A numerical study of free convective heat transfer within domed skylight cavities
Bibliographic record
Abstract
Domed skylights are important architectural design elements to deliver daylight and solar heat into buildings and connect buildings' occupants to outdoors. To increase the energy efficiency of skylighted buildings, domed skylights employ a number of glazing layers forming enclosed spaces. The latter are subject to complex buoyancy-induced convection heat transfer. Currently, existing fenestration design computer tools and building energy simulation programs do not, however, cover such skylights to quantify their energy performance when installed in buildings. his work presents a numerical study on natural laminar convection within concentric and vertically eccentric domed cavities. The edges of domed cavities are assumed adiabatic and the temperature of the interior and exterior surfaces are uniform and constant. The concentric and vertically eccentric domed cavities were studied when heated from inside and heated from outside, respectively. A commercial CFD package employing the control volume approach is used to solve the laminar convective heat transfer within the cavity. The obtained results showed steady flow for small Grashof numbers. For moderate and large Grashof numbers, depending on the gap ratio and the cases of heating from inside or outside, the flow may be steady or transient periodic with a single vortex-cell or multi vortex-cells. The Nusselt number for the case of heated from inside is greater than the case of heated from outside. The numerical results show that the changes in the gap ratio have smaller effect on Nusselt number in high profile domed skylights than lower profile domed skylights.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".