AN IMPROVED DOUBLE HETEROGENEITY MODEL FOR PEBBLE-BED REACTORS IN DRAGON-5
Bibliographic record
Abstract
In pebble-bed reactors, the fuel is contained in small grains, which are included in a graphite matrix. Some burnable poison particles may also be present. In this work, an additional ’double heterogeneity’ model is introduced in the DRAGON5 lattice code. The model is based on the legacy work of She (INET) and has been improved to overcome intrinsic limitations. It is based on a simplified physical model whereas the two already existing models were based on the collision probability analysis or on renewal theory. The advantage of this new model is its simplicity to implement. The theory shows that the correction suggested in the original model should not be arbitrary, but a constant equivalent particle fraction of 0.63. Numerical comparison between the models is generally good. However it does not support the theory of a constant equivalent fraction. Additional work is needed to reduce the discrepancy between the models in some cases.
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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 | 0.001 |
| 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 | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".