Recycled aggregate porous concrete: Pore structure, clogging properties and models.

The issue of clogging in porous concrete (PC) pavements has been a significant concern. This study investigated the impact of various design porosities (20%, 25%, 30%) and different areas (commercial, traffic, residential, and park) on the clogging performance of recycled aggregate porous concrete (RAPC) using clogging materials. Image analysis and computer image processing techniques were utilized to examine the pore structure. Clogging tests were conducted using a custom-made permeability experimental apparatus to assess the changes in the permeability coefficient, permeability loss rate, and permeability recovery rate of RAPC. Additionally, a clogging model based on pore structure parameters was developed. The findings indicate a strong linear correlation between the permeability coefficient and RAPC planar porosity, perimeter, specific surface area, and average shape factor, as well as a quadratic polynomial relationship with composite pore structure parameters. The correlation coefficient exceeds 0.95. The permeability coefficient of RAPC decreases gradually with an increasing number of cloggings, while the recovery rate of the permeability coefficient initially decreases rapidly with an increasing number of backwashings before gradually stabilizing. The regression correlation coefficient exceeds 0.80, indicating that the RAPC clogging process follows an exponential decay pattern and can predict the permeability coefficient of RAPC after clogging. A prediction model for the RAPC permeability coefficient under cyclic clogging-rinsing was developed using surface regression analysis, yielding a coefficient of determination (R 2 ) of approximately 0.90. This study offers insights for addressing the clogging issue in RAPC. • Clogging in porous concrete: Impact of porosity & areas on performance. • Strong correlations: permeability-coefficient and pore structure parameters. • Development of a clogging model based on pore structure parameters. • Prediction model developed for RAPC permeability under clogging-rinsing. [ABSTRACT FROM AUTHOR]