Tritium Emission Reduction at Darlington Tritium Removal Facility Using a Bubbler System
Why this work is in the frame
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Bibliographic record
Abstract
Ontario Power Generation Nuclear (OPGN) has a 4 x 880 MWe CANDU nuclear station at its Darlington Nuclear Division located in Bowmanville. The station operates a Tritium Removal Facility (TRF) to reduce and maintain low tritium levels in the Moderator and Heat Transport heavy water systems of Ontario’s CANDU fleet by extracting, concentrating, immobilizing and storing as a metal tritide. Minimizing tritium releases to the environment is of paramount importance to ensure that dose to the public is as low as reasonably achievable (ALARA) and to maintain credibility with the Public. Tritium is removed from the Cryogenic Distillation System to the Tritium Immobilization System (TIS) glove box via a transfer line that is protected by a rupture disc and relief valve. An overpressure event in 2003 had caused the rupture disc to blow, resulting in the release of a significant quantity of elemental tritium into the relief valve discharge line, which ties into the contaminated exhaust system.As a result of a few similar events occurring over a number of years of TRF operation, the released elemental tritium would have been converted to tritium oxide in the presence of a stagnant moist air environment in the stainless steel discharge line. A significant amount of tritium oxide hold-up in the discharge line was anticipated. To minimize any further releases to the environment, a Bubbler System was designed to remove and recover the tritium from the discharge line.This paper summarizes the results of several Bubbler recovery runs that were made over a period of a month. Approximately 3500 Ci of tritium oxide and 230 Ci of elemental tritium were removed and collected. The tritium contained in the water produced from the Bubbler system was later safely recovered in the station’s downgraded D2O clean-up and recovery system.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it