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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 OpenAlexaff
Zhengkun Feng, Azzeddine Soulaïmani

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations8
Published2007
Admission routes1
Has abstractyes

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