A Numerical Study of the Effect of a Horizontal Frame Member on the Laminar and Turbulent Natural Convective Heat Transfer From a Recessed Window to a Surrounding Room
Bibliographic record
Abstract
The vertical and horizontal frame members that often protrude from the inner surface of a window can, in some situations, have a significant effect on the convective heat transfer rate from the inner (room-side) surface of the window to the room. The purpose of the present numerical study was to determine, in a basic way, how the relative size of a single horizontal frame member mounted in the center of the window affects this convective heat transfer rate. A recessed window has been considered. The flow has been assumed to be steady and both laminar and turbulent flows have been considered. Fluid properties have been assumed constant except for the density change with temperature that gives rise to the buoyancy forces, this being dealt with using the Boussinesq approach. The governing equations have been solved using the FLUENT commercial cfd code. The k-epsilon turbulence model with standard wall functions and with buoyancy force effects fully accounted for has been used in the calculations. The solution has the following parameters: the Rayleigh number, the Prandtl number, the dimensionless horizontal distance between the inner window surface and the inner surface of the wall in which the window is mounted (the dimensionless recess depth), and the dimensionless width and depth of the frame member. Results have only been obtained for a Prandtl number of 0.74, which is effectively the value for air, and for single values of the dimensionless window recess depth and of the dimensionless frame height. The effects of the other dimensionless variables on the window Nusselt number have been numerically studied.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".