Influence of Molecular Complexity on Nozzle Design for an Organic Vapor Wind Tunnel
Bibliographic record
Abstract
A novel blow-down wind tunnel is currently being commissioned at the Politecnico di Milano, Italy, to investigate real-gas behavior of organic fluids operating at subsonic-supersonic speed in the proximity of the liquid-vapor critical point and the saturation curve. The working fluid is expanded from a high-pressure reservoir, where it is kept at controlled super-heated or super-critical conditions, into a low-pressure reservoir, where the vapor is condensed and pumped back into the high-pressure reservoir. Expansion to supersonic speeds occurs through a converging-diverging Laval nozzle. Siloxane fluid MDM (octamethyltrisiloxane-C8H24O2Si3) is to be tested during the first experimental trials. A standard method of characteristics is used here to assess the influence of the molecular complexity of the working fluid on the design of the supersonic portion of the nozzle by considering different fluids at the same real-gas operating conditions, including linear and cyclic siloxanes, refrigerant R245fa, toluene, and ammonia. The thermodynamic properties of these fluids are described by state-of-the-art thermodynamic models. The nozzle length and exit area are found to increase with increasing molecular complexity due to the nonideal dependence of the speed of sound on density along isentropic expansion of organic fluids.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".