The understanding of the correlation between a pore-scale structure and its coupled diffusion transport property is crucial in the virtual design and performance optimization of porous fibrous material for various energy applications. Two most common and widely employed pore-scale modeling techniques are the lattice Boltzmann method (LBM) and the pore network modeling (PNM). However, little attention has been paid to the direct comparison between these two methods. To this end, stochastic porous fibrous structures are reconstructed reflecting the structural properties of the fibrous porous material on a statistical level with structural properties obtained from X-ray computed microtomography. Diffusion simulation through the porous phase was subsequently conducted using LBM of D3Q7 lattice and topological equivalent PNM derived from the watershed method, respectively. It is detected that the effective diffusion coefficients between these two methods are in good agreement when the throat radius in the pore network is estimated using the cross-section area equivalent radius. Like most literature, the diffusivity in the in-plane (IP) direction is larger than in the through-plane (TP) direction due to the laid fiber arrangement, but the values are very close. Besides, tortuosity was evaluated from both geometry and transport measurements. Tortuosity values deduced from both methods are in line with the anisotropy of the diffusion coefficients.

A skeleton-based fiber tracing algorithm is described and applied on a specific fibrous material, porous metal fiber sintered sheet (PMFSS), featuring high porosity and curved fibers. The skeleton segments are firstly categorized according to the connectivity of the skeleton paths. Spurious segments like fiber bonds are detected making extensive use of the distance transform (DT) values. Single fibers are then traced and reconstructed by consecutively choosing the connecting skeleton segment pairs that show the most similar orientations and radius. Moreover, to reduce the misconnection due to the tracing orders, a multilevel tracing strategy is proposed. The fibrous network is finally reconstructed by dilating single fibers according to the DT values. Based on the traced single fibers, various morphology information regarding fiber length, radius, orientation, and tortuosity are quantitatively analyzed and compared with our previous results (Wang et al., 2013). Moreover, the number of bonds per fibers are firstly accessed. The methodology described in this paper can be expanded to other fibrous materials with adapted parameters