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Flow Induced Acoustic Resonances of an Annular Duct With Co-Axial Side Branches

2006· article· en· W2072068327 on OpenAlexaff
David Arthurs, Samir Ziada, Rafael Bravo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDuct (anatomy)AcousticsAxial compressorMaterials scienceAcoustic resonanceWavelengthMechanicsOpticsPhysicsEngineeringResonatorGas compressorMechanical engineering

Abstract

fetched live from OpenAlex

This paper investigates the aeroacoustic response of an annular duct with co-axial side branches, and examines the effect of several passive countermeasures. The investigated geometry is inspired by the design of the Roll Posts in the Rolls-Royce LiftSystem® engine, which is currently being developed for the Lockheed Martin Joint Strike Fighter aircraft. The effects of design parameters, such as diameter ratio, branch length ratio and thickness of the annular flow on the frequency and resonance intensity of the first acoustic mode are studied experimentally. Numerical simulations of the acoustic mode shapes and frequencies are also performed. The annular flow has been found to excite several acoustic modes, the strongest in all cases being the first acoustic mode, which consists of an antisymmetric quarter wavelength along the length of each branch. The ratios of the branch length and diameter, with respect to the main duct diameter, have been found to have strong effects on the frequency of the acoustic modes. The effects of passive measures to weaken the acoustic coupling between the co-axial branches have been also investigated. These include detuning the co-axial branches, by decreasing the length of one branch, and installing a pair of splitter plates in the annular flow duct.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.472

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 head0.008
GPT teacher head0.230
Teacher spread0.222 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

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