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Record W4408278182 · doi:10.2514/1.c038116

Modeling of the Six-Degree-of-Freedom Nonlinear Ground Dynamics of the Cessna Citation X

2025· article· en· W4408278182 on OpenAlexafffund
Elias E. Zohreh Nejad, Ilies Rampon, Georges Ghazi, Ruxandra Mihaela Botez

Bibliographic record

VenueJournal of Aircraft · 2025
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsÉcole de Technologie Supérieure
FundersCanada Research ChairsMinistère du Développement Économique, de l’Innovation et de l’Exportation
KeywordsNonlinear systemEuler anglesPhysicsAerospace engineeringStructural engineeringEngineeringSimulationMathematicsGeometry

Abstract

fetched live from OpenAlex

This paper presents a detailed methodology developed at the Laboratory of Applied Research in Active Controls, Avionics, and AeroServoElasticity (LARCASE) to develop the six-degree-of-freedom ground dynamics of the Cessna Citation X (CCX) business aircraft. A highly nonlinear model for ground reaction forces (i.e., horizontal, lateral, and vertical forces) was designed based on an in-house longitudinal ground dynamics model and also considering lateral motion. Furthermore, two new ratios using the angular momentum theorem around the roll and pitch axes were developed to obtain reaction forces, first between the nose and the main landing gears and then between the right and left main landing gears. Finally, based on the landing gear model and its deflections, two trigonometric equations were used to estimate the Euler angles in both roll and pitch motions. The yaw angle was calculated using the sum of ground moments around the [Formula: see text]-axis, incorporating the steering moment. This methodology was tested and validated using the CCX Level-D Research Aircraft Flight Simulator (RAFS). Compared with the RAFS data, the proposed model provided an excellent prediction of the CCX aircraft’s ground performance.

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 score0.055
Threshold uncertainty score0.227

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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