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Record W2078641572 · doi:10.1115/ipc2014-33059

Characteristics, Causes, and Management of Circumferential Stress-Corrosion Cracking

2014· article· en· W2078641572 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsResidual stressStress corrosion crackingCorrosionMaterials scienceCrackingStructural engineeringStress (linguistics)Ultimate tensile strengthCylinder stressGeotechnical engineeringForensic engineeringGeologyMetallurgyEngineeringComposite material

Abstract

fetched live from OpenAlex

While much more rare than axial stress-corrosion cracking (SCC), circumferential SCC (CSCC) has been observed in pipelines in Canada, the United States, and two European countries. In some cases, the CSCC has been of sufficient size to cause in-service leaks. Because the orientation of stress-corrosion cracks invariably is perpendicular to the maximum tensile stress, the axial stresses at the locations of the cracks must have been greater than the hoop stress. The Poisson effect and thermal effects can account for about half of the axial stresses. Evidence from the field suggests that there are three probable sources of additional axial stresses that can promote CSCC: residual stresses in bent pipe, axial stresses caused by movement of unstable soil on slopes, and residual stresses opposite rock dents. CSCC can be managed by one or a combination of the following procedures: direct assessment (DA), in-line inspection (ILI), or hydrostatic testing. Guidance for selection of sites for DA is derived from industry experience, which was determined from responses to a questionnaire and published reports. The capabilities of ILI to detect circumferential stress-corrosion cracks or the conditions that promote them are summarized. The benefits and limitations of hydrostatic testing also are described. A method for calculating the size of circumferential flaws that can cause ruptures is presented and compared with service experience. That information can provide useful guidance for ILI requirements and decisions about which flaws need to be removed immediately.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.259

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 head0.008
GPT teacher head0.215
Teacher spread0.206 · 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