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Record W1971432865 · doi:10.2514/6.2007-4305

Investigations of Nonlinear Aeroelasticity Using A Reduced Order Fluid Model Based on POD method

2007· article· en· W1971432865 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

Venue18th AIAA Computational Fluid Dynamics Conference · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicModel Reduction and Neural Networks
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAeroelasticityPoint of deliveryNonlinear systemComputer scienceModel order reductionAerodynamicsApplied mathematicsControl theory (sociology)MathematicsEngineeringAlgorithmPhysicsAerospace engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Investigations of nonlinear aeroelasticity of flexible structures subjected to unsteady transonic flows were carried out using a three-dimensional aeroelasticity reduced-order fluid model which is based on the Proper Orthogonal Decomposition (POD). The number of degrees of freedom was reduced from more than 150000 in the full-order model to 200 unknown variables for the reduced-order model (ROM). The dynamic responses of the aeroelastic system, particularly, the wing Limit Cycle Oscillation (LCO) in the transonic regime was simulated. Numerical simulations on the AGARD 445.6 wing show good agreement between the ROM and the original full-order fluid model.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.446
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)0.0000.000

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 head0.036
GPT teacher head0.310
Teacher spread0.274 · 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