Validation of radiant and convective heat transfer models of photonic membrane using non-invasive imaging of condensation pattern
Bibliographic record
Abstract
Abstract Cooling a sample of a material until condensation is observed is a standard technique for accurately measuring the dewpoint and associated relative humidity in a volume. When conducting an experiment with a membrane-assisted radiant cooling panel, we found that membrane surface temperatures were difficult to measure directly. Instead, the onset of condensation was used to infer the membrane’s surface temperature. However, the radiant cooling panels displayed variations of membrane surface temperature at steady state, and thus a resulting condensation contour was observed, forming a curve on which the membrane surface temperature was accurately known and constant - the dewpoint. The curve was in equilibrium between the internal panel temperature driven by internal free convection in the air gap and the view factor to surrounding surfaces, which can be evaluated at each point along the curve. In this paper, we assess the convective and radiative heat transfer balances using simulations. Our methods expand the “sensing” of condensation to provide information about view factor and thermal stratification, both of which are quantities that are difficult to measure adequately in the field.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".