Database and code to the paper: A multiscale CNN-based intrinsic permeability prediction in deformable porous media. Including: (1) a dataset of CT images from Bentheim sandstone at different volumetric strain levels; (2) pore-scale permeability simulation data of single-phase flow using the lattice Boltzmann method (LBM); (3) the CNN model with the processed CT images as inputs and permeability tensors as outputs; and (4) data augmentation and alternative CNN architectures.

Supplementary Data for the paper "Three-Dimensional Particle Shape Analysis Using X-ray Computed Tomography: Experimental Procedure and Analysis Algorithms for Metal Powders" by E.J. Garboczi and N. Hrabe.

All the training data of triaxial testing is provided by discrete element modelling wherein a total of 4037 spherical particles with their radii uniformly distributed between 2mm and 4mm are used to generate the specimens. These specimens are isotropically consolidated to a confining pressure of 200 kPa. The normal and tangential contact stiffnesses are 105 N/m and 5 × 104 N/m, respectively. The interparticle frictional coefficient is 0.5, the particle density is 2600 kg/m3, the local ...

45,000 implicit DEM simulations for particle crushing, encompassing a total of 900 different particle types. This includes the Cartesian product of 20 distinct particle diameters, 15 different scaled shapes along the (X, Y, Z) axes, and 3 different compression axes under one-dimensional compression.

The present work investigates the effect of both surface roughness and particle morphology on the retention behaviour of granular materials. To study this, X-ray micro-computed tomography tests were performed on two different sands (i.e. natural and roughened). Each sample was subjected to either drainage or soaking paths consisting in a multiphase ‘static’ flow of potassium iodine (KI) brine (wetting phase) and dry air (non-wetting phase). Tomograms were taken at different saturation st...

3D digital sand grains