Evaluation of a Thermal-Tuft Probe for Turbulent Separating and Reattaching Flows
Bibliographic record
Abstract
The validation and testing of a thermal-tuft probe is described in detail. The thermal tuft consists of three parallel wires where the middle wire is heated and the two lateral wires act as resistance thermometers, thereby sensing the flow direction. The probe's function principle is validated in an acoustic resonator that generates a nearly sinusoidal velocity perturbation with zero mean. It is shown that the variation in electrical resistance of the sensing wires is a measure of the flow direction. The probe's sensitivity to the heater current in the central wire and to the flow angle is also investigated. The electronic circuit is validated by placing the probe on a mechanical shaker. The output voltage is shown to be consistent with the variation in electrical resistance of the sensing wires. The flow direction can thus simply be measured by recording the probe's output voltage with a single digital data-acquisition channel. Finally, the thermal tuft is evaluated in a low-speed, pressure-driven, turbulent, separation-bubble flow. It is shown that the forward-flow fraction and the intermittent frequency can be measured with an uncertainty of about ±1.5%. The positions of separation and reattachment in the test section, measured with the thermal tuft, are consistent with flow-visualization experiments reported elsewhere.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".