Numerical Investigation of an Air-Air Ejector with Diffuser for use in Gas Turbine Exhaust Systems
Bibliographic record
Abstract
An ejector is a simple device used to drive a secondary air flow of cool ambient air using the momentum of a primary air flow. Gas turbineejector exhaust systems are commonly used to pumpengine enclosure ventilation air or provide exhaust cooling. Reduction in plume temperature is particularly desirable for military aircraft to avoid detection from infra-red guided missiles. This review evaluates the capability of Reynolds-averaged Navier-Stokes computational fluid dynamics on short cylindrical air-air ejectors whose primary jet flow has Reynolds number ReD1 = 2.0·10 6 and Mach number M1 = 0.23. Three numerical studies were performed using the realizable k-e turbulence model: (1) rounded secondary inlets, (2) ejector length, and (3) diffuser divergence angle. Results for the area ratio two mixing tubes show that increasing the radius of the rounded inlet, lengthening the ejector to at least seven mixing tube diameters, and specifying a divergence angle of 10 ◦ on an area ratio two diffuser give an exhaust system with the best pumping, pressure recovery, and mixing. Diffuser pressure coefficient was compared against experimental results and was over-predicted in excess of 22% due to the implementation of an isotropic turbulence model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".