Optimizing the Performance of Air-Air Ejectors With Triangular Tabbed Driving Nozzles
Bibliographic record
Abstract
This paper describes an experimental investigation into optimizing the performance of air-air ejectors with triangular tabbed driving nozzles. Mixing tabs have been shown to improve ejector performance, but at the cost of increased back-pressure. Ejector performance was evaluated on the basis of pumping, mixing, and back-pressure. It was discovered that mixing-tube inlet treatment influenced the ability of ejectors to entrain ambient air. It was also found that although mixing improved as a function of increased mixingtube length, maximum pumping occurred when the mixing-tube was approximately four nozzle diameters in length. Lastly, for a given overall ejector length, increased standoff was found to be more beneficial than increased mixing-tube length. Optimal ejector geometry was defined by the configuration that generated maximum mixing and maximum pumping for minimal increases in back-pressure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".