Bibliographic record
Abstract
There are an increasing number of nuclear reactors around the world operating well beyond their original design lives. Some pump seals supplied by original equipment manufacturers are either no longer available or their performance does not meet current requirements. This paper describes both the testing and operational experience of two nuclear pump seals that have been developed by AECL to replace the original equipment manufacturer’s seals in AECL’s National Research Universal reactor, which has been operating since 1957. The two seals described are the main heavy water pump seal and the heavy water degassing pump seal. The main heavy water pump seal is a tandem seal containing two identical, but 180° offset, eccentric seals of 95 mm balance diameter. The requirements were low pressure (0.3 MPa), low leakage (< 0.2 mL/min) and long, reliable lifetime (seven years). The seals were arranged to put full pressure across the outboard seal initially, with the inboard seal providing complete back up in the event of an outboard seal failure. Laboratory testing and operational performance, since initial installation in 1993, is described. The heavy water de-gassing pump seal design is based upon the main heavy water pump seal (a tandem seal containing two identical, but 180° offset, eccentric seals) but its balance diameter of 65 mm is much smaller than that of the main heavy water pump seal. Laboratory testing and operational performance, since initial installation in 2001, is also described.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".