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Record W3099606740 · doi:10.29391/2020.99.020

Bond Formation Mechanism for Resistance Welding of X70 Pipeline Steel

2020· article· en· W3099606740 on OpenAlexaff
Rangasayee Kannan, LEIJUN LI, LULU GUO, Neil Anderson, Imran Rashid, Laurie Collins, M. Arafin

Bibliographic record

VenueWelding Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsEVRAZ (Canada)University of Alberta
Fundersnot available
KeywordsWeldingMaterials scienceMetallurgyMicrostructureFerrite (magnet)Heat-affected zoneAusteniteDecarburizationFlash weldingElectric resistance weldingComposite materialGas metal arc welding

Abstract

fetched live from OpenAlex

A Gleeble® thermo-mechanical simulator combined with microstructure characterization using a field emission scanning electron microscope was used to provide insights into the seam weld formation during resistance welding (RW). Gleeble® was used to physically/microstructurally simulate the seam weld formation during RW for the first time. It was found that a peak temperature of 1500˚C and 10-mm stroke produced a microstructure in the solid-state bondline, the flash, and the heat-affected zone similar to the resistance welded pipe manufactured in an industrial scale. Using the force response obtained during seam weld formation in Gleeble®, microstructure characterization of the seam weld, and thermodynamic calculations, it is pro-posed the seam weld in a resistance weld consists of a mushy zone with delta ferrite and solute-enriched liquid, which solidifies into austenite, and on post welding cooling, transforms into ferrite and stringers of M/A, respectively. The presence of a mushy zone in the weld joints provides a physical explanation for the “decarburization” phenomenon observed in the seam of resistance welds.

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: none
Teacher disagreement score0.908
Threshold uncertainty score0.434

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 head0.212
Teacher spread0.191 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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