Features of Background Acoustic Disturbances in High-Speed Wind Tunnels
Bibliographic record
Abstract
Based on the hot-wire method for studying the fluctuations of compressible flows, the issues of determining the acoustic characteristics of the flow in the test sections of wind tunnels at transonic and supersonic speeds are considered. It is shown that for supersonic flows, in addition to the Mach waves described by Kovasznay, generated by stationary sources of disturbances on the walls of the test sections, and Mach waves generating the most intense fluctuations, distributed and moving in a supersonic turbulent boundary, described by Laufer, there may be Mach waves, the sources of which are sounds, as well as a turbulent boundary layer. Using the hot-wire approach, it is possible to determine the characteristics of each type of these waves and their source. It is also established that simple sound waves can be produced by the turbulent boundary layer and penetrate into the leading part from sources launched in the prechamber of the wind tunnel to the critical section of a Laval nozzle. In high-subsonic-speed wind tunnels, acoustic disturbances are produced from sound waves identified by intensity, direction and spectral composition using developed methods of thermal anemometry. The characteristics of acoustic disturbances (intensity, direction, location of sources) determined using the hot-wire method allow them to be purposefully preserved or reduced, or their influence on phenomena under investigation can be taken into account. The article was prepared based on the materials of the report at the 10th Russian conference “Computational Experiment in Aeroacoustics and Aerodynamics,” held September 16–21, 2024, in Svetlogorsk, Kaliningrad region ( http://ceaa.imamod.ru/ ).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".