On Distribution of Local Thermal and Mass Flow Rate Parameters of Two-Phase Coolant in the Bundle of 7 Rods
Bibliographic record
Abstract
Distribution of thermal and mass flow rate parameters of coolant in the cross-section of 7-rod bundle consisting of the tubes of 6.0-mm outside diameter and 1.0-m heated length for two types of discretization of its cross-section into characteristic cells is experimentally investigated by the method of isokinetic sampling. The range of operation parameters corresponds to the conditions of LOCA accompanied by pressure and flow rate decrease relative to the nominal ones and is as follows: bundle-averaged outlet vapor content varies from −0.6 to 0.2, outlet pressure is 6 and 10 MPa, bundle-averaged mass velocity varies from 300 to 1500 kg/(m2s), inlet temperature varies from deep subcooling to (ts − 20) °C, and heat flux rate reaches 1.0 kJ/kg. It is confirmed by the experiment that the surface in the gap between the peripheral rods is most probable place of burnout in the bundle. Physical model of two-phase flow in the bundle that considers it as the equivalent annular channel with an eccentricity is proposed. The programs of thermal-hydraulic computation of fuel assembly and their adaptation to the experimental data for the two types of discretization into characteristic cells are performed and comparative assessment of them is made. The data resulted from the study concerning one-phase coolant could be applicable for a reference estimation of heat transfer in future designs of the fuel bundles.
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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 | 0.000 |
| 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) | 0.001 | 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".