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Record W2212972698 · doi:10.1115/pvp2015-45205

Effect of Cavity Volume on the Flow-Excited Acoustic Resonance of a Shallow Cavity in a Pipe-Line

2015· article· en· W2212972698 on OpenAlexaff
Saber Mohamed, Samir Ziada

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsMcMaster University
Fundersnot available
KeywordsStrouhal numberAcousticsVolume (thermodynamics)PhysicsMechanicsMaterials scienceTurbulenceThermodynamics

Abstract

fetched live from OpenAlex

The effect of cavity volume on the aeroacoustic source generated by fully developed pipe flow through an axisymmetric shallow cavity is investigated experimentally. Nine cavity sizes are studied in three different groups of length, L, to depth, H, ratios (L/H = 1, 2 and 3) with three different cavity volumes for each group of L/H. The Sound Wave Method (SWM) is used to measure the aeroacoustic sources as function of the Strouhal number. This methodology does not require knowledge of the details of the unsteady flow-sound interaction in the cavity region because it considers the cavity as a black box with a dipole sound source or sink. The aeroacoustic source strength and the Strouhal number corresponding to its maximum value are found to increase in a systematic manner as the cavity volume is increased for the same L/H ratio. These results indicate that the aeroacoustic sources of shallow cavities are affected not only by the ratio L/H, but also by the cavity volume.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.226
Teacher spread0.215 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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