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Record W1995091604 · doi:10.1115/icone21-16448

Assessment of Choking Flow Models in RELAP5 for Flashing Flow Through Small Cracks

2013· article· en· W1995091604 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNuclear Engineering Thermal-Hydraulics
Canadian institutionsCanadian Nuclear Safety Commission
FundersCanadian Nuclear Safety CommissionNational Research Foundation of Korea
KeywordsChokingFlashingMechanicsThermal hydraulicsFlow (mathematics)Mass fluxTube (container)Slug flowEngineeringForensic engineeringHeat transferTwo-phase flowMechanical engineeringMaterials sciencePhysics

Abstract

fetched live from OpenAlex

The estimation of leak rates through steam generator tube crack is an important safety parameter. An assessment of the choking flow models in thermal-hydraulics code RELAP5 is performed and its applicability to predict choking flow rates through steam generator tube cracks is addressed. A RELAP5 nodalization was created to model experimental data from literature. It is found that both the Henry-Fauske and Ransom-Trapp models better predict choking mass flux for longer channels. As the length of a channel decreases the both models’ predictions diverge from each other. While RELAP5 has been shown to predict choking flow in large scale geometries, it is not suited well for small channel lengths. In the case of a more conservative approach, where over prediction of mass flux through short channels is best, the Henry-Fauske model would be most appropriate.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.484
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.229
Teacher spread0.210 · 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

Quick stats

Citations1
Published2013
Admission routes2
Has abstractyes

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