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Record W2594199671 · doi:10.2316/p.2016.848-048

Morphing wing application on Hydra Technologies UAS-S4

2017· article· en· W2594199671 on OpenAlexfundno aff
Marine Segui, Oliviu Şugar Gabor, Andreea Koreanschi, Ruxandra Mihaela Botez

Bibliographic record

VenueUniversity of Salford Institutional Repository (University of Salford) · 2017
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMinistère du Développement Économique, de l’Innovation et de l’Exportation
KeywordsMorphingWingAerodynamicsAerospace engineeringLift coefficientLift-to-drag ratioCruiseVortexComputer scienceAirfoilComputationAngle of attackAcousticsAeronauticsControl theory (sociology)Marine engineeringEngineeringPhysicsMechanicsArtificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

This paper presents the aerodynamic results of a morphing wing study performed on the UAS S4 Éhecatl from Hydra Technologies. Only the cruise phase of the aircraft was considered (constant altitude and constant speed). The difference, from an aerodynamic point of view, between the morphing wing and the original wing was emphasized by computing and comparing their longitudinal aerodynamic coefficients (drag and lift). The computation of the aerodynamic characteristics was done using tornado with the Vortex Lattice Method.

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 score0.226
Threshold uncertainty score0.986

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.006
GPT teacher head0.163
Teacher spread0.158 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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