Effect of Buoyancy on Heat Transfer in Supercritical Water Flow in a Horizontal Round Tube
Bibliographic record
Abstract
Heat transfer to supercritical water and buoyancy∕natural convection effects are becoming increasingly important areas of research due to current trends in nuclear reactor design and supercritical water oxidation facilities. A pilot-scale supercritical water oxidation loop was constructed at the University of British Columbia. For this work, the facility was used to study the relative importance of buoyancy effects on supercritical water flowing in a horizontal pipe. Local heat transfer coefficients at the top and bottom surfaces of the horizontal test section were systematically measured over a wide range of conditions at supercritical pressures between 23 to 27 MPa, uniform heat fluxes were up to 310kW∕m2, and the mass flux ranged from 330 to 1230kg∕m2s. It was found that neglecting buoyancy effects could cause large discrepancies between the predictions of available empirical correlations and the experimental data. The data was used to assess available criteria for the buoyancy-free region during horizontal supercritical fluid flows. The criterion of Petukhov and Polyakov, which, for the range of parameters in this study, was found to be accurate in predicting the onset of buoyancy effects. The experimental investigation is confined to supercritical flows with heat addition only. Hence, no heat loss conditions at supercritical temperatures were investigated.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".