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Record W2076003378 · doi:10.1115/ipc2004-0249

Ductile Cracking Evaluation of X80/X100 High Strength Linepipes

2004· article· en· W2076003378 on OpenAlexaff
Teruki Sadasue, Satoshi Igi, Takahiro Kubo, Nobuyuki Ishikawa, Alan Glover, David Horsley, Masao Toyoda

Bibliographic record

Venue2004 International Pipeline Conference, Volumes 1, 2, and 3 · 2004
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsTransCanada (Canada)
Fundersnot available
KeywordsCrackingMaterials scienceWeldingComposite materialDuctility (Earth science)MetallurgyJoint (building)Deformation (meteorology)Structural engineeringCreep

Abstract

fetched live from OpenAlex

The ductile cracking behavior of girth weld joints, in X80 and X100 grade linepipe, was investigated using single edge notched (SENT) specimens, notched round bar (NRB) specimens and wide plate (WP) specimens. FE analyses were carried out to evaluate critical conditions for ductile cracking at the notch tip. The effect of Y/T ratio of base material on ductile cracking for welded joints was also studied. Ductile cracking from the notch tip in WP specimens can be estimated by using the critical equivalent plastic strain, which can be obtained from SENT or NRB specimens. In addition, a simplified prediction method for ductile cracking by using effective opening displacement was proposed and its validity demonstrated by comparison to the equivalent plastic strain at the notch tip. With respect to the influence of material properties on ductile cracking behavior, deformability of joint to ductile cracking was enhanced by reduction of Y/T ratio of base material. Based on the experimental results and FE analyses, pipe design to prevent ductile cracking from surface flaws under large deformation was discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.021
GPT teacher head0.273
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations7
Published2004
Admission routes1
Has abstractyes

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Same venue2004 International Pipeline Conference, Volumes 1, 2, and 3Same topicMetal Forming Simulation TechniquesFrench-language works237,207