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Record W2614814234 · doi:10.2172/836450

Imaging of Acoustically Coupled Oscillations Due to Flow Past a Shallow Cavity: Effect of Cavity Length Scale

2004· report· en· W2614814234 on OpenAlexaff
Peter Oshkai, Mert Geveci, D. Rockwell, M. Pollack

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsParticle image velocimetryIntermittencyAcousticsTurbulenceFlow (mathematics)Laminar flowPhysicsMechanicsModulation (music)VorticityOpticsVortex

Abstract

fetched live from OpenAlex

Flow-acoustic interactions due to fully turbulent inflow past a shallow axisymmetric cavity mounted in a pipe, which give rise to flow tones, are investigated using a technique of high-image-density particle image velocimetry in conjunction with unsteady pressure measurements. This imaging leads to patterns of velocity, vorticity, streamline topology, and hydrodynamic contributions to the acoustic power integral. Global instantaneous images, as well as time-averaged images, are evaluated to provide insight into the flow physics during tone generation. Emphasis is on the manner in which the streamwise length scale of the cavity alters the major features of the flow structure. These image-based approaches allow identification of regions of the unsteady shear layer that contribute to the instantaneous hydrodynamic component of the acoustic power, which is necessary to maintain a flow tone. In addition, combined image analysis and pressure measurements allow categorization of the instantaneous flow patterns that are associated with types of time traces and spectra of the fluctuating pressure. In contrast to consideration based solely on pressure spectra, it is demonstrated that locked-on tones may actually exhibit intermittent, non-phase-locked images, apparently due to low damping of the acoustic resonator. Locked-on flow tones (without modulation or intermittency), locked-on flow tones with modulation, and non-locked-on oscillations with short-term, highly coherent fluctuations are defined and represented by selected cases. Depending on which of these regimes occur, the time-averaged Q (quality)-factor and the dimensionless peak pressure are substantially altered.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.240
Teacher spread0.229 · 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.

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

Citations0
Published2004
Admission routes1
Has abstractyes

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