2012
DOI: 10.1016/j.ijengsci.2012.03.030
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Digital material laboratory: Wave propagation effects in open-cell aluminium foams

Abstract: This 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 labora… Show more

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Cited by 7 publications
(7 citation statements)
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“…Comparing the experimental investigations with the high-frequency limit of Biot's equations, we are able to determine the tortuosity parameter of the used aluminium foam, cf. [1][2][3]. As we assume that the tortuosity is the only physical effect responsible for the time delay between the reference and signal, we obtain a tortuosity factor of α ∞ = 1.054 for the aluminium foam.…”
Section: Results and Conclusionmentioning
confidence: 92%
See 1 more Smart Citation
“…Comparing the experimental investigations with the high-frequency limit of Biot's equations, we are able to determine the tortuosity parameter of the used aluminium foam, cf. [1][2][3]. As we assume that the tortuosity is the only physical effect responsible for the time delay between the reference and signal, we obtain a tortuosity factor of α ∞ = 1.054 for the aluminium foam.…”
Section: Results and Conclusionmentioning
confidence: 92%
“…For the experimental study, we have used 20 ppi AlSi7Mg-foams of different thickness and porositiy around 94 % by m.pore GmbH [3]. The specimens had an open cell structure enabling a full saturation of the foams with air or water.…”
Section: Methodsmentioning
confidence: 99%
“…Multiple techniques have been used to obtain theoretical and computational models that may be used to study the properties of porous materials, such as: models of regular arrays of polyhedra (Kelvin cells [4,10,11,[13][14][15]17,23] and Weaire-Phelan cells [6]), random tessellation models [13,16,21], 3D image-based models [18][19][20]22], and 1D image-based models ( [8]). However, given the scope of this research, we will focus on reviewing (1) image-based models (1D, and 3D) and (2) models of regular arrays of Kelvin cells.…”
Section: Literature Reviewmentioning
confidence: 99%
“…1. Image-based models: These models take a set of images (commonly from a X-ray computed tomography (CT) [8,[18][19][20]22]) of an actual foam sample to obtain an accurate computational representation of the domain of study. The images are processed to retrieve a 3D representation of the foam and to generate its respective FE model [7].…”
Section: Literature Reviewmentioning
confidence: 99%
“…Furthermore, the accuracy of HPM for 5 modelling of surface waves is higher than the finite difference method with rotated staggered grids . These features could allow us to efficiently calculate not only strong ground motion induced by earthquakes (Takekawa et al, 2012) but also the scattering of seismic waves by fractures (Okamoto et al, 2013) and other applications in material science and engineering (Saenger et al, 2012).…”
Section: Introductionmentioning
confidence: 99%