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Record W1990150112 · doi:10.1504/ijmmp.2008.022042

Experimental investigation of propagation of wetting front on curved surfaces exposed to an impinging water jet

2008· article· en· W1990150112 on OpenAlexafffund
M. Akmal, Ahmed M. T. Omar, M. Hamed

Bibliographic record

VenueInternational Journal of Microstructure and Materials Properties · 2008
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceJet (fluid)WettingMicrostructureBoilingComposite materialRADIUSMechanicsFront velocityFront (military)ThermodynamicsMeteorologyPhysics

Abstract

fetched live from OpenAlex

The wetting phenomenon during the cooling of a hot cylindrical specimen exposed to an impinging water jet has been studied experimentally. The Speed of Propagation of Wetting Front (SPWF) and regions of boiling heat that transfer outwards from the jet stagnation point have been investigated using high-speed video images. The effect of various jet parameters (velocity, diameter, water temperature) and the effect of the surface temperature on SPWF have been considered. Experiments were conducted under transient conditions considering initial specimen surface temperatures of 250°C, 500°C and 800°C, water temperatures in the range between 20°C and 80°C, jet velocities of 5 m/s and 7.75 m/s and jet diameters of 3 mm and 4 mm. For all of the jet and surface parameters considered in the study, SPWF was found to correlate well with power functions of time (i.e., instantaneous wetting front radius R=a(t)n)). Within the considered range of parameters, the results indicate that SPWF is mostly affected by the initial surface temperature, water temperature and jet velocity. Since control of the product microstructure is the key in determining its mechanical properties, the results of the investigation of the SPWF are used to quench carbon steel (1045) cylinders using different combinations of jet parameters. The results show a great flexibility in achieving various cooling rates, as indicated by the change in the final microstructure of the quenched samples.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.023
GPT teacher head0.220
Teacher spread0.197 · 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 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

Citations28
Published2008
Admission routes2
Has abstractyes

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