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Record W2004224936 · doi:10.1115/pvp2012-78507

Residual Stress Distributions and Guidelines for Crack Inspection in Pipe Bends

2012· article· en· W2004224936 on OpenAlexafffund
M. Yetisir, Zane H. Walker

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsAtomic Energy (Canada)
FundersCANDU Owners Group
KeywordsResidual stressResidualBendingCrackingStress (linguistics)Materials scienceStructural engineeringStress corrosion crackingNuclear power plantForensic engineeringComposite materialEngineeringComputer scienceCorrosionPhysics

Abstract

fetched live from OpenAlex

Root cause investigations of feeder pipe cracks detected in one CANDU™ nuclear power plant indicated that the residual stress had a significant role in these failures. As a result, numerous residual stress measurements of pipe bends were obtained and models for predicting the residual stress distributions associated with various bending processes were developed. This paper provides a comprehensive review of pipe bend residual stress data and provides guidelines for identifying the most susceptible locations for targeted crack inspections. Residual stress data, generated since 1997 as part of the CANDU feeder cracking investigation, was compiled and presented for the quick dissemination of information. This information is summarized in quick lookup tables where likely crack locations are identified for pipe bends manufactured using various fabrication techniques.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.332

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 head0.056
GPT teacher head0.330
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2012
Admission routes2
Has abstractyes

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