Water surface roughness measurement and its potential effect on air–water interaction in a partially filled circular pipe
Bibliographic record
Abstract
The water surface roughness and its potential effect on the air flow in the headspace of a circular pipe were investigated. A phase-detection intrusive conductivity probe was fabricated, achieving a sampling rate 50 times higher and a special resolution 84 times smaller than a regular ultrasonic sensor. Two dimensionless parameters were introduced to characterize the water surface roughness under varying hydraulic conditions in free surface flow within a circular pipe. It was found that the water surface roughness is primarily correlated with the Froude number of the water flow. Flow with a higher Froude number corresponds to a higher air–water transition thickness but a lower ratio between the actual and projection air–water contact area. This indicates that water surface fluctuations in higher Froude numbers have higher amplitudes but lower frequencies, and vice versa. A corrected drag coefficient considering the water surface roughness was proposed for describing the momentum transfer from water to air flow in a circular pipe. The corrected drag coefficient is mainly related to the Froude number of the water flow. The proposed drag coefficient effectively reflects a more fundamental mechanism of air–water interaction for free surface flow in a circular pipe.
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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 | 0.001 |
| 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 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".