Digital Slump Flow: Image-based assessment of fresh concrete homogeneity as part of the slump flow test

Abstract

Worldwide, the standardized flow table test, the slump flow test or likewise methods are applied for the characterization of the workability of fresh concrete. These methods, however, give only very limited insight into the parameters controlling the workability of the concrete and important quality factors, such as e.g. the homogeneity of the concrete, cannot be quantified at all. The paper at hand presents a novel image-based approach for the determination of the homogeneity of fresh concrete as part of the slump flow test. Photogrammetric computer vision and artificial intelligence-based algorithms are proposed for the derivation of three-dimensional and semantic representations of the fresh concrete’s slump cake. Characteristic values of the surface determined in this way are correlated with the criteria of the Visual Stability Index (VSI) according to ASTM C1611. Segregation was determined in image data by measuring the aggregate distribution gradient (ADGIA) on the surface and the separation of paste (dPaste) at the peripheral of the fresh concrete as part of the slump flow test. As shown in the results, the image-based method enables an automatic assessment of the homogeneity of fresh concretes during the flow test by deriving digital parameters related to the VSI.

Keywords

• Slump flow test
• Homogeneity
• Image-based method
• Photogrammetric computer vision
• Digital quality control