Supercritical Water Choking Flow Experiments Through a Convergent-Divergent Test Section
Bibliographic record
Abstract
Abstract The heat transport system of Gen-IV supercritical water-cooled reactors (SCWRs) will operate at pressures close to 25 MPa and outlet temperatures of up to 625 °C. The design and safety analyses of this type of reactors still necessitate among others, experimental information and validation of critical (choked) flows models of water above the thermodynamic critical state. Up to now, choked flow data were collected at atmospheric discharge pressure conditions, without changing the discharge pressure to verify the occurrence of choking flow; in most of the cases, using fluids different from water. This paper presents experimental supercritical water choking flow data collected by using a convergent-divergent test section by changing the discharge pressure to verify the occurrence of choked flow. The critical mass flux is presented as a function of the temperature difference between a pseudo-critical temperature and the bulk fluid temperature. This representation allows us to assess similar experiments performed by using different test sections. Hence, a comparison of actual data with those previously obtained using 1.0 mm and 1.4 mm diameter sharp-edged orifices, shows peculiar differences. The actual experiments were limited by very low values of choking mass flow rates. Furthermore, in some cases, it was observed the presence of an increase in the discharge pressure that seems to indicate the existence of shock-wave structures. We are also able to estimate a pseudo-critical temperature difference below which choking flow systematically occurs.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".