MétaCan
Menu
Back to cohort
Record W2982480447 · doi:10.4050/jahs.60.042010

Vehicle Modeling Additions for Off-Axis Improvements in a Real-Time Helicopter Model

2015· article· en· W2982480447 on OpenAlexaboutno aff
Bruce Haycock, Peter R. Grant

Bibliographic record

VenueJournal of the American Helicopter Society · 2015
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsnot available
Fundersnot available
KeywordsAerodynamicsAirfoilHelicopter rotorWakeFlexibility (engineering)Distortion (music)Blade (archaeology)Elasticity (physics)Structural engineeringComputer scienceWake turbulenceRotor (electric)Aerospace engineeringEngineeringSimulationPhysicsMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

An ongoing concern with helicopter simulations is that they often have an incorrect off-axis response to cyclic control inputs when compared with the corresponding flight-test data. The more commonly suggested contributing factors for this discrepancy include the influence of dynamic wake distortion, rotor blade elasticity, and unsteady blade airfoil aerodynamics. A rotor model was developed using a Ritz expansion approach with constrained elastic modes to account for the blade elasticity, as it is computationally compact and efficient and therefore suitable for use in a real-time simulation. The effect of including this blade flexibility on the dynamic response, and in particular the on-axis and off-axis response, of the University of Toronto Institute for Aerospace Studies helicopter models is examined. In addition, the combined effects of dynamic wake distortion, unsteady blade section aerodynamics, and blade flexibility on the dynamic response are examined. The various features were successful in altering the off-axis response, with improvements in some areas, while not disrupting the on-axis response. In some conditions, the magnitude of the resulting change due to flexibility was greater than the differences noted due to the addition of dynamic wake distortion or unsteady aerodynamics.

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 score0.034
Threshold uncertainty score0.537

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 studies0.0000.000
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 head0.017
GPT teacher head0.240
Teacher spread0.223 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Helicopter SocietySame topicVehicle Dynamics and Control SystemsFrench-language works237,207