larger.…”

Section: Discussionmentioning

confidence: 74%

“…Compared with other researchers, it can be seen that References [22,34,35] focus on the influence of rock particle size on the SRM's simulated permeability, but had not considered the influence of the mutual relationship between soil and rock particle size on the SRM's simulated permeability. This study demonstrated that SRM's reproduced permeability is significantly influenced by the soil/rock particle size feature ratio (Figure 15).…”

Section: Discussionmentioning

confidence: 91%

“…), and the soil/rock ratio are all strongly correlated with the physical and mechanical characteristics of the SRM [19]. Additionally, in reference to the research that was conducted by other researchers on SRM seepage characteristics [17,21,22], it has been observed that employing 2D models to simulate SRM seepage characteristics also possesses a particular representativeness. As a result, the classical Monte Carlo method [23] is used to investigate how the aforementioned variables affect the SRM's permeability.…”

Section: Discrete Models Of Soil-rock Mixturementioning

confidence: 88%

See 2 more Smart Citations

Lattice Boltzmann Numerical Study on Mesoscopic Seepage Characteristics of Soil–Rock Mixture Considering Size Effect

Cai

Mao

et al. 2023

Mathematics

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One of the hot topics in the study of rock and soil hydraulics is the size effect of a soil–rock mixture’s (SRM) seepage characteristics. The seepage process of the SRM was simulated from the pore scale through the lattice Boltzmann method (LBM) in this paper to explore the internal influence mechanism of sample size effect on the SRM seepage characteristics. SRM samples were generated using the improved Monte Carlo method (IMCM), and through 342 simulation test conditions the influence of size feature parameters such as resolution (R), segmentation type, model feature size (S), feature length ratio (F), and soil/rock particle size feature ratio (P) was examined. The study demonstrated that as R increases, the permeability of the SRM gradually rises and tends to stabilize when R reaches 60 ppi. At the same S, the dispersion degree of model permeability obtained by the four segmentation types is in the order of center < random < equal < top. With an increase in S, the permeability (k) of the SRM gradually decreases, conforming to the dimensionless mathematical model, k=a0·S−b0, and tends to stabilize at S = 80 mm. With an increase in F and an increase in S, the permeability of the SRM exhibits a linear “zonal” distribution that declines in order. When F is greater than 12, the dispersion of the permeability value distribution is especially small. With an increase in P, the permeability of the SRM decreases gradually before rising abruptly. P is crucial for the grading and structural makeup of the SRM. Overall, this paper concludes that the conditions of R = 60 ppi, center segmentation type, S = 80 mm, F ≥ 12, and P set by demand can be used to select and generate the size of the SRM optimal representative elementary volume (REV) numerical calculation model. The SRM can serve as a general reference for test and engineering construction as a common geotechnical engineering material.

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Section: Discussionmentioning

confidence: 74%

Section: Discussionmentioning

confidence: 91%

Section: Discrete Models Of Soil-rock Mixturementioning

confidence: 88%

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Lattice Boltzmann Numerical Study on Mesoscopic Seepage Characteristics of Soil–Rock Mixture Considering Size Effect

Cai

Mao

et al. 2023

Mathematics

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“…The difficulty in using Equation (9) to calculate the hydraulic conductivity of coarsegrained soils is establishing the equations for d e and α, which are related to equivalent particle size and particle shape and pore structure, respectively. The determination of d e and α through tests requires a combined CT scan and constant-head permeability test for coarse-grained soils.…”

Section: Hydraulic Conductivity Calculation Model For Coarse-grained ...mentioning

confidence: 99%

“…However, the accuracy of such empirical tests is susceptible to factors like specimen preparation and boundary conditions [2][3][4][5][6][7][8], which demand rigorous operational protocols and equipment. In contrast, numerical simulations leverage finite or discrete elements to model real-world coarse-grained soils [9][10][11][12]. However, these models often rely on parameters that are experimentally elusive, undermining their applicability and limiting experimental validation.…”

Section: Introductionmentioning

confidence: 99%

Deep-Learning-Enhanced CT Image Analysis for Predicting Hydraulic Conductivity of Coarse-Grained Soils

Peng

Shen

Zhang

et al. 2023

Water

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Permeability characteristics in coarse-grained soil is pivotal for enhancing the understanding of its seepage behavior and effectively managing it, directly impacting the design, construction, and operational safety of embankment dams. Furthermore, these insights bridge diverse disciplines, including hydrogeology, civil engineering, and environmental science, broadening their application and relevance. In this novel research, we leverage a Convolutional Neural Network (CNN) model to achieve the accurate segmentation of coarse-grained soil CT images, surpassing traditional methods in precision and opening new avenues in soil granulometric analysis. The three-dimensional (3D) models reconstructed from the segmented images attest to the effectiveness of our CNN model, highlighting its potential for automation and precision in soil-particle analysis. Our study uncovers and validates new empirical formulae for the ideal particle size and the discount factor in coarse-grained soils. The robust linear correlation underlying these formulae deepens our understanding of soil granulometric characteristics and predicts their hydraulic behavior under varying gradients. This advancement holds immense value for soil-related engineering and hydraulic applications. Furthermore, our findings underscore the significant influence of granular composition, particularly the concentration of fine particles, on the tortuosity of water-flow paths and the discount factor. The practical implications extend to multiple fields, including water conservancy and geotechnical engineering. Altogether, our research represents a significant step in soil hydrodynamics research, where the CNN model’s application unveils key insights into soil granulometry and hydraulic conductivity, laying a strong foundation for future research and applications.

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Insights into the Effect of Water Content on Mudstone Fragmentation and Cutter Force during TBM Cutter Indentation via the Combined Finite-Discrete Element Method

Yan,

Wang,

Zheng

et al. 2024

Rock Mech Rock Eng

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Numerical study on the effect of meso-structure on hydraulic conductivity of soil-rock mixtures

Cited by 30 publications

References 81 publications

Lattice Boltzmann Numerical Study on Mesoscopic Seepage Characteristics of Soil–Rock Mixture Considering Size Effect

Lattice Boltzmann Numerical Study on Mesoscopic Seepage Characteristics of Soil–Rock Mixture Considering Size Effect

Deep-Learning-Enhanced CT Image Analysis for Predicting Hydraulic Conductivity of Coarse-Grained Soils

Insights into the Effect of Water Content on Mudstone Fragmentation and Cutter Force during TBM Cutter Indentation via the Combined Finite-Discrete Element Method

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