Computational Fluid Dynamics investigation of the impact of 6% crept pressure tubes on flow behaviour, fuel temperature, and pressure tube wall temperature of a single CANDU 37M fuel bundle
Bibliographic record
Abstract
CANDU nuclear generating stations experience aging effects that affect the reactor operation, including pressure tube deformation ( i.e ., diametral expansion, sag, and elongation). The diametral expansion of the pressure tube will alter coolant flow behaviour, which will impact CANDU fuel and pressure tube temperatures, thereby directly affecting the reactor’s operational performance and safety margins. However, these impacts are not yet fully understood at this point. In this study, two Computational Fluid Dynamics simulations were conducted with STAR CCM+ on a single CANDU Modified 37-element (37M) fuel bundle placed in both non-crept and 6% crept pressure tubes under normal operating conditions. The predicted coolant flow behaviour, fuel temperatures, and pressure tube wall temperatures were compared between both cases to predict the impact of diametral expansion on these aspects. The results indicate that approximately 29% of the coolant flow bypasses the bundle in the 6% crept pressure tube, leading to a reduction of up to 25% in subchannel flow velocity and a maximum increase of 36.7 K in fuel maximum temperature. Both the non-crept and 6% crept pressure tube wall temperature profiles were found to be asymmetric with respect to the bundle’s horizontal axis. The temperature at the bottom of the pressure tube is relatively higher than at the top in the non-crept case, while the temperature difference is noticeably greater in the 6% crept case. • This work performed two CFD simulations with heat transfer on a CANDU 37M bundle. • This work predicted the fuel temperature for a bundle in non-crept and 6% crept PTs. • This work predicted the PT temperature for a bundle in non-crept and 6% crept PTs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".