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Record W2086409660 · doi:10.1115/1.4006125

Probabilistic Transgranular Stress Corrosion Cracking Analysis for Oil and Gas Pipelines

2012· article· en· W2086409660 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

VenueJournal of Pressure Vessel Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsIntergranular corrosionStress corrosion crackingProbabilistic logicCrackingFailure assessmentMaterials scienceStructural engineeringCorrosionStress (linguistics)Fracture (geology)Computer scienceEngineeringMetallurgyComposite materialArtificial intelligence

Abstract

fetched live from OpenAlex

The crack morphology of transgranular stress corrosion cracking (TGSCC) suggests that the mechanism of growth and the condition at which TGSCC occur is different than that of intergranular stress corrosion cracking (IGSCC). Several attempts have been made to characterize IGSCC probabilistically; however, limited effort has been noticed for TGSCC. This paper attempts to analyze TGSCC probabilistically. The study includes assessment of probability of failure for low pH, TGSCC by R6 approach/BS 7910 approach/API 579 approach, which considers plastic yielding and linear elastic fracture mechanics, CSA Z 662-07 burst model approach and author’s proposed strain-based approach. The paper observes that failure assessment diagram (FAD) based approaches (R6, BS 7910, and API 579) calculate least failure probability compared to CSA Z 662-07 burst model approach. The authors also noticed that their proposed hoop strain-based approach calculates closely to CSA Z 662-07 burst model approach. Finally, the authors justified the rationality of the results obtained by their approach.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.241
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