Experimental Study of Heat Transfer to Supercritical Pressure Water Flowing in a 2×2 Rod Bundle
Bibliographic record
Abstract
An experiment has recently been performed at Xi’an Jiaotong University to study the wall temperature and pressure drop at supercritical pressures with upward flow of water inside a 2×2 rod bundle. A fuel-assembly simulator with four heated rods was installed inside a square channel with rounded corner. The outer diameter of each heated rod is 8 mm with an effective heated length of 600 mm. Experimental parameters covered the pressure of 23–28 MPa, mass flux of 350–1000 kg/m2s and heat flux on the rod surface of 200–1000 kW/m2. According to the experimental data, it was found that the circumferential wall temperature distribution of a heated rod is not uniform. The temperature difference between the maximum and the minimum varies with heat flux and/or mass flux. Heat transfer characteristics of supercritical water in bundle were discussed with respect to various heat fluxes. The effect of heat flux on heat transfer in rod bundles is similar with that in tubes or annuli. In addition, flow resistance reflected in the form of pressure loss has also been studied. Experimental results showed that the total pressure drop increases with bulk enthalpy and mass flux. Four heat transfer correlations developed for supercritical pressures water were compared with the present test data. Predictions of Jackson correlation agrees closely with the experimental 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 | 0.001 | 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) | 0.001 | 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".