Abstract
This work presents a method to 1) statistically characterize the complex geometry of porous material microstructures, 2) parameterize these random microstructures into statistically condense, feature rich metrics, and 3) relate these metrics to material properties such as permeability. This method is applied to porous synthetic cordierite and aluminum titanate materials covering a range of 40%-70% porosity and 8-18 μm median pore size (as measured by mercury intrusion porosimetry), using X-ray computed tomography images of the porous microstructure. Direct simulations of the microstructures were made to estimate effective permeability and correlations are presented to microstructural metrics. High quality relationships are established, specifically utilizing 2-point correlation functions and lineal path function characteristic dimensions. Results are compared to legacy methods such as the widely known relationships proposed by Kozeny-Carman and Kuwabara.
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