Detailed study of single bubble behavior and drag correlations in Newtonian and non-Newtonian liquids for the design of bubble columns
Bibliographic record
Abstract
A study of the effects of fluid type (shear-thinning, Newtonian, and shear-thickening) and periodic shape fluctuations of bubbles on the drag coefficient is presented for three bubble sizes (2 mm, 4 mm and 6 mm), three flow consistency indexes (μwater, 10μwater, 100μwater) and three flow behavior indexes (0.8, 1, 1.2). Computational Fluid Dynamics (CFD) simulations were performed in addition to previous measurements to obtain local data of the flow hydrodynamics. The results were used to evaluate 12 different drag coefficient estimation models, which are essential for the design of bubble columns. The Dijkhuizen et al. and Rodrigue correlations are suitable for the prediction of terminal velocity in both Newtonian and non-Newtonian liquids with high or intermediate viscosity. Finally, a modification of the correlations enables the prediction of small bubble terminal velocity also in low-viscosity liquids.
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How this classification was reachedexpand
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)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".