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Neutronics-thermalhydraulics coupled analysis of Canadian SCWR based on DONJON5 and CATHENA

2024· article· en· W4399314108 on OpenAlexafffundabout
U. Le Tennier, G. Marleau

Bibliographic record

VenueNuclear Engineering and Design · 2024
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Nuclear Laboratories
KeywordsNeutron transportPython (programming language)BundleNuclear engineeringCore (optical fiber)Computer scienceEngineeringSystems engineeringNuclear physicsProgramming languagePhysicsTelecommunicationsMaterials scienceNeutron

Abstract

fetched live from OpenAlex

In recent years, several studies of the Canadian SCWR led to design and modeling revisions, at both bundle and core scale, to cope with safety criteria. Here, these modifications are evaluated using coupled calculations between DONJON5 (core neutronics) and CATHENA (thermalhydraulics) for a steady-state core under normal operation conditions based on lattice calculations provided by DRAGON5. This article describes the coupling procedure, programmed in Python 3, that deals with input files modification, data management for both DONJON5 and CATHENA execution. Then the Canadian SCWR concept is assessed to highlight the limitations that should be addressed to complete the current design definition stage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.799

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.008
GPT teacher head0.166
Teacher spread0.157 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes3
Has abstractyes

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