Design and Simulation of a Dryer Regeneration Control System for a Tritium Removal Facility
Bibliographic record
Abstract
For decades, Ontario Power Generation’s (OPG’s) CANDU nuclear reactors have provided clean, reliable, and safe power for millions, as well as important radioactive isotopes for the world. Demand for Tritium is only growing, as it is a critical fuel for nuclear fusion – and OPG has the world’s only non-military supply of this isotope. There are several internal and external hazards associated with the operation of a tritium removal facility, which are not limited to fire, exposure to radioactive materials, explosion due to Hydrogen (H2) and the release of radioactive substances from the Tritium Immobilization System. This paper presents an advanced PLC-based, Air Clean-Up System (ACS), to detritiate room air during acute tritium leaks, preventing environmental escape and in-building accumulation. The study includes system modeling, MATLAB-based simulation, PID tuning, PLC ladder logic development, and Human- Machine Interface (HMI) design using MATLAB GUI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".