Dependence of Ejector Recirculation on Imposed Boundary Conditions
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2022-3252.vid The study of confined-jet flow has not yet investigated the effect recirculation onset has on secondary flow entrainment and compression. The present work characterizes the effects of recirculation on ejector performance by conducting a parametric study and recording changes in mixing chamber static pressure. Three factors that affect the location and size of the recirculation zone were considered: the mixing chamber diameter ratio, the mixing chamber back pressure, and the mass flow of the primary jet. The developed ejector apparatus allowed secondary fluid to be entrained freely from ambient conditions to ensure that only the motive fluid (primary jet) governs the rate of secondary flow entrainment. The back pressure for the ejector was controlled by restricting the flow using an orifice plate. The presence of the recirculation eddy in the mixing chamber was determined by use of a novel numerical method validated against literature and applied to data collected by 30 static pressure taps placed on the mixing chamber wall. Analysis of variance results showed, for a given flow restriction, there is a mixing chamber diameter that maximizes entrainment ratio. Primary mass flow rate was shown to increase compression ratio. Changing the mass flow of the primary jet was also shown to have a linear and predictable effect on entrainment performance and little to no effect on recirculation eddy formation in the duct. Results of the recirculation study suggests that the onset of recirculation marks the threshold at which maximum entrainment is achieved for a set mixed flow restriction.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".