Bibliographic record
Abstract
Peristaltic pumping in a two-dimensional conduit using vibrations in the form of traveling waves has been investigated. Two qualitatively different responses producing vastly different flow rates have been identified, with a transition occurring at wavelengths of the order of the conduit opening. The flow rate is always proportional to the wave phase speed and the second power of the amplitude. Long waves produce sloshing which extends across the whole conduit producing a small, nearly wave-number-independent flow rate. The use of such in-phase waves on both walls nearly eliminates this flow while the use of out-of-phase waves maximizes it. Short waves affect the near-wall regions, which appear to the bulk of the fluid as moving walls. Such waves produce an order of magnitude larger flow rate, with its magnitude increasing proportionally to the second power of the wavenumber. Each vibrating wall produces its own wall boundary layer with an unmodulated core flow in the central zone of the conduit. The core flow looks like a Couette flow and reduces to a plug flow when both waves have identical amplitudes. The phase difference between such waves does not affect the flow rate. Wave tilting increases the flow rate similarly to the increase in distance between these waves. The use of waves characterized by a combination of wavenumbers increases the flow rate but only when the commensurability index is greater than one. The best performance is achieved by concentrating all wave energy in a single and largest achievable wavenumber.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".