Pore-network model to quantify internal structure and hydraulic characteristics of randomly packed grains with different morphologies

The flow and transport in porous media are highly dependent on the internal structure and morphology of the pore space. The pore structure is determined by the size and geometrical shape of the solid particles, as well as their distribution and arrangement. In this study, the effect of grains surface morphology on the internal pore structure as well as the flow and transport properties of porous media were quantitatively analyzed using the pore-network approach, with angular quartz sand and round glass beads used as the test substrates. The surface morphology of the grains was visualized through scanning electron microscopy and quantified by Fourier morphological analysis. The pore structure of randomly packed quartz sand and glass beads was visualized using X-ray computed tomography and quantified using the network parameters. The surface morphology of grains with different angularities was distinguished by the shape and angularity parameters calculated from the Fourier representations. The network parameters, including mean coordination numbers, mean pore-body radii, and mean pore-throat radii, of randomly packed angular sand were larger than those of round beads within the same sieving size range. The intrinsic permeability and longitudinal dispersivity in the vertical direction were smaller than those in the horizontal direction, which indicates anisotropic compaction. The intrinsic permeability nonlinearly (power-law) varied with the pore and throat radii of the different extracted networks. The relation between intrinsic permeability and porosity of anisotropic porous media with different grain morphologies followed the Kozeny-Carman equations. Breakthrough curves in the representative elementary volumes of angular sand and round beads exhibited Fickian behavior. The longitudinal dispersivity decreased with an increase in the coordination number regardless of the grain morphology. Graphic abstract