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Non-wetting behaviour of tungsten carbide powders in nickel weld pool: new loss mechanism in GMAW overlays

2013· article· en· W2018694060 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

VenueScience and Technology of Welding & Joining · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceGas metal arc weldingTungsten carbideMetallurgyWettingCarbideDissolutionWeldingTungstenComposite materialArc weldingChemical engineering

Abstract

fetched live from OpenAlex

This paper presents a new mechanism, observed directly for the first time, to explain low carbide fractions in Ni–WC overlays produced with GMAW. In this loss mechanism, a significant amount of powder loss is a consequence of the non-wetting behaviour of tungsten carbide. High speed videography and quantitative metallography of weld deposits are used to identify this mechanism. The non-wetting mechanism found acts simultaneously with the carbide dissolution mechanism, which until now was the only suggested cause of low carbide fraction in GMAW Ni–WC overlays. The non-wetting behaviour is observed in both short circuit and free flight metal transfer, accounting for carbide losses between 20 and 70% in the experiments performed. Low carbide fraction has prevented the mainstream use of GMAW for Ni–WC overlays, despite the advantages of simplicity, capability of in situ repair, and low capital costs. The findings presented here have a potential large impact for further consumable and process development.

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 score0.035
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.205
Teacher spread0.200 · 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