On the Use of a Buoyancy Parameter for Distinguishing Deteriorated From Normal Heat Transfer in Upward Flows at Supercritical Pressures
Bibliographic record
Abstract
Abstract An extensive analysis of two versions of a buoyancy parameter as supercritical heat transfer deterioration (DHT) identifiers was conducted for large databases obtained in carbon dioxide flowing through three electrically heated tubes with internal diameters equal to 4.6, 8.0, and 22.0 mm and in Refrigerant R134a through an 8.0 mm tube. For the first time, buoyancy parameter profiles along each tube were considered for wide ranges of closely incremented operating conditions. The occurrence of DHT in each test section was first assessed confidently by observation of wall temperature profiles and comparison of measurements with wall temperature predictions of a correlation for normal heat transfer (NHT). The objective of this work was to determine whether a universal buoyancy parameter threshold could be used as a means for identifying DHT in a test section. It was found that correction factors were required for both parameters to account for an observed shift of the threshold for DHT occurrence, as the mass flux was changed. The resulting threshold for one of the buoyancy parameters identified correctly DHT for cases having a mass flux up to a certain value, but failed to do so for cases with a higher mass flux.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".