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Record W1972736371 · doi:10.1155/2014/316481

Sound Radiation and Vibration of Composite Panels Excited by Turbulent Flow: Analytical Prediction and Analysis

2014· article· en· W1972736371 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueShock and Vibration · 2014
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsCarleton University
Fundersnot available
KeywordsComposite numberVibrationSandwich-structured compositeNoise (video)IsotropyAcousticsFlow (mathematics)Structural engineeringStructural acousticsAeroacousticsTurbulenceEngineeringSound pressureMaterials scienceComposite materialComputer scienceMechanicsPhysicsOptics

Abstract

fetched live from OpenAlex

The present study investigates the vibration and sound radiation by panels exited by turbulent flow and by random noise. Composite and aluminum panels are analyzed through a developed analytical framework. The main objective of this study is to identify the difference between the vibroacoustic behaviour of these two types of panels. This topic is of particular importance, given the growing interest in applying composite materials for the construction of aircraft structures, in parts where aluminum panels were traditionally being used. An original mathematical framework is presented for the prediction of noise and vibration for composite panels. Results show the effect of panel size, thickness of core, and thickness of face layers on the predictions. Smaller composite panels generally produced lower levels of sound and vibration than longer and wider composite panels. Compared with isotropic panels, the composite panels analyzed generated lower noise levels, although it was observed that noise level was amplified at certain frequencies.

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.

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 score0.474
Threshold uncertainty score0.416

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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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