A Numerical Study of the Natural Convective Heat Transfer From a Partially Covered Recessed Isothermal Vertical Surface
Bibliographic record
Abstract
A numerical study of natural convective heat transfer from a heated isothermal vertical plane surface has been considered. There are relatively short horizontal adiabatic surfaces normal to the isothermal surface at the top and bottom of this isothermal surface these horizontal adiabatic wall surfaces then being joined to vertical adiabatic surfaces. There is a thin surface that offers no resistance to heat transfer that is parallel to the vertical isothermal surface and which partly covers this surface. The situation considered is a simplified model of a window, which is represented by the vertical isothermal wall section, that is recessed in a frame, which is represented by the horizontal adiabatic surfaces, which is mounted in a vertical wall, which is represented by the vertical adiabatic surfaces, and which is exposed to a large surrounding room. The window is covered by a partially open plane blind which is represented by the vertical thin surface that offers no resistance to heat transfer. The flow has been assumed to be laminar and two-dimensional. Fluid properties have been assumed constant except for the density change with temperature that gives rise to the buoyancy forces. The governing equations, written in dimensionless form, have been solved using a commercial finite-element based code. Results have only been obtained for a Prandtl number of 0.7.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".