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Correlation Between the Critical Heat Flux and the Fractal Surface Roughness of Zirconium Alloy Tubes

2001· article· en· W2033887036 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.

Bibliographic record

VenueEnhanced heat transfer/Journal of enhanced heat transfer · 2001
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsMaterials scienceSurface roughnessZirconiumFractalAlloySurface finishMechanicsMetallurgyComposite materialMathematicsPhysics

Abstract

fetched live from OpenAlex

In CANDU® fuel channels, Zircaloy calandria tubes isolate the hot pressure tubes from the cool heavy water moderator. The heavy-water moderator provides a backup heat sink during some postulated loss-of-coolant accidents. The decay heat from the fuel is transferred to the moderator to ensure fuel channel integrity during emergencies. Moderator temperature requirements are specified to ensure that the transfer of decay heat does not exceed the critical heat flux (CHF) on the outside surface of the calandria tube. An enhanced CHF provides increases in safety margin. Pool boiling experiments indicate the CHF is enhanced with glass-peening of the outside surface of the calandria tubes. The objective of this study was to evaluate the surface characteristics of glass-peened tubes and relate these characteristics to CHF. The microtopologies of the tube surfaces were analysed using stereo-pair micrographs obtained from scanning electron microscopy (SEM) and photogrammetry techniques. A linear correlation was found between the CHF and the 'fractal' surface roughness of the tubes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.014
GPT teacher head0.253
Teacher spread0.239 · 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