Development of NEMESI: A Multiparameter Library Generator Prototype for Industrial VVER and PWR Applications Based on APOLLO3®
Bibliographic record
Abstract
A nuclear reactor’s design and safety assessment relies on a calculation platform consisting of a series of calculations performed using different simulation tools, each dedicated to modeling a specific phenomenon. The European Union H2020 CAMIVVER Work Package 4 aims to establish lattice neutronics calculation methodologies for VVER and pressurized water reactor fuel assemblies employing the new-generation deterministic multipurpose neutron transport code APOLLO3®, developed by the CEA (Commissariat à l’Énergie Atomique et aux Énergies Alternatives) with the support of EDF (Electricité de France) and Framatome.The present work aims to present NEMESI, an industrial prototype of a flexible lattice calculation tool developed as part of the CAMIVVER project, showing the applicability of APOLLO3 for industrial research and development and proposing dedicated VVER calculation schemes. Given the intense focus on the industrial issues of the entire CAMIVVER project, the elements constituting the rationale behind the development of such a computational platform are flexible modeling and analysis options, compliance with a series of specified requirements, implementation of innovative algorithms with improved precision, and a modern software and architectural base.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.007 |
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".