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Record W1753260126 · doi:10.1520/stp11401s

Development of Crystallographic Texture in CANDU Calandria Tubes

2002· book-chapter· en· W1753260126 on OpenAlexaff
JR Theaker, CE Coleman

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsTexture (cosmology)Materials scienceCrystallographyNuclear engineeringChemistryComputer scienceArtificial intelligenceEngineeringImage (mathematics)

Abstract

fetched live from OpenAlex

The Zircaloy-2 calandria tubes in a CANDU nuclear reactor separate the hot Zr-2.5Nb pressure tubes from the cool moderator. These tubes are about 6 m long, have an outside diameter of 132 mm, and a wall thickness of 1.4 mm. To date, their performance has been exemplary. A possible feature for future reactors is to increase the strength of these calandria tubes to reduce the economic consequences of a hypothetical accident. The current method of fabrication is to form a sheet of Zircaloy-2 into a cylinder, then weld along the length. In fixed-end burst tests such tubes always fracture in the weld area because of the differences in crystallographic texture between the parent metal and the weld; eliminating the weld would increase the strength and ductility of the tube. We have evaluated four manufacturing routes for seamless tubes. To realize high biaxial strength, we require a large fraction of basal plane normals in the radial direction, FR. This paper describes these manufacturing routes, the calandria tube properties generated by the individual manufacturing routes, and their applicability for the CANDU system. The results show that the biaxial strength of a seamless calandria tube becomes greater with an increase in FR, which is related to the amount of cold work used to make the tubes, with saturation in FR after about 95% cold work. The results are interpreted in terms of anisotropic factors determined from uniaxial tension tests.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.986
Threshold uncertainty score0.998

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)0.0030.000

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 head0.176
Teacher spread0.162 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2002
Admission routes1
Has abstractyes

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