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Distribution of flow-induced stresses in highly porous media
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Image of FIG. 1.
FIG. 1.

Comparison of the pdf (, , and ) with experimentally and computationally obtained pdfs for : Fig. 7 (from Ref. 11) using Doppler optical coherence tomography for chitosan scaffolds prepared via freeze-drying, at 0.5 ml/min (triangles—90% porous, pore size and circles—85% porous, pore size); Fig. 5 (from Ref. 9) using Fluent finite volume code for PolyActive®/PEGT/PBT 80% porous and average pore size scaffolds prepared via compression molding (green: 0.03 ml/min; black: 0.3 mL/min, smoothed using Loess method); Fig. 6a (from Ref. 10) using OpenFOAM: icoFoam finite volume code for collagen-glycosaminoglycan ( average pore size, 90.5%–99% porosity) scaffolds; LBM data from our laboratory for a PLLA nonwoven fiber mesh scaffold with 85% porosity and an average fiber diameter of . Data from other laboratories were extracted using DATATHEIF V1.5.

Image of FIG. 2.
FIG. 2.

Left: comparison of an experimentally obtained dimensional pdf from Fig. 7 (Ref. 11). Right: comparison of a computationally obtained dimensional pdf from Fig. 5 (Ref. 9) with the predicted dimensional stress pdf obtained with the methodology suggested in this letter (solid line).


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Table I.

Levels of significance for data from different laboratories at which the null hypotheses that “the standardized dimensionless stress distribution is described by the distribution” and “the predicted dimensional stress distribution is described by the distribution” cannot be rejected. [Data from Fig. 5(a) in Ref. 9 is smoothed using Loess method.]


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Distribution of flow-induced stresses in highly porous media