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Record W2971896079 · doi:10.3397/1/376722

Vibration of and radiated acoustic power from a simply-supported panel excited by a turbulent boundary layer excitation at low Mach number

2019· article· en· W2971896079 on OpenAlex
Mansour Jenzri, Olivier Robin, Noureddine Atalia

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

VenueNoise Control Engineering Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMach numberAcousticsBoundary layerSound powerAnechoic chamberVibrationWind tunnelExcitationPhysicsMechanicsSound (geography)

Abstract

fetched live from OpenAlex

The general context of this study is to perform cross-validation of analytical and numerical calculations of vibroacoustic response of panels under a turbulent boundary layer excitation. This article focuses on the specific case of a rectangular aluminum panel with controlled simply-supported boundary conditions, and tested in a lowspeed anechoic wind tunnel (Mach number ≤ 0.12). An underlying goal is to setup a microphone array for directly estimating the radiated sound power from the panel. The vibration of and radiated sound power from the panel are first estimated under a shaker mechanical excitation so as to verify agreement with theoretical calculations and the relevance of the proposed shoebox-shaped microphone array. Similar measurements are then conducted under a turbulent boundary layer excitation. Finally, estimated radiation efficiencies under point mechanical and turbulent excitations are compared. © 2019 Institute of Noise Control Engineering

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 categoriesMeta-epidemiology (narrow)
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 score0.560
Threshold uncertainty score1.000

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)0.0010.000

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 head0.006
GPT teacher head0.206
Teacher spread0.199 · 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