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Updated: Jun 22, 2026

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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
Published on: February 23, 2018
Permeability calculations in three-dimensional isotropic and oriented fiber networks
Summary
Calculating hydraulic permeability in 3D fiber networks is crucial. This study found that fiber volume fraction and orientation significantly impact permeability, more so than local network structure, using a volume-averaging method.
Area of Science:
- Fluid Dynamics
- Materials Science
- Computational Mechanics
Background:
- Hydraulic permeability of fiber networks is vital for numerous applications.
- Limited research exists on permeability calculations in three-dimensional random networks.
- Direct simulation of flow through artificial networks is computationally intensive for large scales.
Purpose of the Study:
- To develop a correlation for permeability based on fiber properties (volume fraction, radius, orientation).
- To compare direct finite element calculations with volume-averaging theories for various fiber network configurations.
- To assess the impact of fiber volume fraction and orientation on network permeability.
Main Methods:
- Direct permeability calculations using the finite element method on artificial fiber networks.
- Volume-averaging theory applied to flows parallel and perpendicular to fibers.
- Comparison of results using drag coefficients for isolated fibers versus spatially periodic arrays.
Main Results:
- The finite element model validated well against analytical solutions for structured fiber arrays.
- Volume-averaging methods showed good agreement with direct calculations when using drag coefficients for periodic arrays.
- Using drag coefficients for isolated fibers overpredicted permeability in the studied range.
Conclusions:
- A weighted combination of drag coefficients for spatially periodic fiber arrays provides a good approximation for network permeability.
- Fiber volume fraction and orientation are more dominant factors influencing permeability than local network structure.
- This work offers a more computationally feasible approach to estimating fiber network permeability.
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