MétaCan
Menu
Back to cohort
Record W2349118672

ON THE TOUGHNESS-INDUCED CRACK DECELERATION MECHANISM OF GAS PIPELINES TRANSMITTING GAS FROM THE WEST TO THE EAST

2004· article· en· W2349118672 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsDissipationFracture mechanicsMechanicsFracture toughnessFinite element methodPipeline transportStructural engineeringMaterials scienceToughnessStrain energy release rateCrack growth resistance curveCrack closureEngineeringComposite materialMechanical engineeringPhysicsThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

A numerical analysis method is developed to solve the problem of crack propagation in gas pipelines. It is based on the fundamental theories, methods and arrest criteria in dynamic fracture mechanics as well as finite element method (FEM) in shell dynamics. For high toughness pipelines, the decrease of heat dissipation caused by plastic work unloading cannot be neglected. By referring to the energy balance equation under the condition of nonuniform crack propagation, an iterative method is constructed to solve the instant speed in FEM. The dynamic fracture toughness comprised mainly of the heat dissipation rate is obtained through experiments, and is used as the given function of crack speed, to replace the original steady propagation mode and form the toughness-induced deceleration mechanism. To determine the parameters required in calculation, the two-specimen DWTT method is deducted to determine the heat dissipation rate formula.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.429

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 head0.021
GPT teacher head0.222
Teacher spread0.201 · 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