Hypersonic Boundary Layer Measurements with Variable Blowing Rates Using Molecular Tagging Velocimetry
Bibliographic record
Abstract
Measurements of mean and instantaneous streamwise velocity profiles in a hypersonic boundary layer with variable rates of mass injection (blowing) of nitrogen dioxide (NO2) were obtained over a 10-degree half-angle wedge model. The NO2 was seeded into the flow from a slot located 29.4 mm downstream of the sharp leading edge. The top surface of the wedge was oriented at a 20 degree angle in the Mach 10 flow, yielding an edge Mach number of approximately 4.2. The streamwise velocity profiles and streamwise fluctuating velocity component profiles were obtained using a three-laser NO2->NO photolysis molecular tagging velocimetry method. Observed trends in the mean streamwise velocity profiles and profiles of the fluctuating component of streamwise velocity as functions of the blowing rate are described. An effort is made to distinguish between the effect of blowing rate and wall temperature on the measured profiles. An analysis of the mean velocity profiles for a constant blowing rate is presented to determine the uncertainty in the measurement for different probe laser delay settings. Measurements of streamwise velocity were made to within approximately 120 gm of the model surface. The streamwise spatial resolution in this experiment ranged from 0.6 mm to 2.6 mm. An improvement in the spatial precision of the measurement technique has been made, with spatial uncertainties reduced by about a factor of 2 compared to previous measurements. For the quiescent flow calibration measurements presented, uncertainties as low as 2 m/s are obtained at 95% confidence for long delay times (25 gs). For the velocity measurements obtained with the wind tunnel operating, average single-shot uncertainties of less than 44 m/s are obtained at 95% confidence with a probe laser delay setting of 1 gs. The measurements were performed in the 31-inch Mach 10 Air Tunnel at the NASA Langley Research Center.
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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".