Combining geometric pore descriptors with pore network model predictions via fitted power laws improves in-sample prediction of CFD-computed air flow through paper cutouts.
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Predicting air flow in calendered paper sheets from $\mu$-CT data: combining physics with morphology
Combining geometric pore descriptors with pore network model predictions via fitted power laws improves in-sample prediction of CFD-computed air flow through paper cutouts.