Numerical Simulation of Fluid Flow and Heat Transfer of the Supercritical Water in Different Fuel Rod Channels
Bibliographic record
Abstract
The supercritical water-cooled reactor was proposed as one of the Generation IV nuclear systems. Although many research works on the fluid flow and heat transfer of supercritical water in circular channels have been conducted, there is still lack of research on the fluid flow and heat transfer process in fuel bundles used in supercritical water-cooled nuclear reactors. Besides, fuel bundles have multiple fuel rods, the flow is an external flow, not internal flow as that in circle channels, which will cause the difference in the fluid flow phenomenon and heat transfer on the fuel rod cladding surface. In this work, the heat transfer and fluid flow characteristics of the supercritical water in the single-rod channel and the multi-rod channel are simulated numerically. The results show that there are secondary flows in both channels. The circumferential cladding surface temperature variation is large and should be considered in the future fuel rod design. With the same flow rate and heat flux input, the maximum cladding surface temperature in the multi-rod channel is much higher than that in the single-rod channel. Since the maximum cladding surface temperature is an important parameter for the safety of the nuclear reactor operation, it is recommended to use the multi-rod channel model to conduct numerical simulations for the fluid flow and heat transfer of the supercritical water in the Canadian SCWR.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".