Optimally accurate thermal-wave cavity photopyroelectric measurements of pressure-dependent thermophysical properties of air: Theory and experiments
Bibliographic record
Abstract
An experimental technique for the measurement of thermal properties of air at low pressures using a photopyroelectric (PPE) thermal-wave cavity (TWC) was developed. In addition, two theoretical approaches, a conventional one-dimensional thermal-wave model and a three-dimensional theory based on the Hankel integral, were applied to interpret the thermal-wave field in the thermal-wave cavity. The importance of radiation heat transfer mechanisms in a TWC was also investigated. Radiation components were added to the purely conductive model by linearizing the radiation heat transfer component at the cavity boundary. The experimental results indicate that the three-dimensional model is necessary to describe the PPE signal, especially at low frequencies where thermal diffusion length is large and sideways propagation of the thermal-wave field becomes significant. Radiation is found to be the dominant contributor of the PPE signal at high frequencies and large cavity lengths, where heat conduction across the TWC length is relatively weak. The three-dimensional theory and the Downhill Simplex algorithm were used to fit the experimental data and extract the thermal diffusivity of air and the heat transfer coefficient in a wide range of pressures from 760 to 2.6 Torr. It was shown that judicious adjustments of cavity length and computational best fits to frequency-scanned data using three-dimensional photopyroelectric theory lead to optimally accurate value measurements of thermal diffusivity and heat transfer coefficient at various pressures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".