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Record W1904341417 · doi:10.3390/coatings5040576

A Comprehensive Review on Fluid Dynamics and Transport of Suspension/Liquid Droplets and Particles in High-Velocity Oxygen-Fuel (HVOF) Thermal Spray

2015· review· en· W1904341417 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCoatings · 2015
Typereview
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermal sprayingSuspension (topology)CombustionMaterials scienceCoatingMechanicsThermalGas dynamic cold sprayParticle (ecology)Mechanical engineeringComposite materialThermodynamicsEngineeringChemistryPhysics

Abstract

fetched live from OpenAlex

In thermal spraying processes, molten, semi-molten, or solid particles, which are sufficiently fast in a stream of gas, are deposited on a substrate. These particles can plastically deform while impacting on the substrate, which results in the formation of well-adhered and dense coatings. Clearly, particles in flight conditions, such as velocity, trajectory, temperature, and melting state, have enormous influence on the coating properties and should be well understood to control and improve the coating quality. The focus of this study is on the high velocity oxygen fuel (HVOF) spraying and high velocity suspension flame spraying (HVSFS) techniques, which are widely used in academia and industry to generate different types of coatings. Extensive numerical and experimental studies were carried out and are still in progress to estimate the particle in-flight behavior in thermal spray processes. In this review paper, the fundamental phenomena involved in the mentioned thermal spray techniques, such as shock diamonds, combustion, primary atomization, secondary atomization, etc., are discussed comprehensively. In addition, the basic aspects and emerging trends in simulation of thermal spray processes are reviewed. The numerical approaches such as Eulerian-Lagrangian and volume of fluid along with their advantages and disadvantages are explained in detail. Furthermore, this article provides a detailed review on simulation studies published to date.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.029
GPT teacher head0.264
Teacher spread0.235 · 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