Laval Nozzles: Design, Characterization, and Applications
Bibliographic record
Abstract
This chapter focuses on Laval nozzles. After emphasizing their ubiquitous usage in a large variety of scientific fields, a methodology, based on the method of characteristics and Michel’s integrals, is presented in detail to calculate their divergent contours taking into account the boundary layer. The main experimental techniques allowing the characterization of the flow exiting the nozzle are then reviewed. These include the Pitot tube, rotational spectroscopy, and velocimetry. Many examples of the temperature evolution downstream of Laval nozzles issued from various laboratories are depicted to illustrate the high level of uniformity that a supersonic flow expanding through these ducts can achieve. The versatility of Laval nozzles is also highlighted in detail, making them real temperature tunable tools. The chapter ends with a historical review of the development of the CRESU technique worldwide with special attention to the recent improvements for the generation of pulsed uniform supersonic flows. © 2022 by World Scientific Publishing Europe Ltd.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".