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Record W2560172874 · doi:10.1115/detc2016-59163

FEM-BEM Modeling and Experimental Verification of the Vibro-Acoustic Behaviour of a Section of Aircraft Fuselage

2016· article· en· W2560172874 on OpenAlexafffund
Viken Koukounian, Chris K. Mechefske

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFuselageAerodynamicsAnechoic chamberAcousticsFinite element methodLanding gearVibrationAeroacousticsNoise (video)EngineeringComputer scienceMechanical engineeringStructural engineeringAerospace engineeringSound pressurePhysics

Abstract

fetched live from OpenAlex

The aerodynamics of an aircraft in flight impose significant stresses upon the structure. Specifically, the mechanics of fluid flow are highly turbulent and, the layer around the aircraft, is referred to the turbulent boundary layer (TBL). The TBL incites a gradient of pressure fluctuations across the fuselage skin resulting in its vibration, and in turn, the generation of noise inside the passenger cabin. The investigation herein proposes a hybrid FEM-BEM modeling technique to predict the aforementioned vibro-acoustic response and an experimental methodology to verify the results (following ASTM and ANSI international testing standards). The described expectations required construction of an acoustic facility consisting of a reverberation chamber and a semi-anechoic room, the development of DAQ software using LabVIEW, an assembly of DAQ hardware using National Instruments products, and the post-processing of test data using Microsoft Excel. The principal quantity of interest is transmission loss (though insertion loss, absorption and other metrics are also calculated). Two panels (0.04in (40thou) and 0.09in (90thou) in thickness) were simulated and tested (0.01in = 1thou). The calculated error of the proposed methodology is within a maximum of 5dB, with an average of 1dB. Ongoing work is investigating complex constructions and the use of damping materials.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.134

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 head0.010
GPT teacher head0.207
Teacher spread0.198 · 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 designBench or experimental
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
Published2016
Admission routes2
Has abstractyes

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