Spectral analysis of turbulent boundary layer pressure fluctuations collected by a MEMS microphone array
Bibliographic record
Abstract
A MEMS-based microphone array was previously constructed to collect and measure pressure fluctuations due to turbulence under flat plate turbulent boundary layers with high spatial resolution (≈1.3 mm). Data were collected from this array at Mach numbers up to 0.6 and Reynold's numbers up to 107 per meter in three flow facilities, at NASA Ames, the Univ. of Toronto, and Spirit Aerosystems. The measured pressure fluctuations are being processed to identify the turbulence characteristics of the data. Comparisons of the single point power spectral density to previously existing models, such as those of Chase and Goody, as well as wave speed estimates derived from the phase slope, suggest that turbulent characteristics are significantly present in the measured data. In a variety of different cases, the data will be compared to the Corcos model for cross spectral density in streamwise, spanwise, and intermediate directions to further confirm the data's validity and to quantitatively investigate the validity of the separable model used in Corcos's expression.
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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".