This study presents a method to stochastically generate a PTL composed of sintered titanium (Ti) powders and investigate the transport properties using pore network modeling. A microscale X-ray computed tomography (µ-CT) was performed for a sintered Ti powder PTL sample to obtain a 2D density map. The density map contains material content information, providing higher intensity at the positions with higher material content. With the density map as an input, a stochastic model of the PTL was generated by placing Ti powder particles at positions decided by the density map and a probability function until the model reached the target volume (2). Two critical parameters are considered in this model: the seeding parameter, α, and a filling radius, β. The seeding parameter controls the number of Ti powder “seeds” that act as nucleation sites. The second parameter, the filling radius, allows the model to mimic the morphology of the sintered regions. The structural properties of the stochastic model are investigated by comparing the pore size distribution, throat size distribution, and the porosity profile to the µ-CT reconstruction.
Pore network modeling is an alternative to continuum modeling for simulating transport in porous media. Pore network modeling simplifies the solution of differential equations for mass transport by treating the pore space as a network of pores and narrow throats (3). Using pore network modeling as the analysis tool, the in-plane permeabilities of the µ-CT reconstruction and the stochastic model were compared.
The stochastic modeling of PTLs will facilitate the detailed parametric studies of PTL structural property impacts on transport and provide novel insights into mass transport behavior in PEM electrolyzers.
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