Investigation of a SPH-based sub-cell homogenization for PHWR using a multi-cell model
Bibliographic record
Abstract
Superhomogenization (SPH) has gained interest in the industry as a possible method to overcome the inherent limitations of standard homogenization (SH) for full nuclearreactor-core neutronics calculations because its implementation does not require any changes to existing computer codes. Previous work found that single-cell SPH applied to Pressurized Heavy Water Reactors (PHWR) yields virtually no improvement compared to single-cell standard homogenization. This work attempts to improve those results by accounting for neutron leakage across cell boundaries by performing SPH-based homogenization using a 3??3 multi-cell model. The method is evaluated using a 5??5 lattice-cell model and comparing results for single-cell SH, multi-cell SH, single-cell SPH and multi-cell SPH. Results show that multi-cell SPH produces better results than single-cell SPH and multi-cell SH produces better results than single-cell SH. However, multi-cell SPH offers no improvement compared to multi-cell SH, just as single-cell SPH offers no improvement over single-cell SH.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".