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Record W2026592964 · doi:10.1115/1.2842225

Numerical and Experimental Studies of Oscillatory Airflows Induced by Rotation of a Grass-Cutting Blade

2008· article· en· W2026592964 on OpenAlexafffund
F. Abbasian, Jun Cao, S. D. Yu

Bibliographic record

VenueJournal of Fluids Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsToronto Metropolitan University
FundersOntario Centres of Excellence
KeywordsBlade (archaeology)AcousticsFinite volume methodNoise (video)MechanicsCompressibilityRotation (mathematics)VibrationSound pressureTetrahedronComputer simulationMathematicsPhysicsStructural engineeringGeometryComputer scienceEngineering

Abstract

fetched live from OpenAlex

Three-dimensional oscillatory airflows induced by a rotating grass-cutting blade in a cylindrical chamber are studied experimentally and numerically in this paper. Experimental pressure results are obtained using a sound pressure transducer and a data acquisition system. The measured pressure data contain background noise and high-frequency sound signals due to the blade vibrations. The background noise is separately measured; its effect on the signal is determined from a spectral subtraction algorithm. A time-accurate finite volume numerical solution to the three-dimensional incompressible unsteady Navier–Stokes equations is also sought using the sliding frame technique and the unstructured tetrahedral mesh. Convergence studies are conducted using various combinations of mesh sizes and time increments to ensure the stability of the numerical scheme. The experimental and numerical pressure results are in good agreement.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · 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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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 designSimulation or modeling
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
Published2008
Admission routes2
Has abstractyes

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