Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | e03973 |
| Fachzeitschrift | Case Studies in Construction Materials |
| Jahrgang | 21 |
| Frühes Online-Datum | 15 Nov. 2024 |
| Publikationsstatus | Veröffentlicht - Dez. 2024 |
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.
ASJC Scopus Sachgebiete
- Werkstoffwissenschaften (insg.)
- Werkstoffwissenschaften (sonstige)
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in: Case Studies in Construction Materials, Jahrgang 21, e03973, 12.2024.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Digital Slump Flow
T2 - Image-based assessment of fresh concrete homogeneity as part of the slump flow test
AU - Schack, Tobias
AU - Coenen, Max
AU - Haist, Michael
N1 - Publisher Copyright: © 2024 The Authors
PY - 2024/12
Y1 - 2024/12
N2 - 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.
AB - 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.
KW - Digital quality control
KW - Homogeneity
KW - Image-based method
KW - Photogrammetric computer vision
KW - Slump flow test
UR - http://www.scopus.com/inward/record.url?scp=85209071592&partnerID=8YFLogxK
U2 - 10.1016/j.cscm.2024.e03973
DO - 10.1016/j.cscm.2024.e03973
M3 - Article
AN - SCOPUS:85209071592
VL - 21
JO - Case Studies in Construction Materials
JF - Case Studies in Construction Materials
SN - 2214-5095
M1 - e03973
ER -