MétaCan
Menu
Back to cohort
Record W1967335933 · doi:10.1115/ipc2014-33219

Accuracy of the Double-Clip on Gauge Method for Evaluating CTOD of SE(T) Specimens

2014· article· en· W1967335933 on OpenAlexafffund
Jason Yan, Yifan Huang, Wenxing Zhou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCrack tip opening displacementStrain gaugeMaterials scienceStructural engineeringFinite element methodGauge (firearms)Displacement (psychology)Fracture toughnessPipeline transportFracture (geology)Fracture mechanicsComposite materialCrack closureEngineeringMetallurgyMechanical engineering

Abstract

fetched live from OpenAlex

The crack tip opening displacement (CTOD)-based fracture toughness has been widely used for structural integrity assessment and strain-based design of oil and gas pipelines. The double-clip on gauge method has been used to experimentally determine CTOD. In this study, three-dimensional (3D) finite element analyses of clamped single-edge tension (SE(T)) specimens are carried out to investigate the accuracy of the CTOD evaluation equation associated with the double-clip on gauge method. The analysis considers SE(T) specimens with ranges of crack lengths (0.3 ≤ a/W ≤ 0.7) and specimen thickness (B/W = 0.5, 1 and 2). Based on the analysis results, a modified CTOD evaluation equation based on the double-clip on gauge method is developed to improve the accuracy of the CTOD evaluation. This study will facilitate the application of the fracture toughness determined from the SE(T) specimen in the strain-based design of pipelines.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.063
GPT teacher head0.348
Teacher spread0.285 · 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 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

Citations1
Published2014
Admission routes2
Has abstractyes

Explore more

Same topicFatigue and fracture mechanicsFrench-language works237,207