Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 15th fib International PhD Symposium in Civil Engineering, 2024 |
| Editors | György L. Balázs, Sándor Sólyom, Stephen Foster |
| Publisher | fib. The International Federation for Structural Concrete |
| Pages | 1235-1242 |
| Number of pages | 8 |
| ISBN (print) | 9782940643240 |
| Publication status | Published - 28 Aug 2024 |
| Event | 15th fib International PhD Symposium in Civil Engineering, 2024 - Budapest, Hungary Duration: 28 Aug 2024 → 30 Aug 2024 |
Publication series
| Name | fib Symposium Proceedings |
|---|---|
| ISSN (Print) | 2617-4820 |
Abstract
The workability of fresh concrete is besides its compressive strength one of its most crucial characteristics. Inappropriate rheological properties can lead to serious problems such as segregation, flow blockage or void formation in the structure being cast. Therefore, quality control of fresh concrete prior to pouring is of great importance. Current quality control methods are primarily batch-based empirical test methods, such as the spread-flow or the slump test. More advanced rheometer tests can offer a deeper understanding of the rheological properties of concrete. However, these latter tests are also batch based and highly challenging in data evaluation. This paper presents a new approach for an automated digital concrete quality control using computer-vision based analysis methods. In a unique experimental setup, the flow behaviour of mortars and concretes down an inclined open channel is studied using a camera setup. Variations of the material’s rheological properties manifest itself in different flow behaviours which can be optically detected. By utilizing dense optical flow methods, rheological parameters are determined from the acquired images. The developed method is part of the planned doctoral thesis of the submitter which intends to provide automated tools for concrete quality control. The paper examines analytical and artificial intelligence based approaches to obtain the materials rheological parameters out of the acuired images. The results indicate that the computed flow behaviour of the investigated mixtures is highly correlated with their rheology.
ASJC Scopus subject areas
- Engineering(all)
- Civil and Structural Engineering
- Engineering(all)
- Building and Construction
- Materials Science(all)
- Materials Science (miscellaneous)
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Proceedings of the 15th fib International PhD Symposium in Civil Engineering, 2024. ed. / György L. Balázs; Sándor Sólyom; Stephen Foster. fib. The International Federation for Structural Concrete, 2024. p. 1235-1242 (fib Symposium Proceedings).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Image-based analysis of fresh concrete open-channelflow for obtaining rheological properties
AU - Vogel, Christian
AU - Coenen, Max
AU - Schack, Tobias
AU - Haist, Michael
N1 - Publisher Copyright: © Fédération Internationale du Béton–International Federation for Structural Concrete.
PY - 2024/8/28
Y1 - 2024/8/28
N2 - The workability of fresh concrete is besides its compressive strength one of its most crucial characteristics. Inappropriate rheological properties can lead to serious problems such as segregation, flow blockage or void formation in the structure being cast. Therefore, quality control of fresh concrete prior to pouring is of great importance. Current quality control methods are primarily batch-based empirical test methods, such as the spread-flow or the slump test. More advanced rheometer tests can offer a deeper understanding of the rheological properties of concrete. However, these latter tests are also batch based and highly challenging in data evaluation. This paper presents a new approach for an automated digital concrete quality control using computer-vision based analysis methods. In a unique experimental setup, the flow behaviour of mortars and concretes down an inclined open channel is studied using a camera setup. Variations of the material’s rheological properties manifest itself in different flow behaviours which can be optically detected. By utilizing dense optical flow methods, rheological parameters are determined from the acquired images. The developed method is part of the planned doctoral thesis of the submitter which intends to provide automated tools for concrete quality control. The paper examines analytical and artificial intelligence based approaches to obtain the materials rheological parameters out of the acuired images. The results indicate that the computed flow behaviour of the investigated mixtures is highly correlated with their rheology.
AB - The workability of fresh concrete is besides its compressive strength one of its most crucial characteristics. Inappropriate rheological properties can lead to serious problems such as segregation, flow blockage or void formation in the structure being cast. Therefore, quality control of fresh concrete prior to pouring is of great importance. Current quality control methods are primarily batch-based empirical test methods, such as the spread-flow or the slump test. More advanced rheometer tests can offer a deeper understanding of the rheological properties of concrete. However, these latter tests are also batch based and highly challenging in data evaluation. This paper presents a new approach for an automated digital concrete quality control using computer-vision based analysis methods. In a unique experimental setup, the flow behaviour of mortars and concretes down an inclined open channel is studied using a camera setup. Variations of the material’s rheological properties manifest itself in different flow behaviours which can be optically detected. By utilizing dense optical flow methods, rheological parameters are determined from the acquired images. The developed method is part of the planned doctoral thesis of the submitter which intends to provide automated tools for concrete quality control. The paper examines analytical and artificial intelligence based approaches to obtain the materials rheological parameters out of the acuired images. The results indicate that the computed flow behaviour of the investigated mixtures is highly correlated with their rheology.
UR - http://www.scopus.com/inward/record.url?scp=85216770550&partnerID=8YFLogxK
UR - https://www.fib-international.org/components/com_virtuemart/views/download/tmpl/stream.php?time=1739448508&hash=475971c796ac044ff890ef96afa0b1eb0b3ae90d1be0077f124358540f91a17c&file=%2FFIBPRO-0066-2024-E-15th-PhD-Symposium-in-Budapest-Hungary.pdf
M3 - Conference contribution
AN - SCOPUS:85216770550
SN - 9782940643240
T3 - fib Symposium Proceedings
SP - 1235
EP - 1242
BT - Proceedings of the 15th fib International PhD Symposium in Civil Engineering, 2024
A2 - Balázs, György L.
A2 - Sólyom, Sándor
A2 - Foster, Stephen
PB - fib. The International Federation for Structural Concrete
T2 - 15th fib International PhD Symposium in Civil Engineering, 2024
Y2 - 28 August 2024 through 30 August 2024
ER -