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Record W2172300304 · doi:10.2514/1.26625

Ground Dynamics Model Validation by Use of Landing Flight Test

2007· article· en· W2172300304 on OpenAlexaff
M. Nadeau Beaulieu, Ruxandra Mihaela Botez, Adrian Hiliuta

Bibliographic record

VenueJournal of Aircraft · 2007
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsTouchdownStiffnessLanding gearCenter of gravityFlight testMoment (physics)Aerospace engineeringMechanicsEngineeringControl theory (sociology)PhysicsStructural engineeringComputer scienceClassical mechanics

Abstract

fetched live from OpenAlex

[Abstract] In this paper, a new formulation for a ground dynamics model of a commercial two-engine helicopter is validated after touchdown. The inputs of the ground dynamics model are the velocities and angles at touchdown, and its outputs are the forces and moments produced by the ground on the helicopter. Expressions for forces and moments, which depend on the ground contact force, the friction coefficient between the skids and the ground, and the system stiffness and damping are determined. . The system stiffness and damping are defined between the touchdown point and the center of gravity in each of the helicopter’s degree of freedom. Expressions for the stiffness, damping and friction coefficients are validated for two kinds of landing situations: one-engine inoperative and autorotation. The ground dynamics of the Bell-427 helicopter model are then used to build and certify a level-D flight simulator.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.205
Teacher spread0.195 · 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

Citations8
Published2007
Admission routes1
Has abstractyes

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