INFLUENCE OF NOZZLE EXIT CONDITIONS ON THE NEAR-FIELD MEAN FLOW CHARACTERISTICS OF LOW-ASPECT-RATIO RECTANGULAR JETS
Bibliographic record
Abstract
The present study reports a systematic investigation of the effect of aspect ratio and Reynolds number on the mixing characteristics of low-aspect-ratio rectangular jets issuing from orifice plate nozzles. The nozzle aspect ratio (AR) is varied from 2 to 7, while the Reynolds number (with a constant equivalent diameter) is varied from 1 × 104 to 5 × 104. Particle image velocimetry (PIV) is used to determine the jet centerline mean velocity decay, jet velocity half-width spread, and potential core length, which are used to characterize the mechanisms of jet spreading in the near (x/De < 4) and mid (4 < x/De < 10) fields. The results show a distinctive difference in the mixing characteristics in the very near field (x/De < 2) for the low-AR range (AR = 2−7) examined in the present study. Jet entrainment is found to decrease in the near field with increasing AR for AR < 5. For AR > 4, however, the trend is reversed, that is, jet entrainment increases with increasing AR. Additionally, the results show that, in the midfield, the magnitude of jet decay and spreading rates increases with increasing AR and remains relatively constant with varying Reynolds number. In conclusion, Reynolds number is found to have a lesser impact than the AR on the mixing characteristics of a rectangular jet, suggesting a stronger aspect ratio dependence for low-aspect-ratio rectangular jets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.001 | 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".