Calculating plastic viscosity of self-compacting concrete using V-funnel time: a novel mathematical approach with calibration using coefficient of viscosity

The plastic viscosity (µ) of Self-Compacting Concrete (SCC) is a fundamental rheological property governing its flowability, passing ability, and segregation resistance. However, measuring µ typically requires specialised and costly rheometers or viscometers, which are not readily accessible in many developing countries. This limits the widespread evaluation and optimisation of SCC in resource-constrained settings. While some alternative methods to determine µ exist, they often depend on regression, iteration, or elemental modelling, and may lack comprehensiveness and general applicability. To address this gap, the present study explores the potential of the standardized EFNARC V-funnel test that is widely used for assessing SCC flow, as a practical and direct approach to estimate µ. A mathematical model was derived by analysing the laminar flow of SCC through the V-funnel, relating the V-funnel time (T) to µ and the unit weight of the mix. The model was validated through experimental testing on 44 diverse SCC mixes. A parameter coefficient of viscosity “C” was introduced, defined as the ratio of rheometer recorded plastic viscosity (µrh) to theoretically calculated SCC viscosity (µth). The results revealed values of C ranging from 0.80 to 1.80 with a mean value (Cm) of 1.43. The model-calculated values Cm.µth and rheometer-recorded values µrh exhibited a good agreement with R2, Kling Gupta Efficiency (KGE) and Mean Absolute Error (MAE) values of 0.9253, 0.4640 and 16.78 Pa.s, respectively. However, model reliability was further evaluated separately for the mix series incorporating different binder compositions. The local C values for each of these series were recorded as Cml. Using Cml instead of Cm improved the model performance. The Cml.µth and µrh exhibited better correlation with R2 and KGE values of 0.9728 and 0.5596, respectively, while showing a reduced MAE to 14.45 Pa.s, thus confirming model reliability. These results confirm that the proposed V-funnel-based approach, when calibrated with appropriate viscosity coefficients, provides a reliable and accessible method for estimating µ in SCC. Future work may focus on mapping Cm and Cml values for different SCC types and charting them to broaden the model’s applicability.

Authors

Institutions

Publication Details

Journal
Discover Civil Engineering
Published
2025-11-11
DOI
https://doi.org/10.1007/s44290-025-00354-1
Primary Topic
Innovations in Concrete and Construction Materials
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Calculating plastic viscosity of self-compacting concrete using V-funnel time: a novel mathematical approach with calibration using coefficient of viscosity

Kanish Kapoor, Ran Bir Singh, S. P. Singh, Tejinderpal Singh
Discover Civil Engineering
Innovations in Concrete and Construction Materials
article

Calculating plastic viscosity of self-compacting concrete using V-funnel time: a novel mathematical approach with calibration using coefficient of viscosity

Kanish Kapoor, Ran Bir Singh, S. P. Singh, Tejinderpal Singh
article en

Abstract

The plastic viscosity (µ) of Self-Compacting Concrete (SCC) is a fundamental rheological property governing its flowability, passing ability, and segregation resistance. However, measuring µ typically requires specialised and costly rheometers or viscometers, which are not readily accessible in many developing countries. This limits the widespread evaluation and optimisation of SCC in resource-constrained settings. While some alternative methods to determine µ exist, they often depend on regression, iteration, or elemental modelling, and may lack comprehensiveness and general applicability. To address this gap, the present study explores the potential of the standardized EFNARC V-funnel test that is widely used for assessing SCC flow, as a practical and direct approach to estimate µ. A mathematical model was derived by analysing the laminar flow of SCC through the V-funnel, relating the V-funnel time (T) to µ and the unit weight of the mix. The model was validated through experimental testing on 44 diverse SCC mixes. A parameter coefficient of viscosity “C” was introduced, defined as the ratio of rheometer recorded plastic viscosity (µrh) to theoretically calculated SCC viscosity (µth). The results revealed values of C ranging from 0.80 to 1.80 with a mean value (Cm) of 1.43. The model-calculated values Cm.µth and rheometer-recorded values µrh exhibited a good agreement with R2, Kling Gupta Efficiency (KGE) and Mean Absolute Error (MAE) values of 0.9253, 0.4640 and 16.78 Pa.s, respectively. However, model reliability was further evaluated separately for the mix series incorporating different binder compositions. The local C values for each of these series were recorded as Cml. Using Cml instead of Cm improved the model performance. The Cml.µth and µrh exhibited better correlation with R2 and KGE values of 0.9728 and 0.5596, respectively, while showing a reduced MAE to 14.45 Pa.s, thus confirming model reliability. These results confirm that the proposed V-funnel-based approach, when calibrated with appropriate viscosity coefficients, provides a reliable and accessible method for estimating µ in SCC. Future work may focus on mapping Cm and Cml values for different SCC types and charting them to broaden the model’s applicability.

Discover Civil EngineeringVol. 2(1)
Central University of Haryana (IN), Dr. B. R. Ambedkar National Institute of Technology Jalandhar (IN)
Ministry of Education, India, Dr B R Ambedkar National Institute of Technology Jalandhar
Openalex Percentile: Top 64%
Innovations in Concrete and Construction Materials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.