A Comparative Evaluation of Finite Element Modeling of Creep Deformation of Fuel Channels in CANDU® Nuclear Reactors
Bibliographic record
Abstract
A key element of the fuel channel life cycle management in CANDU® nuclear reactors is to prevent contact between the pressure tube (PT) and the calandria tube (CT) in a fuel channel. By preventing PT-CT contact, the development of hydride blisters and delayed hydride cracking of the PT can be avoided. The PT-CT contact is a result of in-reactor deformation due to irradiation induced creep of the fuel channel assembly. Excessive sagging of the PT can also interfere with the free passage of the fuel bundles when the channel is refueled. Contact of the CT with reactor control mechanisms located horizontally between the fuel channels can result from excessive sag of the CT. The prediction of dimensional changes due to in-reactor creep and the time of PT-CT contact is calculated using finite element modeling of the fuel channel with appropriate creep constitutive laws describing PT and CT deformation. The three-dimensional nature of creep deformation of fuel channels can be approximated by a one-dimensional finite element model (1D-FEM), which is a computationally tractable problem. However, the simplifications of a 1D-FEM model come at the expense of loss of prediction accuracy. This paper compares creep deformation analysis of fuel channels using 1D-FEM and 3D-FEM models. The comparison is based on PT and CT sag profiles as well as on PT-CT gap at different time intervals during service of the fuel channel. Results from the comparative analysis show that the 1D-FEM model predicts greater values of PT-CT gap. The difference in gap predicted between both FEM models increases rapidly when the minimum gap is located in the outlet span. At 250,000 equivalent full power hours, the 1D-FEM model overestimate the gap by 1.12 mm with respect to the 3D-FEM model.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".