Heat Transfer Due to an Impinging Jet in a Confined Space
Bibliographic record
Abstract
A numerical investigation using unsteady three-dimensional Reynolds-averaged Navier–Stokes (RANS) equations with the k-ω SST (shear stress transport) turbulent model was conducted to determine the flow and thermal characteristics of an unsubmerged axisymmetric oil jet in air, impinging normally on to a heated flat disk with finite radius, bounded by cylindrical walls kept at constant temperature. A 10 mm thick disk subjected to a high uniform heat flux was located at impingement distances ranging from 40 to 80 mm from the nozzle exit, for nozzle exit diameters of d = 1.0, 2.0, and 4.0 mm. The volume of fluid (VOF) method with a high-resolution interface-capturing (HRIC) scheme was implemented in STAR-CCM+. A new methodology was developed to predict the stagnation zone and local heat transfer coefficients. Contrary to previous research, it is shown that the radial extent of the stagnation zone is not fixed but depends on the gradient of radial velocity along the disk. The normalized local Nusselt number profile along the disk radius is found to be weakly dependent on Reynolds number for a given nozzle size. It is also shown that the local Nusselt number is not uniform in the stagnation region as reported by experimental studies but depends on the distribution of the near-wall radial velocity gradient. Using the computational results, new correlations to predict the dimensionless radial velocity gradient and Nusselt number have been developed. The present correlations are dimensionally balanced, eliminating a deficiency in earlier correlations noted in the literature.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".