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Record W2063111089 · doi:10.1063/1.2717177

Sound generation by a street of vortices in a nonuniform flow

2007· article· en· W2063111089 on OpenAlexaff
Tinghui Zheng, Georgios H. Vatistas, Alex Povitsky

Bibliographic record

VenuePhysics of Fluids · 2007
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsConcordia University
Fundersnot available
KeywordsPhysicsVortexMach numberSound pressureVorticityAcousticsAmplitudeStarting vortexAcoustic waveMechanicsMean flowAeroacousticsDirectivityVortex ringTurbulenceOptics

Abstract

fetched live from OpenAlex

Propagation of acoustic waves originating from periodic vortices deforming in a nonuniform flow about a rigid body is examined numerically using a high-order compact finite-difference approximation. The governing equations are approximated by the linearized Euler equations in terms of disturbances. The aim of the study is to determine the sound directivity and strength as a result of the vortex street interaction with a solid body under subsonic base flow conditions. Both the vortex core diameter and vortex street spacing have a minor influence on the amplitude of the produced sound wave. When low-frequency vortex streets interact with a cylinder, the produced sound waves are very different from those that originated from high-frequency vortex streets. The interaction mechanism, sound generation, and propagation in a nonuniform flow are quite different for Taylor and Vatistas’ vortex streets. In the case of a low-frequency Vatistas vortex street, the root-mean-square (RMS) value of the acoustic pressure has a well-defined sound directivity and amplitude. The former is greatly affected by the Mach number of the mean flow. For a high-frequency Vatistas vortex street, the RMS of acoustic pressure becomes highly nonmonotonic in the angular direction, while the mean flow Mach number has a moderate effect on the RMS angular profile. The striking differences in the sound amplitude and directivity for Taylor and Vatistas vortices are discussed in terms of their vorticity distribution.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
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 head0.011
GPT teacher head0.228
Teacher spread0.218 · 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 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

Citations9
Published2007
Admission routes1
Has abstractyes

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