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

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

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OriginalspracheEnglisch
Seiten (von - bis)621-627
Seitenumfang7
Fachzeitschriftce/papers
Jahrgang6
Ausgabenummer6
PublikationsstatusVeröffentlicht - 6 Dez. 2023

Abstract

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.

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Image-based analysis of fresh concrete flow: determining the correlation between flow behavior and rheological properties. / Vogel, Christian; Coenen, Max; Schack, Tobias et al.
in: ce/papers, Jahrgang 6, Nr. 6, 06.12.2023, S. 621-627.

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

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title = "Image-based analysis of fresh concrete flow: determining the correlation between flow behavior and rheological properties",
abstract = "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.",
keywords = "fresh concrete, open channel flow, rheology, digitization, quality control, dense optical flow",
author = "Christian Vogel and Max Coenen and Tobias Schack and Dries Beyer and Michael Haist",
note = "The authors kindly acknowledge the funding of this project provided by Deutsche Forschungsgemeinschaft (DFG) un-der the grant No. 452024049. The authors declare no con-flict of interest.",
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month = dec,
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doi = "10.1002/cepa.2916",
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Download

TY - JOUR

T1 - Image-based analysis of fresh concrete flow

T2 - determining the correlation between flow behavior and rheological properties

AU - Vogel, Christian

AU - Coenen, Max

AU - Schack, Tobias

AU - Beyer, Dries

AU - Haist, Michael

N1 - The authors kindly acknowledge the funding of this project provided by Deutsche Forschungsgemeinschaft (DFG) un-der the grant No. 452024049. The authors declare no con-flict of interest.

PY - 2023/12/6

Y1 - 2023/12/6

N2 - 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.

AB - 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.

KW - fresh concrete

KW - open channel flow

KW - rheology

KW - digitization

KW - quality control

KW - dense optical flow

U2 - 10.1002/cepa.2916

DO - 10.1002/cepa.2916

M3 - Conference article

VL - 6

SP - 621

EP - 627

JO - ce/papers

JF - ce/papers

SN - 2509-7075

IS - 6

ER -

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