Burnable absorber-integrated guide thimble (BigT) – II: application to 3D PWR core design
Bibliographic record
Abstract
This paper is a companion to its immediate predecessor in the “Burnable absorber-integrated Guide Thimble” (BigT) series. It aims to demonstrate potential applications of the BigT concepts in a three-dimensional (3D) commercial pressurized water reactor core, which is based on the AP1000 first core design. The study specifically compares neutronic characteristics of the reference core against a BigT-loaded design. In this study, reactivity depletion patterns of nine fuel assembly lattices in the reference core were first evaluated. Corresponding sets of BigT-loaded assemblies that yield neutronically similar characteristics (i.e., initial reactivity suppression and depletion trend) with those of the reference assembly lattices were determined next. These BigT-loaded fuel assemblies were later loaded in place of the reference fuel assemblies for the subsequent high-fidelity 3D Monte Carlo core simulations. Results of the study clearly demonstrate that the BigT-loaded AP1000 first core performs as well as the reference core since all neutronic parameters are comparable, especially in terms of reactivity depletion, power peaking factors and shutdown margin. All simulations were completed using the Monte Carlo Serpent code with ENDF/B-VII.0 library.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".