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Record W2077207391 · doi:10.1115/ipc2010-31021

Effect of Fracture Speed on Ductile Fracture Resistance: Part 2—Results and Application

2010· article· en· W2077207391 on OpenAlexaff
Da-Ming Duan, Joe Zhou, Do-Jun Shim, Gery Wilkowski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsTransCanada (Canada)
Fundersnot available
KeywordsFracture toughnessFracture (geology)Materials scienceFracture mechanicsPipeline (software)Pipeline transportToughnessComposite materialWork (physics)Mechanical engineeringEngineering

Abstract

fetched live from OpenAlex

One of the many aspects of natural gas pipeline design and material selection is the consideration of propagation and arrest of high-speed axial ductile fracture in the line pipes. Understanding the material ductile fracture behavior is essential for establishing an integrated fracture control plan. This is particularly important for pipelines of high design pressures utilizing large-diameter and high-grade line pipes. The procedure of Battelle Two-Curve Method (TCM) has been most commonly used in ductile fracture analysis in the prediction of fracture speed and minimum arrest toughness for axially running cracks. In the past decades, discussions and research have been in that the TCM approach, among with others, could not accurately predict either fracture speed or minimum arrest fracture toughness for high-grade pipes, and with pipe grade increasing the prediction errors are getting larger. Recent research work at TransCanada indicates that for a better prediction of pipeline ductile fracture, understanding the basic material mechanical behavior and its fundamental fracture mechanism is essential. One of the important findings of the work is that pipe material fracture toughness is not a constant as being commonly treated, rather the fracture toughness, in terms of both steady-state CTOA and steady-state DWTT fracture energy is fracture speed dependent, being decreasing with increasing fracture speed. Corresponding modifications have been made to the traditional TCM by introducing speed-dependent fracture toughness. The improved model gives much better predictions in both fracture speed and toughness for high grade pipes. This paper presents recent work at TransCanada, together with its industry partner Engineering Mechanics Corporation of Columbus (EMCC), on high-speed pipe-material fracture testing technique (using the modified back-slot DWTT specimen) and high-grade material testing data. The test data supports the predictions of early published work on speed-dependent fracture toughness. The fracture speeds obtained from the modified back-slot DWTT specimens were very close to actual full-scale pipeline ductile fracture speeds and this in turn enhanced the applicability of the modified TCM model.

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 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 score0.090
Threshold uncertainty score0.459

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 head0.003
GPT teacher head0.208
Teacher spread0.206 · 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 teacher head, 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

Citations5
Published2010
Admission routes1
Has abstractyes

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