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[期刊论文]

Pore-scale permeability estimation of undisturbed granite residual soil: A comparison study by different methods

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author:

Que, Y. (Que, Y..) [1] | Chen, X. (Chen, X..) [2] | Jiang, Z. (Jiang, Z..) [3] | Unfold

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Scopus

Abstract:

Purpose: The macropore structure and seepage characteristics profoundly influence the stability of granite residual soil (GRS) slopes. However, accurately predicting the permeability of undisturbed GRS (U-GRS) is challenging owing to its complex and susceptible pore structure. Aims and methods: Employing X-ray computed tomography (CT) technologies, a three-dimensional (3D) pore structure of U-GRS, was established. Permeability prediction for U-GRS samples was conducted using three simulation methods, namely, the pore network model (PNM), finite element method (FEM), and the lattice Boltzmann method (LBM), along with two empirical models (EMs)—specifically, Kozeny–Carman (K–C) and Katz–Thompson (K–T) models. Subsequently, the methods were comparatively analyzed for calculating efficiency and accuracy. Finally, a piecewise permeability prediction model (PPPM) for U-GRS based on the CT-LBM was proposed. Results: The ranking of permeability estimation methods in terms of accuracy was as follows: LBM > PNM > FEM > EMs. Substantial disparity was observed in the permeabilities obtained using both FEM and EMs compared to other methods, which exhibited a deviation of up to six orders of magnitude. The PPPM demonstrated smaller prediction deviations than the EMs, with its accuracy influenced by the strategy for selecting calculation parameters. Conclusion: The CT-LBM, which uses real pore structures, was employed to estimate the permeability of U-GRS. The PPPM, established based on this method, was found to be applicable for estimating U-GRS permeability. Graphical Abstract: (Figure presented.). © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

Keyword:

Comparative analysis Granite residual soil Macropore Permeability model X-ray computed tomography images

Community:

  • [ 1 ] [Que Y.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Chen X.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Jiang Z.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Jiang Z.]Department of Civil and Environmental Engineering, Hong Kong University of Science & amp
  • [ 5 ] Technology, Clear Water Bay, Kowloon, Hong Kong
  • [ 6 ] [Cai P.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 7 ] [Cai P.]College of Highway, Chang’an University, Xi’an, 710064, China
  • [ 8 ] [Xue B.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 9 ] [Xie X.]College of Civil Engineering, Fuzhou University, Fuzhou, 350108, China

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Source :

Journal of Soils and Sediments

ISSN: 1439-0108

Year: 2024

Issue: 4

Volume: 24

Page: 1591-1613

2 . 8 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

30 Days PV: 5

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