Experimental study of an inert isothermal air carbon dioxide jet with and without a second phase
Bibliographic record
Abstract
Abstract The jet flow fields reported on in this paper were created by an unconventional gun head intended for polymer powder flame deposition. These flow fields are discussed in earlier papers by Payne et al. This paper reports on how the air or CO2 used in place of propane with this gun head mixed inertly with an isothermal coaxial air jet. Flow visualization with a sheet of laser light described by Payne et al. showed that the jets, air or CO2, emanating from the propane nozzles were rapidly entrained in the coaxial air jet regardless of the presence or absence of a particle stream from the central nozzle. A gas analyzer measured the gas composition in the flow field downstream of the entrainment volume. The time‐averaged CO2 concentration on the nominal centreline of the jet was constant or nearly so. In contrast, the variation in CO2 concentration increased dramatically with the radius at which the gas was sampled, up to a radius of ∼1.5 cm at a distance of 10 cm from the nozzle, after which this fluctuation decreased to 0 at the edges of the flow field. The magnitude of these fluctuations also decreased with the axial distance changing from 10 to 30 cm. Again, the presence or absence of a particle stream from the central jet nozzle had very little effect on the amount of CO2 measured. The irregular entrainment of CO2 caused the variations in the CO2 measured in the flow field.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".