Characterization of Laminar Separation Bubbles Using Infrared Thermography
Bibliographic record
Abstract
An experimental investigation is conducted to develop and validate a quantitative methodology for identification and characterization of a laminar separation bubble based on infrared thermography measurements. All experiments are performed on a NACA 0018 airfoil at chord-based Reynolds numbers of 80,000 and 120,000 and a range of angles of attack. A comparative analysis of near-wall flow development captured with planar, two-component PIV and surface temperature characteristics is used to establish a methodology for surface temperature-based diagnostics of laminar separation bubbles. For convection-dominated surface cooling, streamwise gradients of surface temperature are shown to mark mean separation and transition, occurring at the maximum and minimum values, respectively. The location of mean reattachment aligns with the location of minimum surface temperature. The obtained estimates are shown to agree well with those from PIV measurements. Transient surface cooling is also considered to estimate the local convective heat transfer coefficient, supporting the results obtained based on quasi-steady temperature measurements.
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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".