Tritium Emissions from a Detritiation Facility
Bibliographic record
Abstract
Tritium is produced in heavy-water reactors through neutron capture by the deuterium atom. Annual production of tritium in a CANDU reactor is typically 52-74 TBq/MW(e). Some CANDU reactor operators have implemented detritiation technology to reduce both tritium emissions and dose to workers and the public from reactor operations. However, tritium removal facilities also have the potential to emit both elemental tritium and tritiated water vapor during operation. Authorized releases to the environment, in Canada, are governed by Derived Release Limits (DRLs). DRLs represent an estimate of a release that could result in a dose of 1 mSv to an exposed member of the public. For the Darlington Nuclear Generating Station, the DRLs for airborne elemental tritium and tritiated water emissions are ∼15.6 PBq/week and ∼825 TBq/week respectively. The actual tritium emissions from Darlington Tritium Removal Facility (DTRF) are below 0.1% of the DRL for elemental tritium and below 0.2% of the DRL for tritiated water vapor. As part of an ongoing effort to further reduce tritium emissions from the DTRF, we have undertaken a review and assessment of the systems design, operating performance, and tritium control methods in effect at the DTRF on tritium emissions. This paper discusses the results of this study.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".