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Record W2988537149 · doi:10.1115/1.4045449

Experimental and Numerical Investigation on Ductile Fracture of Steel Pipelines

2019· article· en· W2988537149 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 · 2019
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFracture toughnessMaterials scienceFracture (geology)Pipeline transportStructural engineeringFinite element methodStress (linguistics)Geotechnical engineeringComposite materialGeologyEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Rupture of steel pipelines leads to the loss-of-containment that may be accompanied with loss of life or damage to property and environment. Therefore, the understanding of the fracture characteristics of steel grades used in the pipelines is essential for a safe and reliable design. In this study, a set of small-scale fracture tests was designed and conducted in order to characterize the fracture of X65 steel grade. The experimental results show that not only is the fracture strain dependent on the triaxial stress condition but also the three-dimensional nature of the stress field considerably affects the ductile fracture toughness. Moreover, parallel finite element (FE) simulation of experiments were conducted and a hybrid experimental–numerical approach was used to calibrate the Mohr–Coulomb fracture criterion and obtain the equivalent plastic strain to fracture of X65 steel as a three-dimensional function of stress triaxiality and Lode angle. An engineering application friendly ductile fracture model is proposed for X65 steel 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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.359

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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