A novel method to predict the mesostructure and performance of pervious concrete

The permeability and compressive strength of pervious concrete are mainly determined by its mesostructures including the pore, cement paste and aggregate. However, most of the current performance prediction methods have not considered the influence of mesostructural characteristics on the performance reasonably and comprehensively. In this study, a novel method based on image processing techniques was proposed to predict the mesostructures of pervious concrete. Experiments were designed to validate the effectiveness and accuracy of the proposed mesostructure prediction method. Furthermore, the prediction models of the permeability and compressive strength are proposed using the predicted characteristics of cement paste distribution. This study provides a novel method that can predict the mesostructures of pervious concrete with various mix design without repeated X-ray scanning, reducing the time and cost of trials. Compared to the reported correlation models between performance and pore characteristics, the proposed models can predict the performance accurately.