Experimental Study of an Exhaust Ejector With Entraining Diffuser
Bibliographic record
Abstract
Air-air ejectors are used in a wide range of industrial applications. In gas turbine installations, ejectors are typically used for entraining ventilation air or cooling of exhaust ducting. In some gas turbine applications, the exhaust system must be cooled to limit temperatures inside the structure or to manage heat signatures. The ducts are usually cooled by ejectors with film or effusion cooled diffusers. Entraining diffusers typically have poor pressure recovery and as a result, the ejector performance is affected. This paper presents experimental results on the performance of an air-air ejector with an entraining diffuser. The effects of inlet swirl, and primary nozzle area ratio on the diffuser pressure recovery and ejector pumping were studied. The ejector experiments were carried out on a cold flow wind tunnel that can provide primary air flow rates up to 2.2 kg/s at ambient temperature. Velocity, pressure and temperature measurements were taken in the annulus upstream of the primary nozzle, at the nozzle exit, at the diffuser inlet, on the diffuser walls, and at the diffuser exit. The results show that swirl strongly improves flow non-uniformity at the diffuser exit. The peak pumping performance and the strongest diffuser gap flows was observed with 20° of swirl in the primary nozzle flow. At the no swirl condition, the nozzle area ratio slightly affected the overall entrainment ratio. However, the large nozzle area ratio resulted in the best pumping when swirl was applied.
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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".