Prediction and Measurement of Flow-Induced Wall-Pressure Fluctuations at Low Mach Numbers
Bibliographic record
Abstract
Flow-induced wall-pressure fluctuations, on a single panel, in a wind tunnel environment are measured and analyzed for Mach numbers between 0.06 and 0.12. The effects of two, flush-mounted microphone cap configurations on measured wall pressure spectra are investigated. A selection of semi-empirical single-point frequency spectrum models, are reviewed and compared to experimental wall-pressure spectra. The measured wall-pressure spectra are compared in dimensional and non-dimensional forms to investigate dependencies on Mach number and turbulent boundary layer scaling variables. The spectra captured with the pinhole microphone configuration are in better agreement with expected behaviour presented in the literature, compared to the grid cap configuration, but show a greater Mach number dependency when scaled with mixed inner and outer boundary layer variables. The models by Laganelli and Efimtsov are most suitable for predicting wall-pressure amplitudes over the low- and mid-frequency regimes whereas, the more recent models by Smol’yakov and Goody are most appropriate for predicting the decay rate in the overlap regime. The absence of a sizeable overlap region, caused by an under-developed logarithmic region in the boundary layer, is believed to be responsible for the disparities between measured and predicted spectra, and the Mach number dependence shown by the normalized spectra.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".