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Record W2069592520 · doi:10.1051/snamc/201404307

Integration of the DRAGON5/DONJON5 codes in the SALOME platform for performing multi-physics calculations in nuclear engineering

2014· article· en· W2069592520 on OpenAlexaff
Alain Hébert

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsComponent (thermodynamics)Thermal hydraulicsComputer scienceCode (set theory)Computational scienceSet (abstract data type)Software engineeringSystems engineeringMechanical engineeringProgramming languagePhysicsEngineeringMechanics

Abstract

fetched live from OpenAlex

We are presenting the computer science techniques involved in the integration of codes DRAGON5 and DONJON5 in the SALOME platform. This integration brings new capabilities in designing multi-physics computational schemes, with the possibility to couple our reactor physics codes with thermal-hydraulics or thermo-mechanics codes from other organizations. A demonstration is presented where two code components are coupled using the YACS module of SALOME, based on the CORBA protocol. The first component is a full-core 3D steady-state neuronic calculation in a PWR performed using DONJON5. The second component implement a set of 1D thermal-hydraulics calculations, each performed over a single assembly.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.017
GPT teacher head0.208
Teacher spread0.192 · 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 designNot applicable
Domainnot available
GenreSoftware

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

Citations4
Published2014
Admission routes1
Has abstractyes

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