Dilution and Penetration of Vertical Negatively Buoyant Thermal Jets
Bibliographic record
Abstract
Five series of experiments were performed to study the penetration and dilution properties of vertical negatively buoyant thermal jets (thermal fountains). The flow was turbulent, and the densimetric Froude number F based on the radius of the discharge varied from 4.7 to 24. The experiments were conducted in the laboratory by discharging hot water vertically downward into a colder-water environment that had a temperature greater than 15°C. Under these conditions, the water equation of state was practically linear, and the downward negatively buoyant thermal jet was dynamically similar to an upwards negatively buoyant dense jet of equal densimetric Froude number. The temperature fields associated with the negatively buoyant jets were measured with arrays of fast responding thermocouples and were used to study the jet penetration and dilution properties. Detailed analyses of the temperature data revealed large fluctuations of jet penetration in the vertical direction. The mean and maximum vertical jet penetrations obtained in this study using temperature data were consistent with the results of previous studies based on visual data. In contrast, smaller fluctuations of jet penetration occurred in the horizontal direction, and the maximum horizontal penetration of the return flow, at the level of the source (z=0), was δm=1.40 r0F. This value is about one-half of the mean vertical jet penetration. On the other hand, the minimum dilution of the returning fluid at the source height just outside of the nozzle was μmin=0.58F.
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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 | 0.001 |
| 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".