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Record W4299729743 · doi:10.31399/asm.cp.itsc2004p0645

Splat Formation in Wire Arc Spraying

2004· article· en· W4299729743 on OpenAlexaff
A. Pourmousa, S. Chandra, J. Mostaghimi

Bibliographic record

VenueThermal spray · 2004
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceSubstrate (aquarium)Deposition (geology)CoatingAluminiumComposite materialSplashAdhesionPorosityParticle (ecology)MetallurgyGas dynamic cold spray

Abstract

fetched live from OpenAlex

Abstract An experimental study was conducted to study the effect of impact velocity and substrate temperature on splat morphology using a wire arc spraying system. Aluminum was sprayed onto polished AISI304L substrates held at various temperatures. In-flight particle parameters (size, velocity, temperature) were measured using a DPV 2000 system. Individual splats deposited on the substrate were photographed. Comparisons between the in-flight particle size distribution and the final splat size distribution showed that increasing substrate temperature results in increased mean spread factor. A transition temperature from splash to disk splats was determined. Coatings were also produced at various substrate temperatures and porosity levels measured. The effect of substrate temperature on deposition efficiency and coating adhesion was measured. Increasing substrate temperature was found to improve both deposition efficiency and adhesion strength.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.216
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2004
Admission routes1
Has abstractyes

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