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Laser welding of Ti–5Al–5V–5Mo–3Cr

2011· article· en· W2011268979 on OpenAlexaffabout
Tasneem Shariff, X. Cao, Richard R. Chromik, Javad Gholipour Baradari, Priti Wanjara, J. Cuddy, A. Birur

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2011
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsMcGill UniversityCanadian Standards AssociationNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceWeldingUltimate tensile strengthComposite materialHeat-affected zoneLaser beam weldingButt jointMicrostructureMetallurgy

Abstract

fetched live from OpenAlex

Ti-5Al-5V-5Mo-3Cr butt joints were welded using a 4 kW continuous wave Nd:YAG laser. The effect of welding speed and defocusing distance on the weld quality was investigated. Welds with full penetration were achieved at a defocusing distance ranging from-1 to 0 mm and welding speeds from 2·25 to 6·0 m min -1. Underfill and porosity were the two main defects most frequently observed; however, within the optimum process window, these defects could be maintained to meet aerospace specification tolerances. The fusion zone consisted entirely of retained β with a refined dendritic morphology. Compared with the bimodal α+β microstructure of the base metal, dissolution of the α phase in the heat affected zone and the presence of entirely metastable/retained β phase in the fusion zone were observed, which led to a significant decrease in the HAZ and FZ hardness. To determine the tensile properties of the welds, an automated three-dimensional deformation measurement system was used to measure the local strain in the weld region. The yield strength and ultimate tensile strength increased with welding speed, achieving a maximum joint efficiency of 75%, albeit with a concomitant reduction in the ductility. © 2011 Canadian Institute of Mining, Metallurgy and Petroleum.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.999

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)0.0020.000

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 head0.018
GPT teacher head0.180
Teacher spread0.162 · 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.

Study designNot applicable
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

Citations14
Published2011
Admission routes2
Has abstractyes

Explore more

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