Power Mapping in a Canada Deuterium Uranium Reactor Using Kalman Filtering Technique.
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Bibliographic record
Abstract
For a Canada Deuterium Uranium 600 MWe (CANDU 6) reactor, a new power mapping method has been developed by using detector readings as boundary conditions. In this study, the measured detector readings are combined with the diffusion theory with the Kalman filtering (DIKAL) method. The measured detector readings are transformed into the measured mesh flux through appropriate approximation. And, the difference between calculated and measured mesh flux is filtered out by Kalman filtering technique. Then, the measured mesh fluxes are used as an internal boundary condition in the diffusion equation. The performance of the DIKAL method has been assessed for the various core states, and has been also applied to the calculation of power and flux distribution calculation in the CANDU 6 reactor. Sensitivity studies have shown that DIKAL is quite stable to the detector random and systematic errors. Also, it is shown that the DIKAL approach is more accurate than the currently used flux synthesis approach in CANDU 6 reactors.
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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 | 0.000 | 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 | 0.000 |
| 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