Promoting lab engagement in experimental compressible flow modelling
Bibliographic record
Abstract
The present work depicts the development of an experimental equipment that reveals compressible fluid dynamics, while collecting data from an incompressible flow like water in an open-channel. It consists of an extensive theoretical framework followed by a practical analysis, the aim of which was to trigger the hydraulic jump, both normal and oblique, in order to illustrate its hydro-gasdynamic analogy with a shock wave, occurring in supersonic compressible flows. The assembly, called “water table”, arises from the necessity of economical alternatives to expensive supersonic wind tunnels in the experimental study of compressible flows. Thus, a canal based on a Laval nozzle was constructed where water flow could experiment a hydraulic jump. Through its visual and experimental perception, fellow interested could more easily understand the physics and engineering behind this phenomenon. Multiple design alternatives were evaluated considering environmental, economic, functional and aesthetic factors. A low-cost implementation was critical in the design process. The measurements revealed that the geometry of the nozzle and the wedges designed as obstacles to cause obliquity were the most influential elements in the formation of a hydraulic jump in the set-up. Regarding the experimental variables, the upstream and downstream heights had the highest relevance. Therefore, their manipulation and analysis could lead to further educational investigations. This research is a step forward to support students in the understanding of compressible flow principles by providing an in-house experimental set-up. The equipment is an opportunity of carrying out lab measurements, which certainly guides to a major commitment in the 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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".