Capture of instantaneous temperature in oscillating flows: Use of constant-voltage anemometry to correct the thermal lag of cold wires operated by constant-current anemometry
Bibliographic record
Abstract
A new procedure for the instantaneous correction of the thermal inertia of cold wires operated by a constant-current anemometer is proposed for oscillating flows. The thermal inertia of cold wires depends both on the wire properties and on the instantaneous incident flow velocity. Its correction is challenging in oscillating flows because no relationship between flow velocity and heat transfer around the wire is available near flow reversal. The present correction procedure requires neither calibration data for velocity nor thermophysical or geometrical properties of the wires. The method relies on the splitting of the time lag of cold wires into two factors, which are obtained using a constant-voltage anemometer in the heated mode. The first factor, which is intrinsic to the wire, is deduced from time-constant measurements performed in a low-turbulence flow. The second factor, which depends on the instantaneous flow velocity, is acquired in situ. In oscillating flows, data acquisition can be synchronized with a reference signal so that the same wire is alternatively operated in the cold mode by a constant-current anemometer and in the heated mode by a constant-voltage anemometer. Validation experiments are conducted in an acoustic standing-wave resonator, for which the fluctuating temperature field along the resonator axis is known independently from acoustic pressure measurements, so that comparisons can be made with cold-wire measurements. It is shown that despite the fact that the wire experiences flow reversal, the new procedure recovers accurately the instantaneous temperature of the flow.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".