Comparison of CANDU Fuel Bundle Finite Element Model with Unirradiated Mechanical Load Experiments
Bibliographic record
Abstract
Abstract A requirement of spent nuclear fuel is to maintain its structural integrity at all times to enable its safe and efficient handling during storage, transportation, and placement in a deep geological repository. In Canada, commercial spent fuel is currently stored in light water pools for about ten years before being transferred to dry storage where storage may extend up to 100 years. Investigations on the fuel structural integrity evolution during dry storage are being performed for spent CANDU fuel bundles. A CANDU nuclear fuel bundle is a cylindrical assembly approximately 0.1 m in diameter and 0.5 m in length made of 28 or 37 fuel elements held together by welding two endplates at both ends. The welds have a circular notch of less than 10 μm diameter. Significant hydraulic, mechanical, and thermal loads during bundle irradiation in the reactor may lead to bundle deformation, which when coupled with the sharp weld notch can result in significant stress enhancement at the notch tip and possibly activate delayed hydride cracking (DHC) during dry storage. To better understand the stress levels in CANDU fuel during dry storage, a finite element model of CANDU fuel bundles is under development. The stress distribution in the bundle and the stress intensity factor at each weld notch can be evaluated by the model for the spent fuel geometry and dry storage conditions. This paper discusses the agreement between the finite element model and validation experiments using unirradiated 28-element CANDU fuel bundles tested in the elastic and plastic regime.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".