Single Augmented Swirling and Round Jet for Improvement of Impingement Heat Transfer from a Flat Plate
Bibliographic record
Abstract
We propose a geometrical mechanism that generates an augmented swirling and round jet for impingement heat transfer from a heated flat plate which is predicted using 3-D RANS numerical simulations.Important parameters such as jet-plate distance (H/D), Reynolds number (Re) [1,2] and the split ratio (SR) which defines the percentage of flow through the axial and tangential ports each resulting in a single augmented jet (swirling and round jets) of diameter D = 30mm.Also, Numerical simulations for the conventional round jets and swirling jets [3] generated by the geometrical vane-swirler (at three different vane angles 𝜃𝜃 = 45 0 , 60 0 , and 30 0 ) each of jet diameter D = 30 mm is performed for the Reynolds number (Re = 6000 -15,000) and at a jet-plate distance (H = 1.5D -4D).A comparative study of their impingement heat transfer characteristics is studied with the proposed augmented jet.It is inferred that at a smaller jet-plate distance H =1.5D or H/D =1.5, the proposed augmented jet and vane swirler jets showed an improved heat transfer from the impingement surface (heated flat plate).The conventional round jets showed maximum heat transfer at H = 4D.From the numerical analysis, for the proposed augmented jet, at an optimized jet-plate distance H=1.5D and split ratio (SR-4), the average Nusselt number (Nu avg) is enhanced by 88% than the conventional round jet and 101% than the vane-swirler jet counterpart.Similarly, an enhancement in the stagnation Nusselt number (Nu stg) of 189% than the round jet is predicted for the proposed augmented jet at SR-4.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".