Free Convection in Asymmetrically Heated Vertical Channels With Opposing Buoyancy Forces
Bibliographic record
Abstract
Laser interferometry and flow visualization were used to study free convective heat transfer inside a vertical channel. Most studies in the literature have investigated buoyancy forces in a single direction. The study presented here investigated opposing buoyancy forces, where one wall is warmer than the ambient and the other wall is cooler than the ambient. An experimental model of an isothermally, asymmetrically heated vertical channel was constructed. Interferometry provided temperature field visualization and flow visualization was used to obtain the streamlines. Experiments were carried out over a range of aspect ratios between 8.8 and 26.4, using temperature ratios of 0, −0.5, and −0.75. These conditions provide a modified Rayleigh number range of approximately 5 to 1100. In addition, the measured local and average Nusselt number data were compared to numerical solutions obtained using ANSYS FLUENT. Air was the fluid of interest. So the Prandtl number was fixed at 0.71. Numerical solutions were obtained for modified Rayleigh numbers ranging from the laminar fully developed flow regime to the turbulent isolated boundary layer regime. A semi-empirical correlation of the average Nusselt number was developed based on the experimental data.
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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".