@article{WANG2019276,
title = "An updated Lagrangian LBM–DEM–FEM coupling model for dual-permeability fissured porous media with embedded discontinuities",
journal = "Computer Methods in Applied Mechanics and Engineering",
volume = "344",
pages = "276 - 305",
year = "2019",
issn = "0045-7825",
doi = "https://doi.org/10.1016/j.cma.2018.09.034",
url = "http://www.sciencedirect.com/science/article/pii/S0045782518304870",
author = "Kun Wang and WaiChing Sun",
keywords = "Discrete-continuum coupling, Strong discontinuity, Machine learning, LBM–DEM–FEM, Dual-permeability, Fractured porous media",
abstract = "Many engineering applications and geological processes involve embedded discontinuities in porous media across multiple length scales (e.g. rock joints, grain boundaries, deformation bands and faults). Understanding the multiscale path-dependent hydro-mechanical responses of these interfaces across length scales is of ultimate importance for applications such as CO2 sequestration, hydraulic fracture and earthquake rupture dynamics. While there exist mathematical frameworks such as extended finite element and assumed strain to replicate the kinematics of the interfaces, modeling the cyclic hydro-mechanical constitutive responses of the interfaces remains a difficult task. This paper presents a semi-data-driven multiscale approach that obtains both the traction-separation law and the aperture-porosity–permeability relation from micro-mechanical simulations performed on representative elementary volumes in the finite deformation range. To speed up multiscale simulations, the incremental constitutive updates of the mechanical responses are obtained from discrete element simulations at the representative elementary volume whereas the hydraulic responses are generated from a neural network trained with data from lattice Boltzmann simulations. These responses are then linked to a macroscopic dual-permeability model. This approach allows one to bypass the need of deriving multi-physical phenomenological laws for complex loading paths. More importantly, it enables the capturing of the evolving anisotropy of the permeabilities of the macro- and micro-pores. A set of numerical experiments are used to demonstrate the robustness of the proposed model."
}