Determination of CANDU End Fitting Jacking Limits Using Elastic–Plastic Finite Element Analysis1
Bibliographic record
Abstract
In one CANDU reactor unit in Ontario, the west end fitting is designed to connect to the end shield via a stop collar. The outboard end of the stop collar is welded to an attachment ring, which shrink-fits on the end fitting body. The east side end fitting is supported by inboard and outboard journal rings resting on their respective bearing sleeves, which allow the “free” axial movement of the channel. In support of some maintenance activities, the west end fitting is required to be jacked to get certain clearance for accommodating the operating tools. The previous elastic calculation got the jacking limit of 8.89 mm, which did not provide enough clearance for tooling. In this paper, an elastic–plastic finite element analysis following ASME B&PV code Section III, Division 1, Subsection NB is performed to increase the jacking limit. The finite element analysis is carried out using ANSYS and validated by an ABAQUS model. In the elastic–plastic finite element analysis, the following effects are considered: strain hardening of stop collar material, stress concentration in stop collar weld, notch effect on stress concentration, and fatigue in stop collar. Cyclic jacking loads as displacement controlled loading are applied in the analysis. Considering the time to the end of unit life, the maximum anticipated end fitting jacking cycles are eight. The higher jacking limit is achieved with an acceptable plastic deformation and fatigue damage at the stop collar, which is the weakest part during the end fitting jacking. The results show that the end fitting can be jacked at west side end-face with 29.7 mm for 1–3 cycles, 29.2 mm for 4 cycles, 26.2 mm for 5 cycles, 24.1 mm for 6 cycles, 21.6 mm for 7 cycles, and 20.3 mm for 8 cycles. The jacking limits achieved in this paper provide enough clearance for the required maintenance operations.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".