This dataset consists of two types of image data for sand particle analysis, covering a variety of typical sand types. It is suitable for tasks such as image super-resolution, object detection, and instance segmentation. Sand Particle Super-Resolution Dataset contains 800 high-resolution images (4480×4480 pixels) captured using a Canon 5D Mark IV camera equipped with an EF 100 mm f/2.8 L IS USM macro lens. The dataset includes 8 types of sand particles: Fujian sand, Hebei Sand No.1, Heb...

This dataset is designed to support the automatic recognition and segmentation of nonoverlapping and overlapping particles in granular images. All images were captured from a top-down view using a Canon 5D Mark IV camera equipped with an EF24-105mm lens, with a resolution of 6720×4480 pixels. The dataset contains a total of 420 images. Each image has been annotated at the instance level using the LabelMe tool, with particles categorized into two types of labels: “nonoverlapping particles...

The datasets (84 flume, 118 field photos) cover a wide range of fluvial environments and include a variety of field site and flume experiment images. The datasets were grouped into three subsets according to sediment and channel conditions: (1) flume channel (84 photos; photo size ~ 0.2 m × 0.2m); (2) forested mountain rivers (70 photos; photo size ~ 1m × 1m); and (3) sparsely vegetated large rivers (6 photos; photo size ~ 20m × 20m). To train the machine learning model to better disting...

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