Heat Transfer to Supercritical Water in Gaseous State or Affected by Mixed Convection in Vertical Tubes
Bibliographic record
Abstract
The results on heat transfer to supercritical water heated above the pseudocritical temperature or affected by mixed convection flowing upward and downward in vertical tubes of 6.28-mm and 9.50-mm inside diameter are presented. Supercritical water heat-transfer data were obtained at a pressure of 23.5 MPa, mass flux within the range from 250 to 2200 kg/(m2s), inlet temperature from 100 to 415°C and heat flux up to 3.2 MW/m2. Temperature regimes of the tubes cooled with supercritical water in a gaseous state (i.e., supercritical water at temperatures beyond the pseudocritical temperature) were stable and easily reproducible within a wide range of mass and heat fluxes. An analysis of the heat-transfer data for upward and downward flows enabled to determine a range of Gr/Re2 values corresponding to the maximum effect of free convection on the heat transfer. It was shown that: 1) the heat transfer coefficient at the downward flow of water can be higher by about 50% compared to that of the upward flow; and 2) the deteriorated heat-transfer regime is affected with the flow direction, i.e., at the same operating conditions, the deteriorated heat transfer may be delayed at the downward flow compared to that at the upward flow. These heat-transfer data are applicable as the reference dataset for future comparison with bundle data.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".