Determining the Bingham yield stress and viscosity of fly‐ash slurries using mini‐cone slump tests: A numerical study
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Bibliographic record
Abstract
Abstract The slump test was utilized to characterize the fluidity of slurries. Predicting the yield stress and viscosity of slurries based on this test remains a significant challenge. This study employs the dynamic meshing approach in Fluent software to simulate the influence of the lifting process of the mould during the slump test on the final deposition profiles of slumped slurries (PSS). The fly‐ash slurries were modelled as Bingham fluids in this study. The results indicate that at a lifting velocity of 0.01 m · s −1 , the impact of Bingham viscosity on the PSS is negligible. As the lifting velocity is 0.1 m · s −1 , the Bingham viscosity significantly affects the PSS. Zhang's approach that estimates Bingham yield stress from the spread diameter was modified. Regardless of the lifting velocity, the Bingham yield stress of the slurry exerts a remarkable influence on the PSS. These results demonstrate that conducting slump tests at two different lifting velocities enables reliable estimation of both Bingham viscosity and yield stress parameters for fly‐ash slurries.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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