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Record W4299137823 · doi:10.31399/asm.cp.itsc2004p0632

Interactions Between Molten Metal Splats Landing on a Substrate during Coating Formation

2004· article· en· W4299137823 on OpenAlexaff
Rajeev Dhiman, S. Chandra

Bibliographic record

VenueThermal spray · 2004
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceSubstrate (aquarium)Composite materialDrop (telecommunication)Surface finishMetallurgyMechanical engineeringGeology

Abstract

fetched live from OpenAlex

Abstract Interactions between multiple splats landing on a substrate was studied experimentally by photographing deformations of droplets as they land and freeze on the substrate, or previously solidified splats. Uniform-size molten tin droplets (550 µm diameter) were produced using a drop-on-demand generator. To achieve high impact velocities the stainless steel coupons used as substrates were mounted on the rim of a rotating flywheel and heated using cartridge heaters to vary substrate temperature. To hit a falling droplet with the substrate and photograph its impact, a timing circuit was used to synchronize the ejection of a droplet, triggering of the camera and a flash to provide illumination. The substrate temperature and substrate roughness significantly affected splat impact dynamics. Droplets hitting a smooth cold substrate splashed extensively whereas those hitting a hot substrate spread in the form of a smooth disc. The final splat shapes were dependent on the offset distance between the impacting droplet and the previously solidified splat. The size of fingers around the splat edge increased with the offset distance. Large pieces of metal detached from the droplet rim when the droplet hit a rough substrate whereas droplets hitting previously solidified splats splashed in a star-like shape with extremely long fingers.

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 score0.269
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 head0.017
GPT teacher head0.225
Teacher spread0.208 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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