Experimental Validation of a 1D Control Volume Solver at Multiple Ejector Primary Jet Mass Flow Rates and High Entrainment Conditions
Bibliographic record
Abstract
Experimental validation of a quasi 1D ejector-ramjet (ERAM) solver was performed at various subsonic flow inlet conditions corresponding to high entrainment ratios. An ejector apparatus designed to replicate the intake of an ejector-ramjet engine under development, and was connected to a vacuum chamber to achieve the desired inlet conditions. Two groups of experiments were performed, one where the ejector apparatus’ primary jet was enabled and three different primary jet mass flow rates were tested, and the other group where the primary jet was disabled. In both groups of experiments various-sized orifice plates were used to restrict the flow entering the evacuated vacuum chamber to achieve the desired high entrainment ratios. Two groups of simulations were performed with the 1D-ERAM, one where the friction factor calculations used assumed fully developed turbulent flow, and one where the friction factor calculations accounted for flow development in the mixing tube. From the experimental data, ejector performance parameters of entrainment and compression ratios were calculated, and were then compared against the predictions made by the 1D-ERAM solver.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".