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

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 (ADG IA ) on the surface and the separation of paste (d Paste ) 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.

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Publication Details

Journal
Case Studies in Construction Materials
Published
2024-11-15
DOI
https://doi.org/10.1016/j.cscm.2024.e03973
Citations
4
Primary Topic
Innovations in Concrete and Construction Materials
Type
article
Field-Weighted Citation Impact
1.06
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article

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

Max Coenen, Michael Haist, Tobias Schack
4 citations
Case Studies in Construction Materials
Innovations in Concrete and Construction Materials
1.06
article

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

Max Coenen, Michael Haist, Tobias Schack
article en
4 citations

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 (ADG IA ) on the surface and the separation of paste (d Paste ) 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.

Case Studies in Construction MaterialsVol. 21
Leibniz University Hannover (DE)
Sustainable cities and communities
Openalex Percentile: Top 24%
Innovations in Concrete and Construction Materials
1.06
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