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Record W2038385820 · doi:10.2514/1.27602

Aeroelastic Solutions Using the Nonlinear Frequency-Domain Method

2008· article· en· W2038385820 on OpenAlexafffund
Farid Kachra, Siva Nadarajah

Bibliographic record

VenueAIAA Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransonicAeroelasticityAirfoilFlutterNonlinear systemFrequency domainTime domainComputational fluid dynamicsDomain (mathematical analysis)Benchmark (surveying)AerodynamicsComputer scienceSwept wingMathematicsApplied mathematicsControl theory (sociology)Mathematical analysisMechanicsPhysicsGeology

Abstract

fetched live from OpenAlex

In this work, both fully implicit time-domain and nonlinear frequency-domain methods are used to compute aeroelastic solutions in transonic flows. Specifically, flutter boundaries for a two-dimensional NACA64A010 airfoil are calculated and compared with preexisting numerical results. The second-order backward-difference time-accurate scheme will serve as our numerical benchmark when determining the computational efficiency of the nonlinear frequency-domain method. Comparable results between the time-domain and nonlinear frequency-domain approaches will further justify the nonlinear frequency-domain method as an efficient alternative to the study of unsteady periodic problems. A temporal resolution study will establish the required number of modes or time steps per period required for unsteady transonic flows.

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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.249
Teacher spread0.225 · 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
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

Citations10
Published2008
Admission routes2
Has abstractyes

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