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Record W2001876349 · doi:10.1520/jai103521

Improved Zr-2.5Nb Pressure Tubes for Reduced Diametral Strain in Advanced CANDU Reactors

2011· article· en· W2001876349 on OpenAlexaffabout
Grant A. Bickel, M. Griffiths, A. Douchant, S. Douglas, O.T. Woo, A.G. Buyers

Bibliographic record

VenueJournal of ASTM International · 2011
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsMaterials scienceStrain (injury)Nuclear engineeringComposite material

Abstract

fetched live from OpenAlex

Abstract In an Advanced CANDU Reactor (ACR) (ACR is a registered trademark of Atomic Energy of Canada Limited), pressure tubes of cold-worked Zr-2.5Nb materials will be used in the reactor core to contain the fuel bundles and the light water coolant. They will be subjected to higher temperature, pressure, and flux than those in a CANDU (CANDU is a registered trademark of Atomic Energy of Canada Limited) reactor, and accordingly require a thicker wall (6.5 mm for ACR versus 4.2 mm for CANDU). In order to ensure that these tubes will perform acceptably over their 30-year design life in such an environment, a study to model and forecast the performance of these thicker pressure tubes has been undertaken. One of the main requirements for the pressure tube is to have low diametral creep. Based on previous experience with CANDU reactor pressure tube performance and manufacture, an assessment of the grain structure and texture of the ACR pressure tubes indicates that the in-reactor creep deformation will be improved. Analysis of the distribution of texture parameters from a trial batch of 26 tubes shows that the variability is reduced relative to tubes fabricated in the past. This reduction in variability together with a shift to a coarser grain structure will result in a reduction in diametral creep design limits and thus a longer economic life for the fuel channels of the advanced CANDU reactor.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.029
GPT teacher head0.259
Teacher spread0.230 · 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 designBench or experimental
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

Citations6
Published2011
Admission routes2
Has abstractyes

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