Image Analysis Applications for the Study of Segregation in Lightweight Concretes

The use of lightweight concrete allows great flexibility and cost savings when it is used in building construction having a positive impact on the energy consumption of buildings due to its good thermal characteristics. However, it is also known that the differences between the densities of the materials used to produce these concretes make it highly susceptible to the segregation phenomenon. The main objective of the present work is to present a method to quantify this phenomenon using techniques of image analysis. In this work, a lightweight concrete produced was molded in cylindrical molds using different times of internal vibration and causing different degrees of segregation. The samples were cured, vertically saw-cut in two pieces (halves) and the sections were photographed. Subsequently, the halves were saw-cut horizontally in four equal parts and posteriorly their densities were determined experimentally. The densities obtained were used to calculate the segregation index of each sample (experimental method). Furthermore, the photographed sections were processed using image analysis software in order to determine the volumetric proportions of aggregates in each sample (noise reduction, threshold adjustment, binarization and fill holes). The processed images were used to calculate the densities and segregation index of the lightweight concrete produced through image analysis. In addition, using the photographed sections, a vertical density profile was programmed to analyze the distribution of the lightweight concrete components (mortar and aggregate). Finally, the results obtained experimentally and through image analysis were compared. This study demonstrates that the image analysis allows a deeper knowledge of the behavior of segregated concrete