Digital sieving of pervious concrete air voids using X-ray computed tomography

摘要

The design and quality assessment of the pervious concrete mixtures based on its structural and functional performance are greatly influenced by the microstructural properties of the internal pore structure. The main objective of this study is to investigate the internal pore structure properties of two different pervious concrete mixtures (gap graded mixtures with nominal maximum aggregate sizes including 9.5mm and 12.5mm) using X-Ray computed tomography and digital image processing. Image segmentation algorithms based on the histogram and laboratory volumetric characteristics of the pervious concrete mixtures have been utilised for the CT scan images. The key microstructural parameters of the air voids such as effective porosity, pore volume distribution, surface area distribution, elongation, flatness and shape factor distributions of the two different mixtures. It is expected that the developed procedure will serve as a valuable tool with potential applications in the current design methods of the pervious concrete pavements.