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Record W2313168366 · doi:10.2514/6.2005-332

Aerodynamic Optimisation of a Realistic Aircraft Wing

2005· article· en· W2313168366 on OpenAlexaff
Anas Bentamy, François Guibault, Jean‐Yves Trépanier

Bibliographic record

Venue43rd AIAA Aerospace Sciences Meeting and Exhibit · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Analysis Techniques
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsAerodynamicsWingParametrization (atmospheric modeling)Representation (politics)Surface (topology)Computer scienceSet (abstract data type)InverseWing configurationAerospace engineeringMathematicsEngineeringGeometryPhysics

Abstract

fetched live from OpenAlex

This paper presents an extended use of the NURBS paradigm for the efcient parametrization of a realistic aircraft wing, to represent a complex three-dimensional wing surface in terms of a relatively small set of design variables. The aim is to illustrate the method using NURBS geometric representation of a wing surface satisfying manufacturing constraints and its use in the r st stage of aerodynamic design. The paper describes a methodology for providing a smooth geometry and demonstrates the potential of such approach in an inverse design problem.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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 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

Citations7
Published2005
Admission routes1
Has abstractyes

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