Three‐dimensional lattice Boltzmann simulation of the permeability of soil‐rock mixtures and comparison with other prediction models

Jin, Lei; Cheng, Tao; Zhang, Yi; Li, Jingjing

doi:10.1002/nag.3193

Cited by 8 publications

(4 citation statements)

References 33 publications

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“…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. Compared with the reenactment computation effects of SRM's penetrability described in Reference [34], it is consistent with the calculation data reported in this paper.…”

Section: Discussionsupporting

confidence: 91%

“…The influence of particle size on permeability was clearly linked to rock content in the conclusion of Reference [35]. Compared with Reference [34], this study found that the soil/rock particle size feature ratio extent similarly has a particular threshold, which can cause an unforeseen increase in simulated permeability, and the two had explicit similarities in this regard.…”

Section: Soil/rock Particle Size Feature Ratio Pmentioning

confidence: 45%

“…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%

“…This study demonstrated that SRM's reproduced permeability is significantly influenced by the soil/rock particle size feature ratio (Figure 15). Additionally, Reference [34] showed that the presence of a critical value of rock content causes an unexpected shift in the pattern of the influence of rock particle size on permeability. The influence of particle size on permeability was clearly linked to rock content in the conclusion of Reference [35].…”

Section: Discussionmentioning

confidence: 99%

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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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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: Discussionsupporting

confidence: 91%

Section: Soil/rock Particle Size Feature Ratio Pmentioning

confidence: 45%

Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 99%

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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Study on the variation of the permeability coefficient of soil–rock mixtures in fault zones under different stress states

Tan,

Liang,

et al. 2024

Deep Underground Science and Engineering

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As the first gold mine discovered at the sea in China and the only coastal gold mine currently mined there, Sanshandao Gold Mine faces unique challenges. The mine's safety is under continual threat from its faulted structure coupled with the overlying water. As the mining proceeds deeper, the risk of water inrush increases. The mine's maximum water yield reaches 15 000 m3/day, which is attributable to water channels present in fault zones. Predominantly composed of soil–rock mixtures (SRM), these fault zones' seepage characteristics significantly impact water inrush risk. Consequently, investigating the seepage characteristics of SRM is of paramount importance. However, the existing literature mostly concentrates on a single stress state. Therefore, this study examined the characteristics of the permeability coefficient under three distinct stress states: osmotic, osmotic–uniaxial, and osmotic–triaxial pressure. The SRM samples utilized in this study were extracted from in situ fault zones and then reshaped in the laboratory. In addition, the micromechanical properties of the SRM samples were analyzed using computed tomography scanning. The findings reveal that the permeability coefficient is the highest under osmotic pressure and lowest under osmotic–triaxial pressure. The sensitivity coefficient shows a higher value when the rock block percentage ranges between 30% and 40%, but it falls below 1.0 when this percentage exceeds 50% under no confining pressure. Notably, rock block percentages of 40% and 60% represent the two peak points of the sensitivity coefficient under osmotic–triaxial pressure. However, SRM samples with a 40% rock block percentage consistently show the lowest permeability coefficient under all stress states. This study establishes that a power function can model the relationship between the permeability coefficient and osmotic pressure, while its relationship with axial pressure can be described using an exponential function. These insights are invaluable for developing water inrush prevention and control strategies in mining environments.

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Lattice Boltzmann simulation and mesoscopic mechanism analysis of permeability in soil-rock mixtures

Cai,

Mao,

Dai

et al. 2023

Comp. Part. Mech.

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Three‐dimensional lattice Boltzmann simulation of the permeability of soil‐rock mixtures and comparison with other prediction models

Cited by 8 publications

References 33 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

Study on the variation of the permeability coefficient of soil–rock mixtures in fault zones under different stress states

Lattice Boltzmann simulation and mesoscopic mechanism analysis of permeability in soil-rock mixtures

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