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Record W2332127784 · doi:10.2514/6.2009-2862

Dynamics Modeling for an Unmanned, Unstable, Fin-Less Airship

2009· article· en· W2332127784 on OpenAlexaff
Prashant Peddiraju, Torsten Liesk, Meyer Nahon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Energy Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsAerospace engineeringFinDynamics (music)Computer scienceAerodynamicsAeronauticsEnvironmental scienceControl theory (sociology)EngineeringPhysicsControl (management)Acoustics

Abstract

fetched live from OpenAlex

The research described in this paper relates to a platform under development at Quanser Inc. that embodies a novel small airship: the highly-maneuverable almost-lighter-than-air vehicle (ALTAV). Its marginal stability and redundant actuation make the problem of controller design particularly important and challenging. A high-fidelity mathematical model has been developed to accurately represent the behavior of the airship under the effect of winds and other disturbances. The equations of motion have been derived taking into account the effects of added-mass and wind. Hull forces for a 360◦ range of angle of attack have been estimated by adapting an existing semi-empirical method for slender bodies. A simple thruster model developed from experimental data has been shown to provide good agreement with actual thrust measurements under static conditions. Finally, simulation results are presented to highlight the importance of closed-loop control and directions for future work are discussed.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.022

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.213
Teacher spread0.192 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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