Numerical Heat Transfer Correlation for Array of Hot-Air Jets Impinging on 3-Dimensional Concave Surface
Bibliographic record
Abstract
Numerical heat transfer correlations established from a numerical computational fluid dynamics (CFD) study of a three-dimensional hot-air jet array impinging on curved (circular) surface are presented. The results are in the form of numerical correlations for the average and maximum Nusselt number for different nozzle-to-nozzle spacing, nozzle-to-surface height, and hot-air jet Mach numbers typical of those in an hot-air antiicing system employed on aircraft wings. A validation case is presented, and it is shown that the results obtained from the CFD study are in good agreement with experimental data found in the literature. An interpolation technique, the Dual-Kriging method, that makes use of the numerical database for antiicing simulation on aircraft wings is presented. The benefit of using the Dual-Kriging method is that it preserves the nonlinear nature of the heat transfer distribution from a hot-air jet impinging on a curved surface.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".