  Porous materials are ubiquitous in various engineering and geological
applications, where their permeability plays a critical role in viscous fluid
flow and transport phenomena. Understanding and characterizing the microscale
properties, the effective hydraulic parameters, and also the anisotropy of
porous materials are essential for accurate modeling and predicting fluid flow
behavior. The study pursues the Digital Rock Physics approach to retrieve
intrinsic permeability and its evolution in anisotropic configurations of
porous media, which are subjected to pore space alterations. Therefore, we
discuss the development and implementation of a computational framework based
on the finite difference method to solve the pseudo-unsteady Stokes equations
for fluid flow on the pore scale. We present an efficient and highly
parallelized implementation of this numerical method for large voxel-based data
sets originating from different image-based experimental setups. A
comprehensive variety of benchmarks has been conducted to assess and evaluate
the performance of the proposed solver. The solver's compatibility with huge
domain sizes generated by state-of-the-art imaging techniques is demonstrated.
We investigate an open-cell foam undergoing deformation, observing that
contrary to initial expectations, no anisotropy emerges. Further, we examine a
microfluidic cell experiencing precipitation within its pore space, resulting
in clear anisotropic development during the clogging process.
