Measurement and Analysis for Determination of PCR of the CANDU6 Core
Bibliographic record
Abstract
The power coefficient of reactivity (PCR) needs to be negative to achieve the inherent safety of a reactor. However, the possibility that the PCR of CANada Deuterium Uranium (CANDU) reactors can be positive has been raised in recent studies. In such circumstances, there was an experimental approach on evaluating the PCR of CANDU in 2012 at an in-operation CANDU reactor, Wolsong Unit 2. In the evaluation, the PCR was indirectly measured by a method that required estimating the reactivity variation due to Xe, liquid zone controllers (LZCs), and fuel depletion based on the measurement data. In this study, the PCR of a CANDU was reevaluated by the same methodology with more proper and detailed methods to estimate all the factors in addition to some minor reactivity corrections. The estimation of Xe and LZC reactivity was performed by an in-house three-dimensional code and Serpent2 in addition to RFSP-IST. Furthermore, several short studies regarding the factors that result in uncertainty of the Xe/LZC reactivity estimation were done in detail. First, a method to determine 14 LZC levels at a certain time based on the measurement data was appropriately selected through determining the features of the measurement data. The influence of the power transient scheme and the impact of local refueling transients due to daily refueling of CANDU reactors on xenon reactivity estimation were also analyzed briefly. Finally, the PCR of the CANDU in operational conditions was evaluated to be ~0.5 pcm/%P on average at a measurement time of 5 to 20 min after the power perturbation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".