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Record W2082575232 · doi:10.4271/2013-01-2323

Stability-Based Motion Planning for a Modular Morphing Wing

2013· article· en· W2082575232 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2013
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMorphingModular designComputer scienceWingMotion (physics)Motion planningComputer visionArtificial intelligenceEngineeringAerospace engineeringRobot

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Aircraft wing geometry morphing is a technology that has seen recent interest due to demand for aircraft to improve aerodynamic performance for fuel saving. One proposed idea to alter wing geometry is by a modular morphing wing designed through a discretization method and constructed using variable geometry truss mechanisms (VGTM). For each morphing maneuver, there are sixteen possible actuation paths for each VGTM module. This paper proposes a method to find an optimal actuation path from the point of view of the longitudinal static stability.</div><div class="htmlview paragraph">To do so, we locate the aerodynamic center (ac) and the center of gravity (cg) of each VGTM module which is first determined according to its morphed shape. Then, the ac and cg of the entire modular morphing wing can be determined and the stability margin can be computed. The two suggested methods to obtaining the ac for each VGTM module are the integration method and the geometry method. The integration method treats each VGTM module as a full half-wing and applies existing theory for determination of ac for full half-wings, and under similar assumptions, a piece-wise defined equation can be derived where each piece is a VGTM module. The geometry method solves for the location of the ac by determining the location of the mean aerodynamic chord of each VGTM module and further applying airfoil theory. If an assumption is made that the airfoil shape remains constant for all VGTM modules, then a mass axis can be drawn from wing root to wing tip based on the airfoil shape. If the wing has taper, then only airfoil size will change, and a uniform mass distribution will be applied based on the given parameters of each VGTM module and a cg can be determined for the module. The ac and cg of the entire modular morphing wing is determined on the roll axis of the aircraft as a common reference point and longitudinal static stability margin is determined.</div><div class="htmlview paragraph">Ideally, since there are sixteen actuation paths for each VGTM module, a three module morphing wing would have a total of 16<sup>3</sup> permutations of actuation paths for one morphing maneuver. A search loop is then designed to obtain the static margin of all possible actuation paths where the optimal path will be the one with the most stable static margin. To simplify the analysis, all three modules are assumed to morph in unity during a wing morphing maneuver, and the search loop is designed to obtain the static margins and selecting the actuation path of the most stable static margin for the morphing wing. A case study of a three module morphing wing is provided to demonstrate the actuation path selection process as described above.</div></div>

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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