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Record W2415649882 · doi:10.1017/aer.2016.64

Distributed actuation concepts for a morphing aileron device

2016· article· en· W2415649882 on OpenAlexfundno aff
Gianluca Amendola, Ignazio Dimino, Marco Magnifico, Rosario Pecora

Bibliographic record

VenueThe Aeronautical Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsnot available
FundersConsortium de Recherche et d’innovation en Aérospatiale au Québec
KeywordsMorphingAileronActuatorCamber (aerodynamics)AirfoilAerodynamicsComputer scienceEngineeringKinematicsAerospace engineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

ABSTRACT The actuation mechanism is a crucial aspect in the design of morphing structures due to the very stringent requirements involving actuation torque, consumed power, and allowable size and weight. In the framework of the CRIAQ MD0-505 project, novel design strategies are investigated to enable morphing of aeronautical structures. This paper deals with the design of a morphing aileron with the main focus on the actuation technology. The morphing aileron consists of segmented 'finger-like' ribs capable of changing the aerofoil camber in order to match target aerodynamic shapes. In this work, lightweight and compact actuation kinematics driven by electromechanical actuators are investigated to actuate the morphing device. An unshafted distributed servo-electromechanical actuation arrangement is employed to realise the transition from the baseline configuration to a set of target aerodynamic shapes by also withstanding the aerodynamics loads. Numerical investigations are detailed to identify the optimal actuation architecture matching as well as the system integratability and structural compactness.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.021
GPT teacher head0.267
Teacher spread0.245 · 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

Citations42
Published2016
Admission routes1
Has abstractyes

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