Examinando por Materia "PERMEABILIDAD"
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Ítem Digital material laboratory: Wave propagation effects in open-cell aluminium foams(Elsevier, 2012-09) Saenger, E.H.; Uribe, D.; Jänicke, R.; Ruíz, O.; Steeb, H.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEThis paper is concerned with numerical wave propagation effects in highly porous media using digitized images of aluminum foam -- Starting point is a virtual material laboratory approach -- The Aluminum foam microstructure is imaged by 3D X-ray tomography -- Effective velocities for the fluid-saturated media are derived by dynamic wave propagation simulations -- We apply a displacement-stress rotated staggered fnite-difference grid technique to solve the elastodynamic wave equation -- The used setup is similar to laboratory ultrasound measurements and the computed results are in agreement with our experimental data -- Theoretical investigations allow to quantify the influence of the interaction of foam and fluid during wave propagation – Together with simulations using an artificial dense foam we are able to determine the tortuosity of aluminum foamÍtem Estimation of large domain Al foam permeability by Finite Difference methods(WILEY-VCH Verlag, 2013) Osorno, María; Steeb, Holger; Uribe, David; Ruíz, Óscar; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEClassical methods to calculate permeability of porous media have been proposed mainly for high density (e.g. granular) materials -- These methods present shortcomings in high porosity, i.e. high permeability media (e.g. metallic foams) -- While for dense materials permeability seems to be a function of bulk properties and occupancy averaged over the volume, for highly porous materials these parameters fail to predict it -- Several authors have attacked the problem by solving the Navier-Stokes equations for the pressure and velocity of a liquid flowing through a small domain (Ωs) of aluminium foam and by comparing the numerical results with experimental values (prediction error approx. 9%) -- In this article, we present calculations for much larger domains (ΩL) using the Finite Difference (FD) method, solving also for the pressure and velocity of a viscous liquid flowing through the Packed Spheres scenario -- The ratio Vol(ΩL)/Vol(Ωs) is around 103 -- The comparison of our results with the Packed Spheres example yields a prediction error of 5% for the intrinsic permeability -- Additionally, numerical permeability calculations have been performed for Al foam samples -- Our geometric modelling of the porous domain stems from 3D X-ray tomography, yielding voxel information, which is particularly appropriate for FD -- Ongoing work concerns the reduction in computing times of the FD method, consideration of other materials and fluids, and comparison with experimental dataÍtem Numerical estimation of Carbonate properties using a digital rock physics workflow(2014) Osorno, M.; Uribe, D.; Saenger, E.H.; Madonna, C.; Steeb, H.; Ruíz, Ó.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Laboratorio CAD/CAM/CAEDigital rock physics combines modern imaging with advanced numerical simulations to analyze the physical properties of rocks -- In this paper we suggest a special segmentation procedure which is applied to a carbonate rock from Switzerland -- Starting point is a CTscan of a specimen of Hauptmuschelkalk -- The first step applied to the raw image data is a nonlocal mean filter -- We then apply different thresholds to identify pores and solid phases -- Because we are aware of a nonneglectable amount of unresolved microporosity we also define intermediate phases -- Based on this segmentation determine porositydependent values for the pwave velocity and for the permeability -- The porosity measured in the laboratory is then used to compare our numerical data with experimental data -- We observe a good agreement -- Future work includes an analytic validation to the numerical results of the pwave velocity upper bound, employing different filters for the image segmentation and using data with higher resolution