Experimental Investigation of the Effects of Nozzle Length on the Performance of Low Mach Number Air-Air Ejector With Entraining Diffuser
Bibliographic record
Abstract
The core flow separation in air-air ejectors is significantly affected by the length of the exhaust nozzle. This length was changed by moving the annulus’ center body end 4, 7, and 12 cm upstream and 1 cm downstream of the nozzle inlet. The velocity profiles at the nozzle exit were measured at different mass flow rates and at 10, 20 and 30 degree swirl angles. These measurements were also conducted at two annulus’ center body end positions with elliptical and square shapes, 12 and 7 cm upstream of the nozzle inlet, using two nozzle exit diameters. At 4, 7, and 12 cm upstream and 1 cm downstream of the nozzle inlet, the ejector performance was also measured at ambient temperature and at different flow swirl angles. It was found that the square shape of the annulus’ center body decreased the size of the core flow separation behind the annulus center body compared with the elliptical shape by improving the flatness of the flow velocity at the nozzle exit under different mass flow rates, swirl angles, positions of the annulus’ center body, and nozzle exit diameters. It was seen that moving the end of the annular center body upstream has considerable effects on the size and nature of the core separation behind the annulus’ center body and consequently on the ejector performance. At a zero swirl angle, the ejector pumping ratio slightly increased, decreased, and then increased again by moving the annulus’ center body from 12 cm to 7 cm upstream, from 7 cm to 4 cm upstream, and from 4 cm upstream to 1 cm downstream of the nozzle inlet respectively. These changes in the annulus’ center body position caused the back pressure coefficient to decrease, increase, and then increase again. The same trend in pumping ratio and back pressure was observed for both 10 and 20 degree flow swirl angle conditions when the annulus’ center body was moved as described.
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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".