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ZENODO
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License: CC BY
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image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2020
License: CC BY
Data sources: Datacite
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sw-octave-01: compute_permeability: Computing effective permeability from 2d images of porous media with FEM.

Authors: Pereira, Andre; Vianna, Rafael; Cunha, Alexsander; Azeredo, Rodrigo; Leiderman, Ricardo;

sw-octave-01: compute_permeability: Computing effective permeability from 2d images of porous media with FEM.

Abstract

It is an educational code developed in Octave/Matlab to compute effective permeability from 2d images of heterogeneous porous materials, by simulating a Stokes flow in the porous media modeled with periodic boundary conditions using finite elements. The code is described in the paper "Computing effective permeability of porous media with FEM and micro-CT: An educational approach" to be published in Fluids Journal (MDPI) which can be accessed by the special issue: Teaching and Learning of Fluid Mechanics: https://doi.org/10.3390/fluids5010016

{"references": ["Erik Andreassen, Casper Schousboe Andreasen (2014). How to determine composite material properties using numerical homogenization, Computational Materials Science, Volume 83, 2014, Pages 488-495, ISSN 0927-0256, https://doi.org/10.1016/j.commatsci.2013.09.006."]}

Keywords

finite element method, microstructure, homogenization, permeability, micro-CT, fluid

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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