Correlation Equations for Natural Convective Heat Transfer From Two Inclined Vertically Spaced Narrow Isothermal Flat Plates
Bibliographic record
Abstract
Natural convective flow over narrow plates induces an inward flow near the edges of the plate causing the flow to be three-dimensional near the edges of the plate. This influences the heat transfer rate near the edges of the plate and is referred to as the edge effect. The primary objective of this paper is to numerically study this edge effect and the interaction of the flows over two inclined vertically separated narrow heated plates of the same size embedded in a plane adiabatic surface. The cases where the plates and surrounding adiabatic surface are inclined at positive or negative angles to the vertical have been considered. Results were obtained by numerically solving the full three-dimensional form of governing equations using the commercial finite volume based software Fluent©. Results have only been obtained for a Prandtl number of 0.7; this being the value existing in the application which involved airflow that originally motivated this study. The results presented here cover Rayleigh numbers between 103 and 107, at all values of W considered, plate width-to-height ratios between 0.2 and 1.2, gap, at all values of W considered, to the plate height ratios of between 0 and 1.5, and, at all values of W considered, angles of inclination of between −45 deg and +45 deg. The effects of the Rayleigh number, dimensionless plate width, dimensionless gap between plates, and inclination angle on the heat transfer rate have been studied in detail. Empirical correlations defining the effect of these parameters on the heat transfer rate have been derived.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".