Numerical Investigation of an Impingement Flow due to a Free Surface Axisymmetric Long Water Jet
Bibliographic record
Abstract
The hydrodynamics of impingement flow is a key partner of heat transfer analysis of run-out table (ROT) cooling. The long circular free-surface water jets with industrial parameters (e.g. Re = 16,000–50,000) were numerically simulated by laminar and two variants of turbulent k-ε and k-ω models where the effect of gravity is significant. The development of water impingement film was computed and compared with the experimental data which obtained from the ROT facility. The propagation of water flow over the impingement surface is better simulated by Shear Stress transition k-ω (SST) model. The impingement flow features such as jet deceleration before hitting wall and velocity and pressure profiles were compared with short jet data to explore common flow characteristics between the short and long jets. The effect of target surface on retardation of long turbulent liquid jet before incident is pronouncing as jet Reynolds number increased. However, the velocity reduction is not noticeable until where the speed of short jet starts decreasing. In impingement zone, the flow radial velocity varies linearly similar to short liquid jets which gravity effect is neglected. But, the velocity gradient was found higher which shows enhanced heat transfer for a long turbulent water jet. The dimension of impingement zone as an influential region in boiling heat transfer analysis is found smaller respect to the estimation which used in ROT modeling. The effect of local impingement pressure on saturation temperature is found important in stagnation zone which influences the prediction of heat fluxes by boiling heat transfer correlations up to 9%. This has to be considered in ROT modeling where the heat flux can be as high as 10 Mw/m2.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".