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Record W4403273058 · doi:10.3397/in_2024_3551

Experimental validation of vibration similitude laws for stiffened panels excited by a turbulent boundary layer

2024· article· en· W4403273058 on OpenAlexaff
Xavier Plouseau-Guédé, Alain Berry, Laurent Maxit, Valentin Meyer, Anaïs Mougey, Olivier Robin

Bibliographic record

VenueNOISE-CON proceedings · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSimilitudeOrthotropic materialVibrationBoundary layerStructural engineeringBoundary value problemEngineeringScale (ratio)TurbulenceMechanicsMathematicsComputer scienceAerospace engineeringMathematical analysisPhysicsAcousticsFinite element method

Abstract

fetched live from OpenAlex

Stiffened structures excited by a turbulent boundary layer (TBL) occur in many engineering applications, particularly in the aerospace and naval sectors. The structures encountered in these applications are generally large and complex, and carrying out experiments in order to characterize their vibration response can be costly, time-consuming and difficult. To overcome these constraints, the similitude theory can be used to estimate the response of a full scale structure from the response of a reduced scale structure. A simplifying step to determine these similitude laws for stiffened panels consists in modeling the panel as an equivalent orthotropic panel. Then, using the governing equation of the orthotropic panel and considering the TBL excitation, the vibration similitude laws are derived implying similitude conditions to be respected on geometrical and material properties of the structure as well as flow velocity. In this paper, we present the developments of these similitude laws and an experimental validation for panels in air. The similitude conditions are discussed to adequately choose the properties of scaled stiffened panels. Experimental results are presented to show that the structural response of the reference panel can be recovered from the response of the reduced scale panel using the related scaling laws.

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 score0.008
Threshold uncertainty score0.608

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 communication0.0000.001
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 head0.018
GPT teacher head0.257
Teacher spread0.239 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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