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Record W2085348855 · doi:10.1115/1.3043821

Effect of CANDU Bundle-Geometry Variation on Dryout Power

2009· article· en· W2085348855 on OpenAlexaffabout
L.K.H. Leung

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2009
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsBundleNuclear engineeringMaterials scienceEnriched uraniumNatural uraniumUraniumMechanicsEnvironmental scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

Dryout powers have been evaluated at selected inlet-flow conditions for two proposed designs of Canada deuterium uranium, CANDU® (a registered trademark of Atomic Energy of Canada Limited (AECL)) bundles and compared with those of the 37-element and CANDU Flexible, CANFLEX® (a registered trademark of AECL and Korea Atomic Energy Research Institutes (KAERI)) bundles. These proposed designs consist of a large center element (18 mm for one design and 20 mm for the other) and three rings of elements of 11.5 mm in outer diameter. The critical heat flux for each bundle design has been predicted using the correlation derived with Freon data obtained from the corresponding full-scale bundle test. An improvement in dryout power has been shown for the proposed design having a 20 mm center element with a radial power profile corresponding to the natural-uranium fuel as compared with other bundles, particularly the natural-uranium 37-element bundle, with a symmetric-cosine axial power profile. The dryout power improvement is further enhanced for the upstream-skewed axial power profile.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.194
Teacher spread0.191 · 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

Citations8
Published2009
Admission routes2
Has abstractyes

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