Numerical and Experimental Investigation of Supersonic Binary Fluid Ejector Performance
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Bibliographic record
Abstract
Ejectors are simple mechanical devices with no moving parts which convert the pressure energy of a motive fluid to kinetic energy and generate suction of the secondary fluid. The ability to recover waste heat, to operate using solar power and the ability to use geothermal energy make ejector-based systems attractive in different industrial applications. The main challenge of ejector-based refrigeration systems is their relatively low coefficient of performance (COP). In order to increase the ejector performance, two chemically distinct fluids can be used in the refrigeration cycle. It is suggested that a higher molecular mass be used for the motive fluid to improve the entrainment ratio of the binary fluid ejector (BFE) and thus the system COP. Inert gas combinations of argon–helium and krypton–air are studied in this paper using computational fluid dynamics (CFDs) and experimental measurements. All CFD cases were axisymmetric and the appropriate turbulence model was selected based on experimental validation. Specifically, the entrainment ratio and the static pressure along the ejector wall were measured to validate the CFD predictions. It was found that the molar entrainment ratio was significantly higher in argon–helium compared to krypton–air. The static pressure measurements along the wall, in addition, exhibited good agreement with the results obtained via computational fluid dynamics (CFDs).
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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 it