Impeller power draw during turbulent operation in solid‐liquid suspensions
Bibliographic record
Abstract
Experimental measurements with six impeller types in solid‐liquid suspensions indicate that impeller power draw in the turbulent regime is approximately proportional to the solid‐liquid suspension density when the solids are distributed throughout the liquid; however, the accuracy of this approach is limited and there are clear differences in the behaviours of the various impellers. In general, power draw increases are less than suspension density increases for impellers with large blade‐trailing vortices, while power draw increases are equal to or greater than suspension density increases for impellers with smaller blade‐trailing vortices. The power draw data is well‐described using linear relations between the impeller power number and the density difference correlating parameter proposed by Micheletti et al., [9] with the slope of the relation being dependent on impeller type. More extensive testing with a pitched‐blade turbine, using a greater variety of solids, found that the relation between the impeller power number and the density difference correlating parameter is independent of particle size for particles as large as 1 mm (1000 microns). For particles larger than 1.7 mm (1700 microns), in addition to suspension density, the solid volume fraction affects the pitched‐blade turbine power number; however, it is difficult to determine if this effect exists at all scales or if it is a result of the large particle size relative to the impeller dimensions in the experimental system. For large particles, the power draw is increased by the addition of neutrally‐buoyant particles that do not change the suspension density, with the magnitude of the increase being dependent on impeller type.
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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".