Integrating Experimental and Theoretical Investigations of Porous Graphite Materials with Scanning Electron Microscope Image Processing

Abstract

Accurate determination of fractal dimension (FD) and permeability of porous graphite materials (PGM) is essential for applications like porous aerostatic bearings (PABs). This study addresses the need for improved measurement methods by employing image processing and computer vision (IPCV) techniques to enhance FD and permeability accuracy. We aimed to refine these measurements by analysing the effects of image size and magnification on accuracy. The research developed theoretical models based on fractal theory, Darcy's law, and a modified Hagen-Poiseuille gas equation to evaluate these effects. A dual-path X-ray imaging detection system was used for experimental validation. The gauge pressure was varied across the surface of the PGM and volume flow rate was measured. MATLAB was utilized for IPCV, enabling precise FD determination and underscoring the importance of image parameters. Results showed that FD values stabilize at specific image sizes and magnifications, improving accuracy. Linear relationships between pressure gradient and volume flow rate were observed, with permeability stabilizing at high pressures. Porosity values varied among materials: Toyo Carbon (15%), SGL Graphite (17%), Super Carbon Graphite (27%), and poplar porous (30%). FD obtained through theoretical and scanning electron microscope (SEM) methods had a maximum error of 0.08. The study also found a positive correlation between relative density and image grayscale at the macroscopic level. The findings emphasize the importance of optimizing image size and clarity for accurate PGM analysis, providing crucial insights for PAB design and other advanced applications.