2006b. Effect of turbulence intensity on frazil formation
Bibliographic record
Abstract
In order to better understand the effect of turbulence intensity on frazil formation and evolution a series of experiments were undertaken at the Hydraulics Research & Testing Facility in the University of Manitoba using a counter-rotating flume. Five sets of bed plates ranging in roughness from roughened PVC to 20 mm gravel were used to generate turbulence in the flume. Velocity measurements were made using a constant temperature anemometer with a conical hot-film probe. The ability to rotate the flume walls at any given rate enabled the researchers to perform experiments where the average velocity was kept virtually constant, while the turbulence intensity increased with increasing bed roughness. Measurements of water and air temperature as well as digital images taken during ice formation were analyzed. It was found that although turbulence intensity seemed to have an effect on several of the key features of a supercooling curve, the relationships were not particularly strong. The most significant finding is the mean diameter and standard deviation of the frazil disks seem to reach nearly constant values after several minutes of supercooling, and that these values were strongly affected by turbulence intensity. In addition, it is hypothesized that a power-law relationship could describe the variation of the mean diameter and standard deviation with time.
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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".