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Using semipenetration ratio to characterise effects of waveform variables on bead profile and heat affected zone with single electrode submerged arc welding

2012· article· en· W1973768772 on OpenAlexaff
Joel Pepin, Christopher Penniston, H. Henein, Douglas G. Ivey, Laurie Collins, D. Boyd

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2012
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsEVRAZ (Canada)University of AlbertaQueen's UniversityTransCanada (Canada)Alberta Innovates
Fundersnot available
KeywordsWeldingWaveformMaterials scienceCharpy impact testSubmerged arc weldingPenetration (warfare)Composite materialElectrodeVoltageHeat-affected zoneMetallurgyElectrical engineeringMicrostructureChemistry

Abstract

fetched live from OpenAlex

When using alternating current submerged arc welding to produce pipes from microalloyed linepipe steel strip, it is necessary to balance penetration depth and deposition rates in order to minimise the number of weld passes while still maintaining good heat affected zone properties. A series of bead on plate submerged arc welds were performed on X70 steel, varying either traditional variables (i.e. current, voltage, travel speed and polarity) or waveform variables (i.e. balance, offset and frequency). Cross-section profile areas were measured, penetration profile shape [i.e. the semipenetration (SP) ratio] was calculated and hardness and Charpy V notch (CVN) impact testing were performed. By using a 3·2 mm welding wire with a constant current mode, increased current resulted in greater wire feed speeds (WFS), while WFS was reduced by increasing voltage or decreasing travel speed. Increased balance reduced WFS and increased weld penetration, while offset and frequency did not appear to significantly affect WFS or bead profile. Waveform variables did not have significant effects on Vickers hardness traverses. Preliminary CVN testing showed that using 30 Hz frequency resulted in lower fracture energies, and using 75% balance resulted in greater energies. Improved CVN results were achieved when welds were produced with lower heat input and greater SP ratio values.

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 score0.025
Threshold uncertainty score0.726

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 head0.201
Teacher spread0.192 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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