Enlarged Pores

## Overview

Enlarged Pores is a dataset for object detection tasks - it contains Test WiTv annotations for 1,672 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Pores

## Overview

Pores is a dataset for instance segmentation tasks - it contains Pores annotations for 444 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

X-Ray computed tomography (XCT) scan of 11 individual metallic powder particles, made of (Mn,Fe)2(P,Si) alloy

The data set consists of 4 single XCT scans which have been stitched together [3] after reconstruction. The powder material is an (Mn,Fe)2(P,Si) alloy with an average density of 6.4 g/cm³. The particle size range is about 100 - 150 µm with equivalent pore diameters up to 75 µm. The powder and the metallic alloy are described in detail in [1, 2].

Data acquisition

The data was acquired using a Zeiss Xradia 620 Versa X-ray microscope which provides the opportunity of optical magnification.

Tomographic imaging parameters


    XCT system
    Zeiss Xradia 620 Versa


    Voltage
    80
    kV


    Power
    10
    W


    Source filtering
    "LE2" (system specific)
    -


    Source-object distance
    10
    mm


    Object-detector distance
    10
    mm


    Geom. magnification
    2
    -


    Optical magnification
    20
    -


    Native pixel size
    13.5
    µm


    Binning
    2x2
    px


    Voxel size
    0.68
    µm


    No. of projections per scan
    801
    1


    No. of scans
    4
    -


    Exposure time per projection
    5
    s

Projection data (801 single TIFF-files each):

proj_00

proj_01

proj_02

proj_03

Reconstructed data:

raw-volume (MnFePSi-Powder_80kV_10W_LE2_20x_5s_801_0p68_BHC=2_Stitch_U16_966x1020x2916.raw + header.txt)

analyzed data as Volume Graphics Studio MAX 3.4.5 project

Stitched 2D data (images stitched with ImageJ-Plugin described in [3]:

Stitched_0deg_Projections.tif

Pores+Particles_Analysis.tif

[1] G.-R. Jaenisch, U. Ewert, A. Waske, and A. Funk, “Radiographic Visibility Limit of Pores in Metal Powder for Additive Manufacturing,” Metals, vol. 10, no. 12, p. 1634, Dec. 2020. https://doi.org/10.3390/met10121634

[2] X. Miao et al., “Printing (Mn,Fe)2(P,Si) magnetocaloric alloys for magnetic refrigeration applications,” J. Mater. Sci., vol. 55, no. 15, pp. 6660–6668, May 2020. https://doi.org/10.1007/s10853-020-04488-8

[3] S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics, vol. 25, no. 11, pp. 1463–1465, Jun. 2009.

Data embargoed until publication of related article, or up to no more than 1 year from data upload Geometric classifications of 3D pores are useful for studying relationships between pore geometry and function in granular materials. Pores are typically characterized by size, but size alone cannot explain 3D phenomena like transport. Here, we implement a KNN-based pore classification approach emphasizing shape-related properties. We find pore types produced in randomly packed systems resemble those of ideal, hexagonally packed systems. In both random and perfect systems, pores tend to configure as octahedrons (O’s) and icosahedrons (I’s). We demonstrate the physical implications of this by running flow simulations through a granular system and observe differences in fluid dynamic behaviors between pore types. We finally show the O/I pore distribution can be tuned by modifying particle properties (shape, stiffness, size). Overall, this work enables analysis of granular system behaviors by 3D pore shape and informs system design for desired distributions of pore geometries. ... [Read More]

This data set contains results from pore network modeling of one sample of dry Fontainebleau sandstone (Case 1), and two samples of Berea sandstones (dry, Case 2, oil and water saturated, case 3). For each sample, there are two .csv file. One file containing information about pockets (pores) and the other containing information about throats. The content of each column is described in the heading of the files.

Pore network simulations were performed to investigate the electrical geophysical signature of solute-transport in dual-_domain media. This data release includes model results, source code, and laboratory data used in the accompanying paper, as explained in the upper-level "readme" file.

the piezometer is designed to measure in-situ pore pressure relative to the hydrostatic pressure and temperature. for this dataset, in-situ excess pore pressure and temperature measurements were made using cable-deployed piezometers equipped with a sediment piercing lance of 60 mm diameter carrying differential pore pressure (pore pressure in excess of hydrostatic pressure or fluid excess pore pressure) and temperature sensors, ballasted with lead weights (up to 1000 kg). the piezometer pore pressure and temperature sensors have an accuracy of ±0.5 kpa and 0.05 °c, respectively.

Pore waters from the top six inches of sediment core collected from the San Juan Generating Station reservoir were collected and analyzed for inorganic elements.

The file uploaded on is the numerical data used for creating figures in manuscript "Diffused pore pressure in a poroelastic, layered medium with dynamic reservoir impoundment". There are two subfiles inclued in it: (1) data used in figures creation, and (2) figures in manuscript and its appendix (both in pdf and jpg format).

Microporosity by performing low pressure nitrogen adsorption measurements on 13 shallow marine mudstone samples from the Nankai Trough offshore Japan. The samples were from two reference Sites on the incoming Philippine Sea Plate, and one Site above the accretionary prism. I determined pore size distributions using the Barrett–Joyner–Hallenda (BJH) model, and merged these with existing mercury injection capillary pressure (MICP) measurements to construct a full distribution covering micro- to macropores. I found that overall pore sizes decrease with consolidation, and that microporosity content (pores < 2 nm in diameter) is influenced mainly by mineralogy, with some influence of diagenetic processes. A small amount of microporosity (~ 0.25% of bulk sediment volume) is present in these sediments at the time of burial, presumably contained mainly in clays. Additional microporosity may develop as a result of alteration of volcanic ash at the reference Sites, and may be related to diagenetic processes that create zones of anomalous high porosity. Comparisons with porewater chemistry (K+, Ca2 +, Sr, Si) show inconsistent relationships with microporosity development and cannot confirm or deny the role of ash alteration in this process. The strongest correlation observed at the three Sites was between microporosity volume and clay mineral fraction. This suggests that microporosity content is determined mainly by detrital clay abundance and development of clay as an ash alteration product, with some contribution from amorphous silica cement precipitated in the zones of anomalous high porosity.

Sand conlumn experiments were conducted to describe time-varying pore water pressure. Height of the sand column is fixed as 50 cm and three pore water pressure transducers were deployed along the sidewall of the sand column at 46 cm, 38 cm, 30cm, 22 cm, 14cm, 6 cm below the sand surface, respectively.

This is the Python code and plotted figure data used to create the figures for the submitted manuscript, "Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation" submitted to JGR: Solid Earth in 2022.

The manuscript concerns a novel technique developed for EGS stimulation, called pore pressure or effective normal stress preconditioning, which preemptively alters the stress field along a fault prior to injection, such that the risk of induced seismicity is reduced. Using a slightly altered version of a preexisting model (a combination of an analytical pore pressure model and a linear slip weakening seismicity model) the effect of this kind of treatment is evaluated.

The results of single-/two-phase flow modeling by pore network modeling.

This is experimental data of combined wave-current induced pore pressure. The corresponding test condition is given in the title of each excel. The channels 4, 2, 1 represent the wave height data measured by the WHGs just above PPTs, in the upstream, and in the downstream, respectively. The channels 6, 8, 3, 7 are pore pressure data monitored by PPTs installed at 0, 6, 9, and 15 cm below the seabed surface, respectively.

Model generated soil pore water salinity (psu) values under scenarios of drought and normal conditions at Tidal Freshwater Forested Wetlands (TFFW) sites along the Waccamaw River and Savannah River in the Southeastern United States.

This dataset contains data used for the paper "Pore network response to freeze-thaw cycles in permafrost aggregates". The Related References field will be updated with a full citation when available. Climate change in Arctic landscapes may increase freeze-thaw frequency within the active layer as well as newly thawed permafrost. A highly disruptive process, freeze-thaw can deform soil pores and alter the architecture of the soil pore network with varied impacts to water transport and retention, redox conditions, and microbial activity. Our objective was to investigate how freeze-thaw cycles impacted the pore network of newly thawed permafrost aggregates to improve understanding of what type of transformations can be expected from warming Arctic landscapes. We measured the impact of freeze-thaw on pore morphology, pore throat diameter distribution, and pore connectivity with X-ray computed tomography (XCT) using six permafrost aggregates with sizes of 2.5 cm3 from a mineral soil horizon (Bw; 28-50 cm depths) in Toolik, Alaska. Freeze-thaw cycles were performed using a laboratory incubation consisting of five freeze-thaw cycles (-10˚C to 20˚C) over five weeks. Our findings indicated decreasing spatial connectivity of the pore network across all aggregates with higher frequencies of singly connected pores following freeze-thaw. Water-filled pores that were connected to the pore network decreased in volume while the overall connected pore volumetric fraction was not affected. Shifts in the pore throat diameter distribution were mostly observed in pore throats ranges of 100 microns or less with no corresponding changes to the pore shape factor of pore throats. Responses of the pore network to freeze-thaw varied with aggregate, suggesting that initial pore morphology may play a role in driving freeze-thaw response. Our research suggests that freeze-thaw alters the microenvironment of permafrost aggregates during the incipient stage of deformation following permafrost thaw, impacting soil properties and function in Arctic landscapes undergoing transition. This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/Erin-Rooney/XCT-freezethaw (DOI: 10.5281/zenodo.5816355).

This dataset is about: Porosity and pore water nutrient chemistries of sediment core TT013_135.

In this paper, the fractal dimension is calculated by extracting pore parameters from SEM images and NMR experimental data, the pore structure heterogeneity in plane and space is comprehensively discussed, and the relationship between the fractal dimension and shale composition and physical parameters is discussed, providing new ideas for the study of shale reservoirs heterogeneity. Fractal dimension analysis of SEM images reveals that the shale pores of the Shanxi Formation can be divided into organic pores, inter-granular pores and micro-fractures. The average diameter of nano-scale pores is 17.13 nm to 67.65 nm, the surface porosity is 5.75% to 9.37%, and the proportion of micro-fractures is 0.36% to 0.72%, with an average value of 0.53%. The ImageJ Weka Segmentation module in ImageJ software intelligently optimizes the degree of pore recognition in SEM images to ensure accurate extraction and characterization of pore structure features. The fractal dimension of the SEM image was calculated using the Dathe formula for the identified pores: Fractal dimension of bound fluid pore (0.4922 ~ 0.9396) and fractal dimension of movable fluid (2.9727 ~ 2.989), quartz content has a negative correlation with the fractal dimension of bound fluid pores, clay mineral content has a positive correlation with the fractal dimension of bound fluid pores, NMR fractal dimension has no obvious correlation with organic matter content and maturity, and NMR fractal dimension has a negative correlation with porosity, but has no obvious correlation with permeability: indicating that NMR fractal dimension is mainly affected by the composition of shale minerals; The Shanxi Formation shale has a high degree of evolution but the organic matter pores are not developed. The reservoirs space is mainly provided by inter-granular pores and micro-fractures; the inter-granular pores and micro-fractures have high heterogeneity and poor connectivity leads to low permeability.This paper attempts to use the ImageJ Weka Segmentation module to intelligently optimize the identification of pores, which improves the efficiency and accuracy of pore identification. At the same time, it combines the fractal dimension of SEM images and the fractal dimension of NMR images to characterize reservoir characteristics, which provides a basis for quantitatively describing the irregularity of shale pore morphology.

Abstract: The design of resilient offshore structures requires knowledge of the prevailing seabed dynamics under wave-induced and structural loading. In particular, seabed liquefaction as one of the most severe forms of seabed dynamics must be understood to prevent structural failure. Progressing towards such knowledge and insights, this dataset comprises the data of a unique large scale experimental test campaign of the wave-structure-soil interaction and seabed liquefaction in the large wave-current flume, GWK+, at the Coastal Research Centre, Hannover, Germany. For the study, a 1 m x 6 m x 5m (depth x length x width) soil pit has been set up in the flume, filled with fine sand with of D50=0.066 mm, and exposed to waves of varying wave heights, as well as structural loading from a floating offshore wind turbine. This particular dataset includes measurements of the surface elevation measured with four wire-gauge in-house wave-gauges, 16 pore pressure transducers, mooring line loads in four mooring cables, six degree-of-freedom (DoF) displacement data, wind load data, as well as echo-sounder measurements of the anchor displacement.

This repository contains data files for the manuscript : Ge et al. (2024) "Modeling the evolution of pore pressure from deep wastewater injection in the Midland Basin, Texas" submitted to the AAPG Bulletin Special Issue: The geology of injection-induced earthquakes in the Midland Basin region on 01/2024, accepted 04/2024. The repository contains an Excel file with information of model parameters and pressure grids.