Flow around Nuclear rod bundles' simulations based on RANS and LES method respectively
Bibliographic record
Abstract
The flow across the rod bundles in reactor pressure vessel is an essential design consideration of nuclear power plants. Experiments and CFD simulations are both effective methods for the rod bundles design and flow mixing analysis. CFD methods have the advantage of timesaving and cheaper, while experiment data is more reliable. Different turbulence models can be chosen in CFD simulation and the results are sensitive to the choice. So two kinds of turbulence model were investigated in this paper to evaluate their applicabilities in rod bundles CFD simulation. They are RANS and LES. The results were compared to experiment data, and the experiment is the flow in 3x3 rod bundles. The comparison between the CFD simulation and experiment data was shown in this paper for validation. The results showed that although there were some difference between the simulation and experiment, RANS and LES are both effective methods in nuclear engineering for simulating flow around rod bundles of fuel assembles. LES simulation can predict the velocity's peak value better and can be used for rod bundles design in nuclear design and research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".