Remote Fabrication of DUPIC Fuel Pellets in a Hot Cell under Quality Assurance Program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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