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Record W2765354541 · doi:10.1115/pvp2017-65298

Aeroacoustic Source of Multiple Cavities and Prediction of Self-Excited Oscillations

2017· article· en· W2765354541 on OpenAlexaff
Ayman A. Shaaban, Samir Ziada

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsMcMaster University
Fundersnot available
KeywordsStrouhal numberPipingAcousticsOscillation (cell signaling)AmplitudeMechanicsFlow (mathematics)PhysicsNoise (video)Excited stateOpticsTurbulenceComputer scienceAtomic physics

Abstract

fetched live from OpenAlex

Self-sustaining oscillations of flow over ducted cavities and corrugated pipes proved to be a potential source of tonal noise and possible failure in industrial applications. Most of the recent studies focused on the flow over a single cavity to simplify the problem and establish basic understanding of the phenomenon. This paper investigates experimentally the flow over multiple cavities, specifically two and three-cavity configurations, and the results are compared with those of a single cavity. Two different categories of experiments were performed in this study. The first category of measurements quantified the aeroacoustic source of various cavity configurations as a function of Strouhal numbers and acoustic velocity of the resonant pipe mode. The cavities are situated at the acoustic pressure node of a piping system which was sufficiently long to maintain the acoustic velocity fairly constant along the test section. The second category involved self-excited oscillations where the cavities were tested in a short piping system. The flow velocity was gradually increased and the acoustic pressure amplitude and frequency were measured and the lock-in ranges for different shear layer modes were identified. A semi-empirical model is then developed to use the measured source to predict the self-excited oscillation amplitude.

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: Simulation or modeling
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
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.195
Teacher spread0.186 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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