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Record W2091530089 · doi:10.1115/pvp2014-28271

Quantitative Visualization of Unstable, Acoustically Coupled Shear Layers in Deep Axisymmetric Cavities

2014· article· en· W2091530089 on OpenAlexafffund
Peter Oshkai, Oleksandr Barannyk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMechanicsTurbulenceFlow visualizationParticle image velocimetryVorticityAmplitudeRotational symmetryAcousticsOpticsPhysicsFlow (mathematics)Vortex

Abstract

fetched live from OpenAlex

High-amplitude acoustic pressure fluctuations associated with locked-on, resonant flow states frequently occur in engineering systems that involve internal cavities located in pipelines, such as components of gas transport systems, steam delivery pipelines and jet engines. This paper describes the evolution of fully turbulent, acoustically coupled shear layers that form across deep, axisymmetric cavities. Effects of geometric modifications of the cavity edges on the separated flow structure were investigated using digital particle image velocimetry (PIV). The internal flow was non-intrusively accessed by means of a borescope, which allowed illumination and optical recording of flow tracers inside the cavity. Instantaneous, phase- and time-averaged patterns of velocity and vorticity provided insight into the flow physics during flow tone generation and noise suppression by the geometric modifications. In particular, the first mode of the shear layer oscillations was significantly affected by shallow chamfers located at the upstream and, to a lesser degree, the downstream edges of the cavity. Specifically, the introduction of the chamfers affected the phase and the location of formation of large-scale vortical structures in the shear layer, which is associated with a maximum of the vorticity thickness across the cavity opening. In turn, these changes in the flow structure affected the amplitude of acoustic pressure pulsations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.761
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.282
Teacher spread0.257 · 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

Citations6
Published2014
Admission routes2
Has abstractyes

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