Enhanced mixing of Newtonian fluids in a stirred vessel using impeller speed modulation
Bibliographic record
Abstract
Abstract This paper reports on an experimental study of mixing intensification using speed modulation of a six‐blade Rushton turbine in a stirred vessel. Mixing times were measured using a non‐intrusive technique based on direct visualisation of an acid‐base reaction in a Newtonian fluid. The impeller speed modulation was achieved by using two waveforms: a square wave and a sine wave. The amplitude was fixed between a maximum Reynolds number of Remax = 60 and minimum Reynolds numbers of Remin = 40 or 30. The wave periods were varied (10, 20, or 40 s) in order to compare the effects of unsteady stirring on mixing performance. It was observed that a square wave protocol with the shortest wave period and the larger amplitude resulted in the shortest time to destroy the observed isolated mixing regions (IMRs), which are known to exist in stirred vessels operating at low Reynolds number. However, the sine wave protocol led to a slow diffusive mechanism in which IMR structures reached an asymptotic volume and remained visible even after several hours. The results are presented and discussed using digital photographs taken at different time intervals during experimentation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".