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Kinematic Viscosities of High‐Temperature Materials Used in Plasma Spraying

2011· article· en· W1931464052 on OpenAlexaff
André McDonald, S. Chandra

Bibliographic record

VenueJournal of the American Ceramic Society · 2011
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsKinematicsViscosityMaterials scienceActivation energyKinetic energyCeramicCubic zirconiaThermodynamicsMechanicsDissipationEnergy balanceYttria-stabilized zirconiaComposite materialChemistryPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

A simple analytical model based on the law of conservation of energy was developed to estimate the kinematic viscosity of high‐temperature materials. An energy balance between the kinetic, viscous dissipation, and surface energies of high‐speed molten droplets and the splats formed after impact and spreading was conducted to produce a nondimensional relationship between kinematic viscosity and the maximum spread factor of the splat. The dimensional kinematic viscosities of a wide variety of high‐temperature materials were determined and comparisons with experimentally measured viscosities were conducted. It was found that the predictions of the model agreed to within one order‐of‐magnitude of experimentally measured values. Experimental data for high‐temperature ceramics such as yttria‐stabilized zirconia were unavailable for comparison. However, the agreement between the model and experimental values of kinematic viscosity observed for alumina, coupled with the monoclinic fluorite structure and high density of zirconia, suggested that its kinematic viscosity was probably much lower than that of alumina, as predicted by the analytical model.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.347

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 head0.010
GPT teacher head0.197
Teacher spread0.188 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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