MétaCan
Menu
Back to cohort
Record W4307702734 · doi:10.3389/fmech.2022.1034555

Sound transmission through baffled multilayered curved shells using a transfer matrix method

2022· article· en· W4307702734 on OpenAlexafffund
A. Parrinello, W. Belgacem, Sebastian Ghinet, Noureddine Atalla

Bibliographic record

VenueFrontiers in Mechanical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsNational Research Council CanadaUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaConsortium de Recherche et d’innovation en Aérospatiale au Québec
KeywordsTransfer matrixBafflePoromechanicsTransfer-matrix method (optics)Matrix (chemical analysis)Finite element methodMechanicsBoundary element methodAcousticsSound transmission classStiffness matrixAcoustic radiationMaterials sciencePhysicsStructural engineeringOpticsEngineeringRadiationPorous mediumComputer scienceComposite material

Abstract

fetched live from OpenAlex

The present work describes the use of a transfer matrix method to define the acoustic behavior of multilayered and periodic baffled curved shells consisting of a generic arrangement of homogeneous and heterogeneous periodic layers of various nature (fluid, solid, and poroelastic). The dynamic stiffness matrix of a unit cell is manipulated in order to derive the through-radius transfer matrix of a cylindrical periodic layer. Thus, the acoustic radiation or transmission of multilayered shells can be assessed. The blocked pressure field due to an incident plane wave is defined by taking into account the infinite rigid baffle by means of a two-dimensional boundary element model. Analytical expressions for the cylindrical acoustic impedances are utilized to define the coupling with the bounding fluid media. Furthermore, a one-dimensional windowing technique is adopted to account for the finite length of the shells. The proposed approach is validated by systematic comparison with a full finite-boundary element method.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.282
Teacher spread0.260 · 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
GenreMethods

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

Citations4
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Mechanical EngineeringSame topicAcoustic Wave Phenomena ResearchFrench-language works237,207