Image‐based analysis of fresh concrete flow ‐ determining the correlation between flow behavior and rheological properties

Abstract

Besides compressive strength, the workability of fresh concrete is one of the most important characteristics of concrete. Only by adapting the rheology of the fresh concrete to the geometry of the element to be casted, the formation of air voids and damages can be avoided. This holds even more so true for 3D printable concrete. Currently, empirical test methods such as the slump test are used to determine rheological parameters. Rheometer tests, on the other hand, allow a much deeper insight into the rheological properties of concrete but are more challenging. Further, all currently available test methods can only be applied on a batch basis.In the paper at hand, a new approach for an automatic digital concrete quality control is presented using modern computer‐vision based analysis methods. Using a newly developed experimental setup, the flow of mortar down an inclined open channel is studied using a monocular camera setup. Differences in the mortar's rheology result in different flow behaviors which can be optically detected. Utilizing dense optical flow, rheological parameters are determined from the acquired monocular image sequences. The results shown in this paper prove that the computed flow behavior of the investigated mortars precisely correlates with their rheological properties, demonstrating the high potential of the method for an automated in‐line testing of fresh concrete e.g. during the discharge of a mixing truck.