2005
DOI: 10.1016/j.compscitech.2005.04.008
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Micro-CT characterization of variability in 3D textile architecture

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Cited by 236 publications
(132 citation statements)
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“…Experimental studies [1][2][3][4] show the scatter in measured global permeability data can be up to 0.5 in terms of coefficient of variation from batch to batch of the same material.…”
Section: Introductionmentioning
confidence: 99%
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“…Experimental studies [1][2][3][4] show the scatter in measured global permeability data can be up to 0.5 in terms of coefficient of variation from batch to batch of the same material.…”
Section: Introductionmentioning
confidence: 99%
“…Although studies have been performed on the probabilistic characterization of the random transport properties of fibrous media [2][3][4], the random effects are usually neglected in the available optimization or on-line control schemes [5][6][7] which employ common simulation softwares for mold filling. Available stochastic studies in the RTM context [8][9][10][11][12] mostly depend on the Monte Carlo simulation (MCS), which is computationally expensive for a fast uncertainty analysis or to be combined with other algorithms for optimization or sensitivity analysis.…”
Section: Introductionmentioning
confidence: 99%
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“…Analytical prediction of the through-thickness permeability requires geometrical characterization of flow channels formed in the respective fabric structure. While X-ray micro-Computed Tomography (-CT) can be used for scanning the internal architecture of 3D materials [12][13][14][15] , as illustrated in Figure 1c and d, data used for permeability prediction were obtained using optical microscopy.…”
Section: Introductionmentioning
confidence: 99%
“…As the technology becomes more readily available, with increased computing power and storage space at lower costs, it is envisioned that more and more cost-effective and feasible industrial CT applications will emerge. In the academic research environment, industrial CT scanning has been applied in many diverse fields, including geology [4,5], archaeology [6], forensic science [7], forestry and wood science [2,8], biology [1,9], soil science [10], composite science [11], and mechanical and electronic engineering [12,13].…”
Section: Introductionmentioning
confidence: 99%