Remote Fabrication of DUPIC Fuel Pellets in a Hot Cell under Quality Assurance Program
Bibliographic record
Abstract
The Korea Atomic Energy Research Institute (KAERI) has been developing the Direct Use of Spent Pressurized Water Reactor (PWR) Fuel in the CANada Deuterium Uranium (CANDU) Reactors (DUPIC) fuel fabrication technology since 1992, and the basic DUPIC fuel fabrication process was established in 2002. In order to demonstrate the robustness of the DUPIC fuel fabrication process through the irradiation test, it is important that a Quality Assurance (QA) program should be in place before a fabrication of the DUPIC fuel. Therefore, the Quality Assurance Manual (QM) for the DUPIC fuel was developed on the basis of the Canadian standard, CAN3-Z299.2-85. This manual describes the quality management system applicable to the activities performed for the DUPIC fuel fabrication at KAERI. In order to demonstrate the DUPIC fuel fabrication technology and produce qualified DUPIC fuel pellets, the process qualification tests were performed, which include three pre-qualification tests and three qualification tests. The characteristics of the DUPIC fuel pellets such as the sintered density, grain size, and surface roughness were measured and evaluated in accordance with the QA procedures. The optimum fabrication process of the DUPIC fuel pellet was also established based on the qualification results. Finally a production campaign was carried out to fabricate the DUPIC fuel pellets at a batch size of 1 kg following the QA program. As a result of the production campaign, qualified DUPIC fuel pellets were successfully produced and, therefore, the remote fuel fabrication technology of the DUPIC fuel pellet was demonstrated.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".