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Record W2092033422 · doi:10.1121/1.2942897

The influence of the acoustic feedback on the fluid-structure interaction within single-reed mouthpieces: A numerical investigation

2007· article· en· W2092033422 on OpenAlexaff
Andrey R. da Silva, Gary Scavone

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2007
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsMouthpieceAcousticsFluid–structure interactionLattice Boltzmann methodsBernoulli's principleStructural acousticsComputer sciencePhysicsMechanicsFinite element method

Abstract

fetched live from OpenAlex

The aim of this article is to complement a previous numerical study conducted to investigate the flow behavior in single-reed woodwind instruments during dynamic regimes with a moving reed [J. Acoust. Soc. Am. 120, 3362 (2006)]. The code uses a fully-coupled scheme based on the lattice Boltzmann method and on a finite-difference scheme to represent the interaction between the reed and the fluid field. The previous study had suggested that, during a dynamic regime and in the absence of acoustic feedback, the flow behavior diverges significantly from what is predicted by the current quasi-stationary models based on the Bernoulli obstruction theory. The present work provides a further investigation on the same topic by taking into account the influence of the acoustic feedback from the bores open end and its interaction with the mean flow within the mouthpiece-reed system. This is achieved by coupling the previous mouthpiece-reed model to a digital waveguide whose reflection function is described by a low-order digital filter to represent the open-end boundary condition. [The first author would like to thank CAPES for supporting his doctoral research.]

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.014
GPT teacher head0.236
Teacher spread0.223 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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