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71 results for “Porous media”
A framework for pore-scale simulation of broadband electrical conductivity and permittivity of porous media
<p>The data presented in a manuscript entitled "A framework for pore-scale simulation of electrical conductivity and permittivity of porous media in the frequency range from mHz to GHz" to be submitted to Journal of Geophysical Research: Solid Earth.</p>
Brine Drying and Salt Precipitation in Porous Media: A Microfluidics Study
<p>This is a dataset of the data used for the research "Brine Drying and Salt Precipitation in Porous Media: A Microfluidics Study'', including all the test images, the images used for U-net training, and the data for figures.</p>
Videos for: Modeling 2D gravity-driven flow in unsaturated porous media for different infiltration rates
<p>This dataset contains videos of transient flow simulations in unsaturated porous media flow related to the manuscript: Modeling 2D gravity-driven flow in unsaturated porous media for different infiltration rates.</p>
Reactive Transport in Heterogeneous Porous Media Under Different Peclet Numbers
<p>In our recent paper “Reactive Transport in Heterogeneous Porous Media Under Different Peclet Numbers“, we study the synergistic effects of the Peclet number and the length scale of medium heterogeneity on the evolution of bimolecular reactive transport between mobile and immobile species. We performed a suite of numerical simulations at the Darcy scale that quantify the instantaneous, irreversible bimolecular reaction , under various transport conditions (Peclet numbers) and porous media configurations (correlation lengths).</p> <p> </p> <p><strong>Numerical Methods</strong></p> <p>We used the following steps to obtain the results:</p> <p>1. Generation of the hydraulic conductivity fields – we used a widely tested sequential Gaussian simulator (Gómez-Hernández & Journel, 1993). The software is written in C and available to download via <a href="https://wiki.52north.org/AI_GEOSTATS/SWGCOSIM3D">https://wiki.52north.org/AI_GEOSTATS/SWGCOSIM3D</a>. In the file ‘real20.mat’, we show an example of the generated 20 realizations, from the software, for <span class="math-tex">\(\ell\)</span>=1 ,<span class="math-tex">\(\sigma^2\)</span>=1. </p> <p>2. Determination of the flow field – we solve the Darcy equation (for each of the hydraulic conductivity fields), using an open-source code MRST (Lie, 2016). The software is available to download via <a href="https://www.sintef.no/projectweb/mrst/">https://www.sintef.no/projectweb/mrst/</a>. In the file ‘real20_solutions.mat’, we show the flow field solutions (for the different realizations from ‘real20.mat’) under different Peclet numbers. For each realization and Peclet, we store the solution of the velocity components (first column), the velocity magnitude (second column) and the hydraulic conductivity field (third column).</p> <p>3. Chemical transport – was modeled through the Langevin equation, where movement by advection and diffusion were taken into account. Chemical reaction between the different chemical species was modeled via the reaction-radius approach (Edery, Porta, Guadagnini, Scher, & Berkowitz, 2016).</p> <p><br> <strong>Results</strong></p> <p>The data of the published figures can be download from the following files:</p> <p><strong>Fig2.txt</strong> -- processed simulation results shown in Figure 2.</p> <p><strong>Fig3.txt</strong> -- processed simulation results shown in Figure 3a,b.</p> <p><strong>Fig4.txt </strong>-- processed simulation results shown in Figure 4.</p> <p><strong>Fig5.txt </strong>-- processed simulation results shown in Figure 5.</p> <p><strong>FigS1.png </strong>-- First and second statistical moments of the generated conductivity fields, for different correlation lengths. The left axis displays the first moment of the generated fields (ln(K)), and the right axis shows the second moment (ln)). The small circles represent individual realizations, and the large circles indicate the mean value among realizations.</p> <p><strong>FigS2.png </strong>-- Sensitivity analysis of the power law parameters (a) and (b) (see equation (1) in the main text), among realizations; mean values are represented by gray circles, and the standard deviations by the vertical black lines. (c) and (d) show the standard deviations of (a) and (b), respectively, in percentage. Note that among the different realizations, the standard deviation does not exceed 3%. </p> <p> </p> <p><strong>References</strong></p> <p>[1] Edery, Y., Porta, G. M., Guadagnini, A., Scher, H., & Berkowitz, B. (2016). Characterization of Bimolecular Reactive Transport in Heterogeneous Porous Media. Transport in Porous Media. https://doi.org/10.1007/s11242-016-0684-0</p> <p>[2] Gómez-Hernández, J. J., & Journel, A. G. (1993). Joint Sequential Simulation of MultiGaussian Fields. https://doi.org/10.1007/978-94-011-1739-5_8</p> <p>[3] Lie, K.-A. (2016). User Guide for the MATLAB Reservoir Simulation Toolbox (MRST). In A. Soares (Ed.), An Introduction to Reservoir Simulation Using MATLAB. Oslo, Norway: SINTEF ICT, Department of Applied Mathematics. </p> <p> </p> <p> </p>
Data and Codes for: Segmentation uncertainty of vegetated porous media propagates during X-ray CT image-based analysis
<p>Phase segmentation is a crucial step in X-ray computed tomography (CT) for image-based analysis (CT-IBA) to derive soil and root information. How segmentation uncertainty (SU) affects CT-IBA of vegetated soil has never been explored. The enclosed data and codes are used to assist the analysis of SU quantification and propagation in the journal paper published in Plant & Soil. The title of the paper is Segmentation uncertainty of vegetated porous media propagates during X-ray CT image-based analysis. </p>
Viscous fingering in fractured porous media
<p>Data from numerical simulations of viscous fingering in fractured porous media.</p> <p>The folder structure of the dataset is given as follows:</p> <p>res_NAME_OF_FRACTURE_GEOMETRY/NAME_OF_VARIABLE/csv/DATA_FILES.</p> <p>The name of the DATA_FILES gives the values of the dimensionless parameters used in the simulation that generated the datafile. The last part of the name (*_task_TASKNUMBER_run_RUNNUMBER.csv) is an identifyer for the simulation and can for most purposes be ignored.</p> <p>The first line of each file is the header with items:</p> <ul> <li>time (dimensionless time of time-step)</li> <li>average_c (the volume averaged concentration in the simulation domain)</li> <li>L05 (the mixing region length in fractures and rock matrix with treshold c<0.05)</li> <li>Lm05 (the mixing region length in rock matrix with treshold c<0.05)</li> <li>Lf05 (the mixing region length in fractures with treshold c<0.05)</li> <li>L01 (the mixing region length in fractures and rock matrix with treshold c<0.01)</li> <li>Lm01 (the mixing region length in rock matrix with treshold c<0.01)</li> <li>Lf01 (the mixing region length in fractures with treshold c<0.01)</li> <li>L001 (the mixing region length in fractures and rock matrix with treshold c<0.001)</li> <li>Lm001 (the mixing region length in rock matrix with treshold c<0.001)</li> <li>Lf001 (the mixing region length in fractures with treshold c<0.001)</li> <li>num_fingers (the number of fingers in the domain)</li> </ul> <p>Each successive line gives the results of a time-step in the simulation.</p> <p> </p>
Data from: Unstable infiltration experiments in dry porous media
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Water Film Thickness in Unsaturated Porous Media: Effect of Pore Size, Pore Solution Chemistry, and Mineral Type
<p>Data set used in figures.</p>
Modeling and Experimental Study of The Effect of Pore Water Velocity on the Spectral Induced Polarization Signature in Porous Media - Dataset
<p>Readme file is attached to every zip file.</p>
Reconstruction software: 4D imaging of two-phase flow in porous media using laboratory-based micro-Computed Tomography
<p>This repository contains the dataset and the computed tomography (CT) reconstruction software used in the journal article "4D imaging of two-phase flow in porous media using laboratory-based micro-Computed Tomography". </p>
Opendata for the manuscript"Study on permeability for random packed porous media using lattice Boltzmann method"
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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