Tritium Research and Development Status at KAERI
Bibliographic record
Abstract
Korea has 26 nuclear power plants (NPPs). Out of these 26 plants, 4 are Canada Deuterium Uranium (CANDU) reactors at the Wolsong nuclear power site. In CANDU reactors, deuterium oxide is used as a moderator/coolant, and tritium is produced whenever a deuterium oxide nucleus captures a neutron. The Wolsong Tritium Removal Facility was designed to remove tritium generated in CANDU reactors. We are introducing tritium environmental protection not only at the Wolsong NPP but also at the High-Flux Advanced Neutron Application Reactor (HANARO) and in high-temperature gas-cooled reactors (HTGRs). We present a tritium behavior analysis code and assess the concentration of tritium in combustible dry active waste. Advanced techniques are introduced to transfer tritium from tritiated water to the gaseous phase. In addition, research on the nuclear fusion tritium storage and delivery system, which is part of the fuel cycle, has been carried out. In this paper, we present the recent progress in the effort to develop tritium systems at the Korea Atomic Energy Research Institute.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".