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Three‐dimensional lattice Boltzmann simulation of the permeability of soil‐rock mixtures and comparison with other prediction models
Author(s) -
Jin Lei,
Cheng Tao,
Zhang Yi,
Li Jingjing
Publication year - 2021
Publication title -
international journal for numerical and analytical methods in geomechanics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.419
H-Index - 91
eISSN - 1096-9853
pISSN - 0363-9061
DOI - 10.1002/nag.3193
Subject(s) - permeability (electromagnetism) , lattice boltzmann methods , relative permeability , slicing , geotechnical engineering , soil science , geology , mechanics , statistical physics , mathematics , chemistry , porosity , physics , engineering , mechanical engineering , biochemistry , membrane
With the discrete element method and the proposed virtual slicing technique for three‐dimensional discrete element model, random pore‐structural models of soil‐rock mixtures (SRMs) are constructed and voxelized. Then, the three‐dimensional lattice Boltzmann method (LBM) is introduced to simulate the seepage flow in SRMs on the pore scale and the influences of rock content, rock size, relative density on the simulated permeability of SRMs are comprehensively investigated. Finally, several theoretical models are introduced to predict the permeability of SRMs, and comparison is made between the results given by these prediction models and the numerical results obtained in this study. The results show that the permeability of SRMs presents a gradually increasing trend with the increase of rock content, and the rate of increase is also getting larger. When the other conditions remain unchanged, the permeability of SRMs decreases with the increase of relative density. When the rock content is lower than a threshold value, the permeability decreases as the rock size increases; however, this trend gets reversed when the rock content exceeds the threshold value. The permeability values of SRMs simulated with the LBM are lower in different levels than those calculated with the HS model, EMA model, and Zhou model, but most of them are very close to those predicted by the Daigle model.